Open a FitPage and choose a model (I chose core shell sphere). Then open another FitPage and chose a model (I chose the same model). Then to to FitPage 1 and copy parameters and then to FitPage 2 to paste.

The core_shell_sphere heading for the parameters after scale and background now looks like a fitable parameter with NaN for value and min max.

in 5.0-beta.1 the console log always stays on top, even if clicking on the data explorer. Further the console cannot be shrunk (nor does it seem to want to expand despite an arrow indicating it should), nor can the data explorer be easily resized.

The default layout should not have the console covering such a key area of the GUI anwyay. Can we make the data explorer smaller by default? and expandable? and also the console?

This ticket is being used to report changed (for the better!) behaviour in 4.2.0 that does not appear to have been previously ticketed or documented, so that the issue can be appropriately reported in future release notes, and to draw attention to the change.

This issue was verified in the presence of @richardh.

To reproduce the issue: Load the attached data in 4.1.2, send it for fitting, select the spinodal model. Increase Qmin to 0.05. Select scale, background & q_0. Fit. Now repeat the fit in 4.2.0.

The Chi2/Npts, Npts(Fit), theory curve, residuals, and indeed the theory intensities reported by DataInfo, are all the same. As are the fitted background and q_0 parameters (and their uncertainties). But the scale (and scale uncertainty) values reported are DIFFERENT. However, simple visual inspection shows that it is 4.2.0 which is giving the correct scale.

Closer inspection shows that 4.1.2 is actually reporting the square root of the correct scale.

The underlying code did not change (apart from the inclusion of an inconsequential numpy import):

This is 4.1.2

from numpy import inf, errstate

name = "spinodal"
title = "Spinodal decomposition model"
description = """\
      I(q) = scale ((1+gamma/2)x^2)/(gamma/2+x^(2+gamma))+background

      List of default parameters:
      scale = scaling
      gamma = exponent
      x = q/q_0
      q_0 = correlation peak position [1/A]
      background = Incoherent background"""
category = "shape-independent"

# pylint: disable=bad-whitespace, line-too-long
#             ["name", "units", default, [lower, upper], "type", "description"],
parameters = [["scale",    "",      1.0, [-inf, inf], "", "Scale factor"],
              ["gamma",      "",    3.0, [-inf, inf], "", "Exponent"],
              ["q_0",  "1/Ang",     0.1, [-inf, inf], "", "Correlation peak position"]
             ]
# pylint: enable=bad-whitespace, line-too-long

def Iq(q,
       scale=1.0,
       gamma=3.0,
       q_0=0.1):
    """
    :param q:              Input q-value
    :param scale:          Scale factor
    :param gamma:          Exponent
    :param q_0:            Correlation peak position
    :return:               Calculated intensity
    """
    
    with errstate(divide='ignore'):
        x = q/q_0
        inten = scale * ((1 + gamma / 2) * x ** 2) / (gamma / 2 + x ** (2 + gamma)) 
    return inten
Iq.vectorized = True  # Iq accepts an array of q values

This is 4.2.0

import numpy as np
from numpy import inf, errstate

name = "spinodal"
title = "Spinodal decomposition model"
description = """\
      I(q) = Imax ((1+gamma/2)x^2)/(gamma/2+x^(2+gamma)) + background

      List of default parameters:
      
      Imax = correlation peak intensity at q_0
      background = incoherent background
      gamma = exponent (see model documentation)
      q_0 = correlation peak position [1/A]
      x = q/q_0"""
      
category = "shape-independent"

# pylint: disable=bad-whitespace, line-too-long
#             ["name", "units", default, [lower, upper], "type", "description"],
parameters = [["gamma",      "",    3.0, [-inf, inf], "", "Exponent"],
              ["q_0",  "1/Ang",     0.1, [-inf, inf], "", "Correlation peak position"]
             ]
# pylint: enable=bad-whitespace, line-too-long

def Iq(q,
       gamma=3.0,
       q_0=0.1):
    """
    :param q:              Input q-value
    :param gamma:          Exponent
    :param q_0:            Correlation peak position
    :return:               Calculated intensity
    """

    with errstate(divide='ignore'):
        x = q/q_0
        inten = ((1 + gamma / 2) * x ** 2) / (gamma / 2 + x ** (2 + gamma))
    return inten
Iq.vectorized = True  # Iq accepts an array of q values

@richardh theorised that this might have something to do with the spinodal model being a non-SLD model, so we also tested the behaviour of the gaussian_peak model. The scale values from that reported by 4.1.2 and 4.2.0 were the same.

Does anyone remember making a change elsewhere that might account for this issue?