def profile(self, Pz):
thickness = self.thickness.value
mbelow, tbelow = 0, (self.thetaM[0].value
if self.thetaM else DEFAULT_THETA_M)
mabove, tabove = 0, (self.thetaM[-1].value
if self.thetaM else DEFAULT_THETA_M)
z = np.sort([0] + [p.value for p in self.z] + [1]) * thickness
rhoM = np.hstack((mbelow, [p.value for p in self.rhoM], mabove))
PrhoM = monospline(z, rhoM, Pz)
if np.any(np.isnan(PrhoM)):
print("in mono")
print("z %s" % str(z))
print("p %s" % str([p.value for p in self.z]))
if len(self.thetaM) > 1:
thetaM = np.hstack(
(tbelow, [p.value for p in self.thetaM], tabove))
PthetaM = monospline(z, thetaM, Pz)
elif len(self.thetaM) == 1:
PthetaM = np.full_like(PrhoM, self.thetaM.value)
else:
PthetaM = np.full_like(PrhoM, DEFAULT_THETA_M)
return PrhoM, PthetaM
def profile(self, Pz, below, above):
thickness = self.thickness.value
rbelow, ibelow = below
rabove, iabove = above
z = sort([0] + [p.value for p in self.z] + [1]) * thickness
rho = hstack((rbelow, [p.value for p in self.rho], rabove))
Prho = monospline(z, rho, Pz)
if len(self.irho) > 0:
irho = hstack((ibelow, [p.value for p in self.irho], iabove))
Pirho = monospline(z, irho, Pz)
else:
Pirho = 0 * Prho
return Prho, Pirho
def profile(self, Pz, below, above):
thickness = self.thickness.value
rbelow,ibelow = below
rabove,iabove = above
z = sort([0]+[p.value for p in self.z]+[1])*thickness
rho = hstack((rbelow, [p.value for p in self.rho], rabove))
Prho = monospline(z, rho, Pz)
if len(self.irho)>0:
irho = hstack((ibelow, [p.value for p in self.irho], iabove))
Pirho = monospline(z, irho, Pz)
else:
Pirho = 0*Prho
return Prho,Pirho
def profile(self, Pz):
thickness = self.thickness.value
z,p = [hstack( (0, cumsum(asarray([v.value for v in vector],'d'))) )
for vector in (self.dz, self.dp)]
if p[-1] == 0: p[-1] = 1
p *= 1/p[-1]
z *= thickness/z[-1]
profile = clip(monospline(z, p, Pz), 0, 1)
return profile
def profile(self, Pz):
thickness = self.thickness.value
z, p = [hstack((0, cumsum(asarray([v.value for v in vector], 'd'))))
for vector in (self.dz, self.dp)]
if p[-1] == 0: p[-1] = 1
p *= 1/p[-1]
z *= thickness/z[-1]
profile = clip(monospline(z, p, Pz), 0, 1)
return profile
def profile(self, Pz, thickness):
mbelow, tbelow = 0, (self.thetaM[0].value if self.thetaM else 270)
mabove, tabove = 0, (self.thetaM[-1].value if self.thetaM else 270)
z = numpy.sort([0] + [p.value for p in self.z] + [1]) * thickness
rhoM = numpy.hstack((mbelow, [p.value for p in self.rhoM], mabove))
PrhoM = monospline(z, rhoM, Pz)
if numpy.any(numpy.isnan(PrhoM)):
print("in mono with bad PrhoM")
print("z %s" % str(z))
print("p %s" % str([p.value for p in self.z]))
if len(self.thetaM) > 1:
thetaM = numpy.hstack((tbelow, [p.value for p in self.thetaM], tabove))
PthetaM = monospline(z, thetaM, Pz)
elif len(self.thetaM) == 1:
PthetaM = self.thetaM.value * numpy.ones_like(PrhoM)
else:
PthetaM = 270 * numpy.ones_like(PrhoM)
return PrhoM, PthetaM
def profile(self, Pz, thickness):
mbelow, tbelow = 0, (self.thetaM[0].value if self.thetaM else 270)
mabove, tabove = 0, (self.thetaM[-1].value if self.thetaM else 270)
z = numpy.sort([0] + [p.value for p in self.z] + [1]) * thickness
rhoM = numpy.hstack((mbelow, [p.value for p in self.rhoM], mabove))
PrhoM = monospline(z, rhoM, Pz)
if numpy.any(numpy.isnan(PrhoM)):
print("in mono with bad PrhoM")
print("z %s" % str(z))
print("p %s" % str([p.value for p in self.z]))
