Update examples and plotters for bumps webview

example/fit.py → example/fit2d.py

@@ -1,6 +1,7 @@
 #!/usr/bin/env python
 
 import sys
+from pathlib import Path
 
 from bumps.names import FitProblem
 
@@ -9,11 +10,12 @@
 from sasmodels.data import load_data, set_beam_stop, set_top
 
 """ IMPORT THE DATA USED """
-radial_data = load_data('DEC07267.DAT')
+path = Path(__file__).resolve().parent
+radial_data = load_data(str(path / 'DEC07267.DAT'))
 set_beam_stop(radial_data, 0.00669, outer=0.025)
 set_top(radial_data, -.0185)
 
-tan_data = load_data('DEC07266.DAT')
+tan_data = load_data(str(path / 'DEC07266.DAT'))
 set_beam_stop(tan_data, 0.00669, outer=0.025)
 set_top(tan_data, -.0185)
 #sas.set_half(tan_data, 'right')
@@ -188,7 +190,15 @@
 else:
     problem = FitProblem(M)
 
+M.problem = problem
+
 if __name__ == "__main__":
     import matplotlib.pyplot as plt
-    problem.plot()
+
+    problem.summarize()
+    # Plot using plotly
+    fig = M._plot(backend="plotly")
+    fig.show(renderer='browser')
+    # Plot using matplotlib
+    M._plot(backend="matplotlib")
     plt.show()

example/multiscatfit.py

@@ -28,6 +28,8 @@
 
 from bumps.names import FitProblem
 
+from sasdata import data_path
+
 from sasmodels.bumps_model import Experiment, Model
 from sasmodels.core import load_model
 from sasmodels.data import load_data
@@ -36,7 +38,7 @@
 ## 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)
+data = load_data(str(data_path / '1d_data' / 'latex_smeared.xml'), index=0)
 
 ## Define the model
 kernel = load_model("ellipsoid")
@@ -78,5 +80,5 @@
 if __name__ == "__main__":
     #M.theory()
     M.plot()
-    import pylab
-    pylab.show()
+    import matplotlib.pyplot as plt
+    plt.show()

example/oriented_usans.py

@@ -1,12 +1,14 @@
 import numpy as np
 from bumps.names import FitProblem
 
+from sasdata import data_path
+
 from sasmodels.bumps_model import Experiment, Model
 from sasmodels.core import load_model
 from sasmodels.data import load_data
 
 # Spherical particle data, not ellipsoids
-sans, usans = load_data('latex_smeared.xml', index='all')
+sans, usans = load_data(str(data_path / '1d_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

example/sesans_sphere_2micron.py

@@ -1,45 +1,54 @@
 """
 This is a data file used to load in sesans data and fit it using the bumps engine
+
+Usage:
+
+    bumps sesans_sphere_2micron.py
 """
-import sesansfit
-from bumps.names import Parameter
+from bumps.names import FitProblem, Parameter
 
-# Enter the model name to use
-model_name = "sphere"
+from sasdata import data_path
 
-# DO NOT MODIFY THIS LINE
-model = sesansfit.get_bumps_model(model_name)
+from sasmodels.bumps_model import Experiment, Model
+from sasmodels.core import load_model
+from sasmodels.data import load_data
 
-# Enter any custom parameters
-# name = Parameter(initial_value, name='name')
-phi = Parameter(0.0855, name='phi')
-# Add the parameters to this list that should be displayed in the fitting window
-custom_params = {"phi" : phi}
+# Enter the model name and the datafile path
+model_name = "sphere"
+data_file = data_path / "sesans_data" / "sphere2micron.ses"
 
-# SESANS data file name
-sesans_file = "spheres2micron.ses"
+# Custom parameters for use in expressions
+# name = Parameter(initial_value, name='name')
+phi = Parameter(0.0855, name='phi')  # scale = phi*(1-phi)
 
