def model_evaluation(dataframe, classes, datapath='./', filename='results'):
pred_chisq = []
alternative_chisq = []
for i in range(len(dataframe)):
row = dataframe.iloc[i]
filepath = datapath + row[0] + '.csv'
data = load_data(filepath)
probab = [
item for item in row[3].split('[')[1].split(']')[0].split(' ')
if item != ''
]
probab = list(map(np.float64, probab))
max_label = [probab.index(x) for x in sorted(probab, reverse=True)[:2]]
label = classes[max_label[0]]
chi_squared = scat_model(data, label)
pred_chisq.append((label, chi_squared))
if probab[max_label[0]] >= 0.7:
alternative_chisq.append('-')
else:
label = classes[max_label[1]]
chi_squared = scat_model(data, label)
alternative_chisq.append((label, chi_squared))
dataframe['predicted_chi_square'] = pred_chisq
dataframe['alternative_chi_square'] = alternative_chisq
dataframe.to_csv(filename, index=False)
return dataframe
from bumps.names import *
from sasmodels.data import load_data
from sasmodels.core import load_model
from sasmodels.bumps_model import Model, Experiment
# Spherical particle data, not ellipsoids
sans, usans = load_data('../../sasview/sasview/test/1d_data/latex_smeared.xml')
usans.qmin, usans.qmax = np.min(usans.x), np.max(usans.x)
usans.mask = (usans.x < 0.0)
usans.oriented = True
#print sans.dxl, usans.dxl
#import pprint; pprint.pprint(sans.__dict__)
kernel = load_model("ellipsoid")
model = Model(
kernel,
scale=0.08, background=0,
sld=.291, sld_solvent=7.105,
r_polar=1800, r_polar_pd=0.222296, r_polar_pd_n=0,
r_equatorial=2600, r_equatorial_pd=0.28, r_equatorial_pd_n=0,
theta=60, theta_pd=0, theta_pd_n=0,
phi=60, phi_pd=0, phi_pd_n=0,
)
# SET THE FITTING PARAMETERS
model.r_polar.range(1000, 10000)
model.r_equatorial.range(1000, 10000)
model.theta.range(0, 360)
model.phi.range(0, 360)
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import sys
from bumps.names import *
from sasmodels.core import load_model
from sasmodels.bumps_model import Model, Experiment
from sasmodels.data import load_data, set_beam_stop, set_top
""" IMPORT THE DATA USED """
radial_data = load_data('DEC07267.DAT')
set_beam_stop(radial_data, 0.00669, outer=0.025)
set_top(radial_data, -.0185)
tan_data = load_data('DEC07266.DAT')
set_beam_stop(tan_data, 0.00669, outer=0.025)
set_top(tan_data, -.0185)
#sas.set_half(tan_data, 'right')
name = "ellipsoid" if len(sys.argv) < 2 else sys.argv[1]
section = "radial" if len(sys.argv) < 3 else sys.argv[2]
if section not in ("radial", "tangential", "both"):
raise ValueError("section %r should be 'radial', 'tangential' or 'both'" %
section)
data = radial_data if section != "tangential" else tan_data
theta = 89.9 if section != "tangential" else 0
phi = 90
kernel = load_model(name, dtype="single")
cutoff = 1e-3
if name == "ellipsoid":
model = Model(
from bumps.names import *
from sasmodels.core import load_model
from sasmodels.bumps_model import Model, Experiment
from sasmodels.data import load_data, plot_data
# latex data, same sample usans and sans
# particles radius ~2300, uniform dispersity
datasets = load_data('latex_smeared.xml', index='all')
#[print(data) for data in datasets]
# A single sphere model to share between the datasets. We will use
# FreeVariables below to set the parameters that are independent between
# the datasets.
kernel = load_model('sphere')
pars = dict(
scale=0.01,
background=0.0,
sld=5.0,
sld_solvent=0.0,
radius=1500.,
#radius_pd=0.1, radius_pd_n=35,
)
model = Model(kernel, **pars)
# radius and polydispersity (if any) are shared
model.radius.range(0, inf)
#model.radius_pd.range(0, 1)
# Contrast and dilution are the same for both measurements, but are not
# separable with a single measurement (i.e., I(q) ~ F(q) contrast^2 Vf),
# so fit one of scale, sld or solvent sld. With absolute scaling from
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import sys
from bumps.names import *
from sasmodels.core import load_model
from sasmodels.bumps_model import Model, Experiment
from sasmodels.data import load_data, set_beam_stop, set_top
""" IMPORT THE DATA USED """
radial_data = load_data('DEC07267.DAT')
set_beam_stop(radial_data, 0.00669, outer=0.025)
set_top(radial_data, -.0185)
kernel = load_model("ellipsoid")
model = Model(kernel,
scale=0.08,
r_polar=15, r_equatorial=800,
sld=.291, sld_solvent=7.105,
background=0,
theta=90, phi=0,
theta_pd=15, theta_pd_n=40, theta_pd_nsigma=3,
r_polar_pd=0.222296, r_polar_pd_n=1, r_polar_pd_nsigma=0,
r_equatorial_pd=.000128, r_equatorial_pd_n=1, r_equatorial_pd_nsigma=0,
