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Commit 0f30025f authored by Wuttke, Joachim's avatar Wuttke, Joachim
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[minor] Correct fixedP handling for Pt example () 

Merging branch 'minor'  into 'main'.

See merge request !1957
parents afc4e946 e5bcd197
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1 merge request!1957Correct fixedP handling for Pt example
Pipeline #112370 passed
Stage: build
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auto/Examples/fit/specular/Pt_layer_fit.py
+ 8
− 6
View file @ 0f30025f
......@@ -122,7 +122,7 @@ def plot(q, r, exp, P):
if __name__ == '__main__':
# Parameters and bounds.
# Parameters and bounds:
fixedPnB = {
# to keep some parameters fixed, move lines here from startPnB
......@@ -139,6 +139,8 @@ if __name__ == '__main__':
fixedP = {d: v[0] for d, v in fixedPnB.items()}
initialP = {d: v[0] for d, v in startPnB.items()}
# Set q axis, load data:
qmin = 0.18
qmax = 2.4
......@@ -146,12 +148,12 @@ if __name__ == '__main__':
qzs = np.linspace(qmin, qmax, 1500)
# Plot data with initial model
# Plot data with initial model:
r = get_simulation(qzs, initialP).simulate().npArray()
r = get_simulation(qzs, initialP | fixedP).simulate().npArray()
plot(qzs, r, data, initialP)
# Fit
# Fit:
Q, R, dR = (data[0], data[1], data[2])
......@@ -171,12 +173,12 @@ if __name__ == '__main__':
finalP = {r.name(): r.value for r in result.parameters()}
# Print and plot fit outcome
# Print and plot fit outcome:
print("Fit Result:")
print(finalP)
r = get_simulation(qzs, finalP).simulate().npArray()
r = get_simulation(qzs, finalP | fixedP).simulate().npArray()
plot(qzs, r, data, finalP)
plt.show()
auto/Examples/fit/specular/Specular1Par.py
+ 3
− 7
View file @ 0f30025f
......@@ -7,9 +7,7 @@ We fit just one parameter, the thickness of the Ti layers,
which has an original value of 30 angstroms.
"""
import os
import numpy as np
import bornagain as ba
import bornagain as ba, numpy as np, os
from bornagain import angstrom, ba_fitmonitor
......@@ -18,6 +16,7 @@ def load_data():
data_fname = os.path.join(datadir, "specular/genx_alternating_layers.dat.gz")
expdata = np.loadtxt(data_fname, usecols=(0, 1), skiprows=3)
# convert double incident angle (degs) to incident angle (radians)
expdata[:, 0] *= np.pi/360
......@@ -46,7 +45,7 @@ def get_sample(P):
def get_simulation(P):
scan = ba.AlphaScan(ba.ListScan("", exp_x))
scan = ba.AlphaScan(ba.ListScan("alpha (rad)", exp_x))
scan.setWavelength(1.54*angstrom)
sample = get_sample(P)
......@@ -54,7 +53,6 @@ def get_simulation(P):
if __name__ == '__main__':
global exp_x
exp_x, exp_y = load_data()
P = ba.Parameters()
......@@ -71,5 +69,3 @@ if __name__ == '__main__':
result = minimizer.minimize(fit_objective.evaluate, P)
fit_objective.finalize(result)
plot_observer.show()
auto/MiniExamples/fit/specular/Pt_layer_fit.py
+ 8
− 6
View file @ 0f30025f
......@@ -122,7 +122,7 @@ def plot(q, r, exp, P):
if __name__ == '__main__':
# Parameters and bounds.
# Parameters and bounds:
fixedPnB = {
# to keep some parameters fixed, move lines here from startPnB
......@@ -139,6 +139,8 @@ if __name__ == '__main__':
fixedP = {d: v[0] for d, v in fixedPnB.items()}
initialP = {d: v[0] for d, v in startPnB.items()}
# Set q axis, load data:
qmin = 0.18
qmax = 2.4
......@@ -146,12 +148,12 @@ if __name__ == '__main__':
qzs = np.linspace(qmin, qmax, 1500)
# Plot data with initial model
# Plot data with initial model:
r = get_simulation(qzs, initialP).simulate().npArray()
r = get_simulation(qzs, initialP | fixedP).simulate().npArray()
plot(qzs, r, data, initialP)
# Fit
# Fit:
Q, R, dR = (data[0], data[1], data[2])
......@@ -171,12 +173,12 @@ if __name__ == '__main__':
finalP = {r.name(): r.value for r in result.parameters()}
# Print and plot fit outcome
# Print and plot fit outcome:
print("Fit Result:")
print(finalP)
r = get_simulation(qzs, finalP).simulate().npArray()
r = get_simulation(qzs, finalP | fixedP).simulate().npArray()
plot(qzs, r, data, finalP)
plt.show()
auto/MiniExamples/fit/specular/Specular1Par.py
+ 3
− 7
View file @ 0f30025f
......@@ -7,9 +7,7 @@ We fit just one parameter, the thickness of the Ti layers,
which has an original value of 30 angstroms.