-# Initial parameter values (if other than defaults)
-# "model_parameter_name" : value
-initial_vals = {
+# Initial parameter values and expressions (if other than defaults)
+# "model_parameter_name" : value or expression
+pars = {
+    "scale": phi*(1-phi),
     "sld" : 1.41,
     "radius" : 10000,
     "sld_solvent" : 2.70,
 }
 
-# Ranges for parameters if other than default
-# "model_parameter_name" : [min, max]
-param_range = {
-    "phi" : [0.001, 0.5],
-    "radius" : [100, 100000]
-}
+# DO NOT MODIFY THIS LINE
+model = Model(load_model(model_name), **pars)
 
-# Constraints
+# Bounds constraints
 # model.param_name = f(other params)
-# EXAMPLE: model.scale = model.radius*model.radius*(1 - phi) - where radius
-# and scale are model functions and phi is a custom parameter
-model.scale = phi*(1-phi)
+model.radius.range(100, 100000)
+phi.range(0.001, 0.5)
+
 
 # Send to the fitting engine
-# DO NOT MODIFY THIS LINE
-problem = sesansfit.sesans_fit(sesans_file, model, initial_vals, custom_params, param_range)
+# DO NOT MODIFY THESE LINES
+data = load_data(str(data_file))
+M = Experiment(data=data, model=model)
+problem = FitProblem([M])
+
+if __name__ == "__main__":
+    import matplotlib.pyplot as plt
+
+    print(f"==== {model_name} model for {data_file.name} has χ² = {problem.chisq_str()} ====")
+    print(problem.summarize())
+    problem.plot()
+    plt.show()

example/sesansfit_CodeCampIII.py

@@ -1,48 +1,23 @@
-import numpy as np
+from pathlib import Path
+
 from bumps.names import FitProblem, Parameter
 
 from sasmodels import bumps_model, core
+from sasmodels.data import load_data
 
-if True: # fix when data loader exists
-#    from sas.dataloader.readers\
-    from sas.dataloader.loader import Loader
-    loader = Loader()
-    filename = 'sphere.ses'
-    data = loader.load(filename)
-    if data is None:
-        raise OSError("Could not load file %r"%(filename,))
-    data.x /= 10
-#    print data
-#    data = load_sesans('mydatfile.pz')
-#    sans_data = load_sans('mysansfile.xml')
-
-else:
-    SElength = np.linspace(0, 2400, 61) # [A]
-    data = np.ones_like(SElength)
-    err_data = np.ones_like(SElength)*0.03
-
-    class Sample:
-        zacceptance = 0.1 # [A^-1]
-        thickness = 0.2 # [cm]
-
-    class SESANSData1D:
-        #q_zmax = 0.23 # [A^-1]
-        lam = 0.2 # [nm]
-        x = SElength
-        y = data
-        dy = err_data
-        sample = Sample()
-    data = SESANSData1D()
+path = Path(__file__).resolve().parent
+data = load_data(str(path / 'sphere.ses'))
 
 radius = 1000
 data.Rmax = 3*radius # [A]
 
 ##  Sphere parameters
 
-kernel = core.load_model("sphere", dtype='single')
+kernel = core.load_model("sphere")
 phi = Parameter(0.1, name="phi")
-model = bumps_model.Model(kernel,
-    scale=phi*(1-phi), sld=7.0, solvent_sld=1.0, radius=radius,
+model = bumps_model.Model(
+    kernel,
+    scale=phi*(1-phi), sld=7.0, sld_solvent=1.0, radius=radius,
     )
 phi.range(0.001,0.5)
 #model.radius.pmp(40)
@@ -74,3 +49,9 @@ class SESANSData1D:
 else:
     M_sesans = bumps_model.Experiment(data=data, model=model)
     problem = FitProblem(M_sesans)
+
+
+if __name__ == "__main__":
+    import matplotlib.pyplot as plt
+    problem.plot()
+    plt.show()

example/simul_fit.py

@@ -1,13 +1,15 @@
 import numpy as np
 from bumps.names import FitProblem, FreeVariables
 