phi_pd=0, phi_pd_n=20, phi_pd_nsigma=3,
)
# SET THE FITTING PARAMETERS
model.r_polar.range(15, 1000)
model.r_equatorial.range(15, 1000)
sasview.exe bumps.cli multiscatfit.py --store=t1
"""
import sys
from bumps.names import *
from sasmodels.core import load_model
from sasmodels.bumps_model import Model, Experiment
from sasmodels.data import load_data, set_beam_stop, set_top
from sasmodels.multiscat import MultipleScattering
## Load the data
#data = load_data('DEC07267.DAT')
#set_beam_stop(data, 0.003, outer=0.025)
data = load_data('latex_smeared.xml', index=0)
## Define the model
kernel = load_model("ellipsoid")
model = Model(
kernel,
scale=0.005,
background=0.05,
radius_polar=2200,
radius_equatorial=2200,
sld=.291,
sld_solvent=7.105,
#theta=90, theta_pd=0, theta_pd_n=0, theta_pd_nsigma=3,
#phi=90, phi_pd=0, phi_pd_n=20, phi_pd_nsigma=3,
radius_polar_pd=0.222296,
from bumps.names import *
from sasmodels.data import load_data
from sasmodels.core import load_model
from sasmodels.bumps_model import Model, Experiment
# Spherical particle data, not ellipsoids
sans, usans = load_data('../../sasview/sasview/test/1d_data/latex_smeared.xml')
usans.qmin, usans.qmax = np.min(usans.x), np.max(usans.x)
usans.mask = (usans.x < 0.0)
usans.oriented = True
#print sans.dxl, usans.dxl
#import pprint; pprint.pprint(sans.__dict__)
kernel = load_model("ellipsoid")
model = Model(
kernel,
scale=0.08,
background=0,
sld=.291,
sld_solvent=7.105,
r_polar=1800,
r_polar_pd=0.222296,
r_polar_pd_n=0,
r_equatorial=2600,
r_equatorial_pd=0.28,
r_equatorial_pd_n=0,
theta=60,
theta_pd=0,
theta_pd_n=0,
import sys
#sys.path.append('path_to_sasmodels')
import numpy as np
from bumps.names import *
from sasmodels.core import load_model
from sasmodels.bumps_model import Model, Experiment
from sasmodels.data import load_data, plot_data
# IMPORT THE DATA USED
data = load_data(sys.argv[1])
#setattr(data, 'qmin', 0.0)
#setattr(data, 'qmax', 10.0)
# DEFINE THE MODEL
kernel = load_model('ellipsoid')
pars = dict(scale=0.08,
background=35,
radius_polar=15,
radius_equatorial=800,
sld=.291,
sld_solvent=7.105,
theta=89.9,
phi=90,
theta_pd=0,
theta_pd_n=0,
theta_pd_nsigma=3,
phi_pd=0,
'P3DDT': 0.316,
'PQT-12': 0.676,
#'Polystyrene-D8':6.407,
'Polystyrene-D8': 6.464, # density of 1.13 g/mL
'Polystyrene-H8': 1.426
}
# loading data for fitting
data_dir = '../../data/sans/Smeared_Data_20200629/'
files = os.listdir(data_dir)
sans_data = {}
usans_data = {}
for file in files:
if 'USANS' in file:
key = int(file.split('_')[0][3:])
usans_data[key] = load_data(data_dir + file)
elif 'SANS' in file:
key = int(file.split('_')[0][3:])
sans_data[key] = load_data(data_dir + file)
# filtering which samples to fit with ellipsoid model
true_keys = []
true_reads = pd.read_csv('../../data/sans/Fit_Truths.csv')
true_reads = true_reads.to_numpy()
mask = true_reads[:, 2].astype(bool)
ellipsoid_keys = true_reads[mask, 0]
run_keys = list(ellipsoid_keys)
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# To Sasview/documents/scripts
from bumps.names import *
from sasmodels.core import load_model
from sasmodels.bumps_model import Model, Experiment
from sasmodels.data import load_data, plot_data
""" IMPORT THE DATA USED """
datafiles = ['latex_smeared_out_0.txt', 'latex_smeared_out_1.txt']
datasets = [load_data(el) for el in datafiles]
for data in datasets:
data.qmin = 0.0
data.qmax = 10.0
#sphere model
kernel = load_model('sphere', dtype="single")
pars = dict(scale=0.01, background=0.0, sld=1.0, sld_solvent=6.0, radius=1500.)
model = Model(kernel, **pars)
model.radius.range(0, inf)
#model.background.range(-inf, inf)
#model.scale.range(0, inf)
model.sld.range(-inf, inf)
model.sld_solvent.range(-inf, inf)
free = FreeVariables(
names=[data.filename for data in datasets],
background=model.background,
scale=model.scale,
from bumps.names import *
from sasmodels.data import load_data
from sasmodels.core import load_model
from sasmodels.bumps_model import Model, Experiment
# Spherical particle data, not ellipsoids
sans, usans = load_data('latex_smeared.xml', index='all')
usans.qmin, usans.qmax = np.min(usans.x), np.max(usans.x)
usans.mask = (usans.x < 0.0)
usans.oriented = True
#print sans.dxl, usans.dxl
#import pprint; pprint.pprint(sans.__dict__)
kernel = load_model("ellipsoid")
model = Model(
kernel,
scale=0.08,
background=0,
sld=.291,
sld_solvent=7.105,
radius_polar=1800,
radius_polar_pd=0.222296,
radius_polar_pd_n=0,
radius_equatorial=2600,
radius_equatorial_pd=0.28,
radius_equatorial_pd_n=0,
theta=60,
theta_pd=0,
theta_pd_n=0,