def build_problem(mydirectory, myfilebase, myend, cost="poisson"):
monitor_efficiency = 0.1
resolution = 0.001
scale = resolution**2 / monitor_efficiency
scale = 1e-6
M = Peaks(
[
Gaussian(name="G1-"),
Gaussian(name="G2-"),
#Gaussian(name="G3-"),
#Gaussian(name="G4-"),
Background()
],
scale,
data=read_data(mydirectory, myfilebase, myend),
#cost='poisson',
cost=cost,
)
# Peak intensity and background
background = 1
M.parts[-1].C.value = background
M.parts[-1].C.range(0, 1000)
for peak in M.parts[:-1]:
peak.A.value = 1. / (len(M.parts) - 1) # Equal size peaks
peak.A.range(0, 1)
peak1 = M.parts[0]
if 0:
# Peak centers are independent
for peak in M.parts[:-1]:
peak.xc.range(0.45, 0.55)
peak.yc.range(-0.55, -0.4)
else:
# Peak centers lie on a line
alpha = Parameter(45.0, name="alpha")
alpha.range(-90., 90.)
peak1.xc.range(0.40, 0.55)
peak1.yc.range(0.40, 0.55)
#peak1.yc.range(-0.55,-0.4)
for i, peak in enumerate(M.parts[1:-1]):
delta = Parameter(.0045, name="delta-%d" % (i + 1))
delta.range(0.00, 0.03)
peak.xc = peak1.xc + delta * pmath.cosd(alpha)
peak.yc = peak1.yc + delta * pmath.sind(alpha)
# Initial values
cx, cy = 0.4996 - 0.4957, -0.4849 + 0.4917
alpha.value = np.degrees(np.arctan2(cy, cx))
delta.value = np.sqrt(cx**2 + cy**2)
peak1.xc.value, peak1.yc.value = 0.4957, 0.4917
# Peak location and shape
dx, dy = 0.4997 - 0.4903, -0.4969 + 0.4851
dxm, dym = 0.4951 - 0.4960, -0.4941 + 0.4879
peak1.s1.value = np.sqrt(dx**2 + dy**2) / 2.35 / 2
peak1.s2.value = np.sqrt(dxm**2 + dym**2) / 2.35 / 2
peak1.theta.value = np.degrees(np.arctan2(dy, dx))
# Peak shape is the same across all peaks
peak1.s1.range(0.001, 0.010)
peak1.s2.range(0.001, 0.010)
peak1.theta.range(-90, 90)
for peak in M.parts[1:-1]:
peak.s1 = peak1.s1
peak.s2 = peak1.s2
peak.theta = peak1.theta
if 1:
print "shape", peak1.s1.value, peak1.s2.value, peak1.theta.value
print "centers alpha,delta", alpha.value, delta.value
print "centers",(peak1.xc.value,peak1.yc.value),\
(M.parts[1].xc.value,M.parts[1].yc.value)
return FitProblem(M)
def build_problem(mydirectory, myfilebase, myend):
M = Peaks(
[
Gaussian(name="G1-"),
Gaussian(name="G2-"),
#Gaussian(name="G3-"),
#Gaussian(name="G4-"),
Background()
],
*read_data(mydirectory, myfilebase, myend))
background = np.min(M.data)
background += np.sqrt(background)
signal = np.sum(M.data) - M.data.size * background
M.parts[-1].C.value = background
M.parts[-1].C.range(0, 200)
peak1 = M.parts[0]
if 0:
# Peak centers are independent
for peak in M.parts[:-1]:
peak.xc.range(0.45, 0.55)
peak.yc.range(-0.55, -0.4)
else:
# Peak centers lie on a line
alpha = Parameter(45.0, name="alpha")
alpha.range(-90., 90.)
peak1.xc.range(0.40, 0.55)
peak1.yc.range(0.40, 0.55)
#peak1.yc.range(-0.55,-0.4)
for i, peak in enumerate(M.parts[1:-1]):
delta = Parameter(.0045, name="delta-%d" % (i + 1))
delta.range(0.00, 0.03)
peak.xc = peak1.xc + delta * pmath.cosd(alpha)
peak.yc = peak1.yc + delta * pmath.sind(alpha)
# Initial values
cx, cy = 0.4996 - 0.4957, -0.4849 + 0.4917
alpha.value = np.degrees(np.arctan2(cy, cx))
delta.value = np.sqrt(cx**2 + cy**2)
peak1.xc.value, peak1.yc.value = 0.4957, -0.4917
# Initial values
for peak in M.parts[:-1]:
peak.A.value = signal / (len(M.parts) - 1) # Equal size peaks
dx, dy = 0.4997 - 0.4903, -0.4969 + 0.4851
dxm, dym = 0.4951 - 0.4960, -0.4941 + 0.4879
peak1.s1.value = np.sqrt(dx**2 + dy**2) / 2.35 / 2
peak1.s2.value = np.sqrt(dxm**2 + dym**2) / 2.35 / 2
peak1.theta.value = np.degrees(np.arctan2(dy, dx))
# Peak intensity varies
for peak in M.parts[:-1]:
peak.A.range(0.10 * signal, 1.1 * signal)
# Peak shape is the same across all peaks
peak1.s1.range(0.001, 0.010)
peak1.s2.range(0.001, 0.004)
peak1.theta.range(0, 90)
for peak in M.parts[1:-1]:
peak.s1 = peak1.s1
peak.s2 = peak1.s2
peak.theta = peak1.theta
if 1:
print "shape", peak1.s1.value, peak1.s2.value, peak1.theta.value
print "centers alpha,delta", alpha.value, delta.value
print "centers",(peak1.xc.value,peak1.yc.value),\
(M.parts[1].xc.value,M.parts[1].yc.value)
return FitProblem(M)
def build_problem():