+from sasdata import data_path
+
 from sasmodels.bumps_model import Experiment, Model
 from sasmodels.core import load_model
 from sasmodels.data import load_data
 
 # latex data, same sample usans and sans
 # particles radius ~2300, uniform dispersity
-datasets = load_data('latex_smeared.xml', index='all')
+datasets = load_data(str(data_path / '1d_data' / 'latex_smeared.xml'), index='all')
 #[print(data) for data in datasets]
 
 # A single sphere model to share between the datasets.  We will use
@@ -61,3 +63,8 @@
 M = [Experiment(data=data, model=model, name=data.run[0]) for data in datasets]
 
 problem = FitProblem(M, freevars=free)
+
+if __name__ == "__main__":
+    import matplotlib.pyplot as plt
+    problem.plot()
+    plt.show()

sasmodels/TwoYukawa/CalTYSk.py

@@ -1,8 +1,8 @@
 import numpy as np
-from numpy import pi, mean
+from numpy import mean, pi
 
-from .Ecoefficient import TYCoeff
 from .CalcRealRoot import CalRealRoot
+from .Ecoefficient import TYCoeff
 from .TInvFourier import TInvFourier
 
 # Supplied Q vector must go out to at least this value to calculate g(r).

sasmodels/TwoYukawa/CalcRealRoot.py

@@ -3,6 +3,7 @@
 from .Ecoefficient import TYCoeff
 from .Epoly import make_poly
 
+
 def CalRealRoot(coeff: TYCoeff):
 
     Ecoefficient = coeff.Ecoefficient

sasmodels/TwoYukawa/Ecoefficient.py

@@ -1,7 +1,7 @@
 from typing import Callable, Tuple
 
 import numpy as np
-from numpy import exp, pi, cos, sin, cosh
+from numpy import cos, cosh, exp, pi, sin
 from numpy.typing import NDArray
 
 # CalCoeff.m
@@ -194,17 +194,17 @@ def ABC12(d1, d2):
               Ccd2_22*Cdd1_12*d1*d2**2 -
               Ccd1_21*Cdd2_22*d1*d2**2 -
               Ccd2_22*d2*k1 + Ccd1_21*d1*k2)))/
-        ((d1*((
+        (d1*(
               (-Ccd1_21)*Ccd2_12*d2 +
-                Ccd1_11*Ccd2_22*d2)))))
+                Ccd1_11*Ccd2_22*d2)))
         C2 = ((-((Ccd2_12*d2*
                 (((-Cd1_1)*d1 - Cdd1_11*d1**2 -
                     Cdd1_12*d1*d2 + k1)) -
               Ccd1_11*d1*
                 (((-Cd2_2)*d2 - Cdd2_12*d1*d2 -
                     Cdd2_22*d2**2 + k2))))) /
-        (((-Ccd1_21)*Ccd2_12*d1*d2 +
-            Ccd1_11*Ccd2_22*d1*d2)))
+        ((-Ccd1_21)*Ccd2_12*d1*d2 +
+            Ccd1_11*Ccd2_22*d1*d2))
         return A, B, C1, C2
     self.ABC12 = ABC12
 
@@ -370,10 +370,10 @@ def tau_d21(s):
 
     E1d02 = 12*c1F01*phi*sigma_d01(z1) - 12*c1F01*exp(-z1)*phi*tau_d01(z1)
 
-    E1d11 = (((12*c1F10*phi*sigma_d01(z1) + \
+    E1d11 = (12*c1F10*phi*sigma_d01(z1) + \
           12*c1F01*phi*sigma_d10(z1) - \
           12*c1F10*exp(-z1)*phi*tau_d01(z1) - \
-          12*c1F01*exp(-z1)*phi*tau_d10(z1))))
+          12*c1F01*exp(-z1)*phi*tau_d10(z1))
     E1d12 = (-c1F01 + 12*c1F11*phi*sigma_d01(z1) +
              12*c1F01*phi*sigma_d11(z1) -
              12*c1F11*exp(-z1)*phi*tau_d01(z1) -