"""
import os
import numpy as np
import bornagain as ba
import bornagain as ba, numpy as np, os
from bornagain import angstrom, ba_fitmonitor
......@@ -18,6 +16,7 @@ def load_data():
data_fname = os.path.join(datadir, "specular/genx_alternating_layers.dat.gz")
expdata = np.loadtxt(data_fname, usecols=(0, 1), skiprows=3)
# convert double incident angle (degs) to incident angle (radians)
expdata[:, 0] *= np.pi/360
......@@ -46,7 +45,7 @@ def get_sample(P):
def get_simulation(P):
scan = ba.AlphaScan(ba.ListScan("", exp_x))
scan = ba.AlphaScan(ba.ListScan("alpha (rad)", exp_x))
scan.setWavelength(1.54*angstrom)
sample = get_sample(P)
......@@ -54,7 +53,6 @@ def get_simulation(P):
if __name__ == '__main__':
global exp_x
exp_x, exp_y = load_data()
P = ba.Parameters()
......@@ -71,5 +69,3 @@ if __name__ == '__main__':
result = minimizer.minimize(fit_objective.evaluate, P)
fit_objective.finalize(result)
plot_observer.show()
rawEx/fit/specular/Pt_layer_fit.py
+ 8
− 6
View file @ 0f30025f
......@@ -122,7 +122,7 @@ def plot(q, r, exp, P):
if __name__ == '__main__':
# Parameters and bounds.
# Parameters and bounds:
fixedPnB = {
# to keep some parameters fixed, move lines here from startPnB
......@@ -139,6 +139,8 @@ if __name__ == '__main__':
fixedP = {d: v[0] for d, v in fixedPnB.items()}
initialP = {d: v[0] for d, v in startPnB.items()}
# Set q axis, load data:
qmin = 0.18
qmax = 2.4
......@@ -146,12 +148,12 @@ if __name__ == '__main__':
qzs = np.linspace(qmin, qmax, 1500)
# Plot data with initial model
# Plot data with initial model:
r = get_simulation(qzs, initialP).simulate().npArray()
r = get_simulation(qzs, initialP | fixedP).simulate().npArray()
plot(qzs, r, data, initialP)
# Fit
# Fit:
Q, R, dR = (data[0], data[1], data[2])
......@@ -171,12 +173,12 @@ if __name__ == '__main__':
finalP = {r.name(): r.value for r in result.parameters()}
# Print and plot fit outcome
# Print and plot fit outcome:
print("Fit Result:")
print(finalP)
r = get_simulation(qzs, finalP).simulate().npArray()
r = get_simulation(qzs, finalP | fixedP).simulate().npArray()
plot(qzs, r, data, finalP)
plt.show()
rawEx/fit/specular/Specular1Par.py
+ 3
− 5
View file @ 0f30025f
......@@ -7,9 +7,7 @@ We fit just one parameter, the thickness of the Ti layers,
which has an original value of 30 angstroms.
"""
import os
import numpy as np
import bornagain as ba
import bornagain as ba, numpy as np, os
from bornagain import angstrom, ba_fitmonitor
......@@ -18,6 +16,7 @@ def load_data():
data_fname = os.path.join(datadir, "specular/genx_alternating_layers.dat.gz")
expdata = np.loadtxt(data_fname, usecols=(0, 1), skiprows=3)
# convert double incident angle (degs) to incident angle (radians)
expdata[:, 0] *= np.pi/360
......@@ -46,7 +45,7 @@ def get_sample(P):
def get_simulation(P):
scan = ba.AlphaScan(ba.ListScan("", exp_x))
scan = ba.AlphaScan(ba.ListScan("alpha (rad)", exp_x))
scan.setWavelength(1.54*angstrom)
sample = get_sample(P)
......@@ -54,7 +53,6 @@ def get_simulation(P):
if __name__ == '__main__':
global exp_x
exp_x, exp_y = load_data()
P = ba.Parameters()
......
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