if len(self.thetaM) > 1:
thetaM = numpy.hstack(
(tbelow, [p.value for p in self.thetaM], tabove))
PthetaM = monospline(z, thetaM, Pz)
elif len(self.thetaM) == 1:
PthetaM = self.thetaM.value * numpy.ones_like(PrhoM)
else:
PthetaM = 270 * numpy.ones_like(PrhoM)
return PrhoM, PthetaM
def randomspline(n,p,a,b,nsteps=100,distribution=numpy.random.random):
"""
increasing monotonically only
n control points, x random points on the range [a,b) where c is the step
"""
#x = numpy.arange(a,b,step)
#xt = numpy.random.uniform(min(x),max(x),p)
Cx = numpy.cumsum(numpy.random.exponential(size=n))
Cx = Cx/Cx[-1]*(b-a)+a
Cy = distribution(Cx.shape)
xt = numpy.linspace(min(Cx),max(Cx),p)
#print (xt,monospline(Cx,Cy,xt),Cx,Cy)
return (xt,monospline(Cx,Cy,xt),Cx,Cy)
def render(self, probe, slabs):
interface = self.interface.value
below_rho, below_irho = self.below.sld(probe)
above_rho, above_irho = self.above.sld(probe)
z = hstack((0, cumsum([v.value for v in self.dz])))
p = hstack((0, cumsum([v.value for v in self.dp])))
thickness = z[-1]
if p[-1] == 0: p[-1] = 1
p /= p[-1]
Pw, Pz = slabs.microslabs(z[-1])
profile = monospline(z, p, Pz)
Pw, profile = util.merge_ends(Pw, profile, tol=1e-3)
Prho = (1 - profile) * below_rho + profile * above_rho
Pirho = (1 - profile) * below_irho + profile * above_irho
slabs.extend(rho=[Prho], irho=[Pirho], w=Pw)
def render(self, probe, slabs):
interface = self.interface.value
below_rho,below_irho = self.below.sld(probe)
above_rho,above_irho = self.above.sld(probe)
z = hstack( (0, cumsum([v.value for v in self.dz])) )
p = hstack( (0, cumsum([v.value for v in self.dp])) )
thickness = z[-1]
if p[-1] == 0: p[-1] = 1
p /= p[-1]
Pw,Pz = slabs.microslabs(z[-1])
profile = monospline(z, p, Pz)
Pw,profile = util.merge_ends(Pw, profile, tol=1e-3)
Prho = (1-profile)*below_rho + profile*above_rho
Pirho = (1-profile)*below_irho + profile*above_irho
slabs.extend(rho=[Prho], irho=[Pirho], w=Pw)
def theory(self):
return monospline(self.Cx, self.Cy, self.xt)
def theory(self):
return monospline([q.x.value for q in self.cpoints], [q.y.value for q in self.cpoints], self.xt)
def spline(x, x1, x2, x3, x4, x5, x6, x7, x8, y1, y2, y3, y4, y5, y6, y7, y8):
return mon.monospline([x1, x2, x3, x4, x5, x6, x7, x8], [y1, y2, y3, y4, y5, y6, y7, y8], x)
import numpy as np
from bumps.names import *
import bumps.mono as mon
import matplotlib.pyplot as plt
#
def spline(x, x1, x2, x3, x4, x5, x6, x7, x8, y1, y2, y3, y4, y5, y6, y7, y8):
return mon.monospline([x1, x2, x3, x4, x5, x6, x7, x8], [y1, y2, y3, y4, y5, y6, y7, y8], x)
#def spline(x, *points):
# return mon.monospline(points[slice(0, int(len(points)/2))], points[slice(int(len(points)/2), len(points))], [x])
x = np.linspace(5, 10, 8)
y = np.random.random(8)
#y = [4.0,4.0,6.3,8.03,9.6,11.9]
y = [.5, .245, .267, .5, .8, .3, .4, .9]
xt = np.linspace(5,10,50)
yt = mon.monospline(x, y, xt)
dyt = np.ones_like(yt) * 0.01
plt.plot(x, y, 'o')
#plt.plot(xt, yt)
#plt.show()
p = [5,6,7,8,9,0.1,0.2,0.3,0.4,0.5]
#M = Curve(spline, xt, yt , dyt,2x1=5, x2=6 , x3=7, x4=8, x5=9, y1=0.1, y2=0.2, y3=0.3, y4=0.4, y5=.5)
M = Curve(spline, xt, yt , dyt, x1=5, x2=6 , x3=7, x4=7.5, x5=8, x6=8.5, x7=9, x8=9.5, y1=0.1, y2=0.2, y3=0.3, y4=0.4, y5=.5, y6=.6, y7=.7, y8=.8)
M.x1.range(5, 10)
M.x2.range(5, 10)
M.x3.range(5, 10)
M.x4.range(5, 10)
M.x5.range(5, 10)
M.x6.range(5, 10)
M.x7.range(5, 10)