M = Peaks([Gaussian(name="G1-"),
Gaussian(name="G2-"),
#Gaussian(name="G3-"),
#Gaussian(name="G4-"),
Background()],
*read_data())
background = np.min(M.data)
background += np.sqrt(background)
signal = np.sum(M.data) - M.data.size*background
M.parts[-1].C.value = background
peak1 = M.parts[0]
if 0:
# Peak centers are independent
for peak in M.parts[:-1]:
peak.xc.range(0.45,0.55)
peak.yc.range(-0.55,-0.4)
else:
# Peak centers lie on a line
theta=Parameter(45, name="theta")
theta.range(0,90)
peak1.xc.range(0.45,0.55)
peak1.yc.range(-0.55,-0.4)
for i,peak in enumerate(M.parts[1:-1]):
delta=Parameter(.0045, name="delta-%d"%(i+1))
delta.range(0.0,0.015)
peak.xc = peak1.xc + delta*pmath.cosd(theta)
peak.yc = peak1.yc + delta*pmath.sind(theta)
# Initial values
cx, cy = 0.4996-0.4957, -0.4849+0.4917
theta.value = np.degrees(np.arctan2(cy,cx))
delta.value = np.sqrt(cx**2+cy**2)
peak1.xc.value,peak1.yc.value = 0.4957,-0.4917
# Initial values
for peak in M.parts[:-1]:
peak.A.value = signal/(len(M.parts)-1) # Equal size peaks
dx, dy = 0.4997-0.4903, -0.4969+0.4851
dxm, dym = 0.4951-0.4960, -0.4941+0.4879
peak1.s1.value = np.sqrt(dx**2+dy**2)/2.35/2
peak1.s2.value = np.sqrt(dxm**2+dym**2)/2.35/2
peak1.theta.value = np.degrees(np.arctan2(dy,dx))
# Peak intensity varies
for peak in M.parts[:-1]:
peak.A.range(0.25*signal,1.1*signal)
# Peak shape is the same across all peaks
peak1.s1.range(0.002,0.02)
peak1.s2.range(0.001,0.02)
peak1.theta.range(-90, -0)
for peak in M.parts[1:-1]:
peak.s1 = peak1.s1
peak.s2 = peak1.s2
peak.theta = peak1.theta
if 1:
print "shape",peak1.s1.value,peak1.s2.value,peak1.theta.value
print "centers theta,delta",theta.value,delta.value
print "centers",(peak1.xc.value,peak1.yc.value),\
(M.parts[1].xc.value,M.parts[1].yc.value)
return FitProblem(M)
def build_problem():
M = Peaks(
[
Gaussian(name="G1-"),
Gaussian(name="G2-"),
#Gaussian(name="G3-"),
#Gaussian(name="G4-"),
Background()
],
*read_data())
background = np.min(M.data)
background += np.sqrt(background)
signal = np.sum(M.data) - M.data.size * background
M.parts[-1].C.value = background
peak1 = M.parts[0]
peak1.xc.range(0.45, 0.55)
peak1.yc.range(-0.55, -0.4)
peak1.xc.value = 0.500
peak1.yc.value = -0.485
if 0:
# Peak centers are independent
for peak in M.parts[1:-1]:
peak.xc.range(0.45, 0.55)
peak.yc.range(-0.55, -0.4)
M.parts[1].xc.value = 0.495
M.parts[1].yc.value = -0.495
else:
# Peak centers lie on a line
theta = Parameter(45, name="theta")
theta.range(0, 90)
for i, peak in enumerate(M.parts[1:-1]):
delta = Parameter(0.0045, name="delta-%d" % (i + 1))
delta.range(0.0, 0.015)
peak.xc = peak1.xc + delta * cosd(theta)
peak.yc = peak1.yc + delta * sind(theta)
# Initial values
cx, cy = 0.4996 - 0.4957, -0.4849 + 0.4917
theta.value = np.degrees(np.arctan2(cy, cx))
delta.value = np.sqrt(cx**2 + cy**2)
# Initial values
for peak in M.parts[:-1]:
peak.A.value = signal / (len(M.parts) - 1) # Equal size peaks
dx, dy = 0.4997 - 0.4903, -0.4969 + 0.4851
dxm, dym = 0.4951 - 0.4960, -0.4941 + 0.4879
peak1.s1.value = np.sqrt(dx**2 + dy**2) / 2.35 / 2
peak1.s2.value = np.sqrt(dxm**2 + dym**2) / 2.35 / 2
peak1.theta.value = np.degrees(np.arctan2(dy, dx))
# Peak intensity varies
for peak in M.parts[:-1]:
peak.A.range(0.1 * signal, 1.1 * signal)
peak1.s1.range(0.002, 0.02)
peak1.s2.range(0.001, 0.02)
peak1.theta.range(-90, -0)
if 1:
# Peak shape is the same across all peaks
for peak in M.parts[1:-1]:
peak.s1 = peak1.s1
peak.s2 = peak1.s2
peak.theta = peak1.theta
else:
for peak in M.parts[1:-1]:
peak.s1.range(*peak1.s1.bounds.limits)
peak.s2.range(*peak1.s2.bounds.limits)
peak.theta.range(*peak1.theta.bounds.limits)
if 1:
M.parts[-1].C.pmp(100.0)
if 1:
for peak in M.parts[:-1]:
peak.s1.value = 0.006
peak.s2.value = 0.002
peak.theta.value = -60.0
peak.A.value = signal / 2
if 0:
print("shape", peak1.s1.value, peak1.s2.value, peak1.theta.value)
print("centers theta,delta", theta.value, delta.value)
print("centers", (peak1.xc.value, peak1.yc.value),
(M.parts[1].xc.value, M.parts[1].yc.value))
return FitProblem(M)