Trusted, Bureaucrats
4,228
edits
Changes
m
Formatting of chi2.
* Added simulations that show, there is perfect agreement between Monte Carlo simulations and covariance estimation. [https://gna.org/task/?7822 Task #7822]: Implement user function to estimate R<sub>2eff</sub> and associated errors for exponential curve fitting.
* Inserted extra tests in system test Relax_disp.test_estimate_r2eff_err_methods to test that all values of R and I<sub>0</sub> are positive, and the standard deviation from Monte Carlo simulations are equal. [https://gna.org/task/?7822 Task #7822]: Implement user function to estimate R<sub>2eff</sub> and associated errors for exponential curve fitting.
* Inserted system test Relax_disp.test_finite_value, to illustrate the return of inf from C code exponential, when R is negative. This can be an issue, if minfx takes a wrong step when no constraints are implemented. [https://gna.org/bugs/?22552 Bug #22552]: Chi2 χ<sup>2</sup> value returned from C code curve-fitting return 0.0 for wrong parameters -> Expected influence on Monte Carlo sim.
* Inserted possibility for bootstrapping in system test Relax_disp.test_estimate_r2eff_err_methods. This shows, that the bootstrapping method get the SAME estimation for R<sub>2eff</sub> errors, as the estimate_r2eff_err() function. This must either mean, that the OLD Monte Carlo simulation was corrupted, or the creation of data in Monte Carlo simulations is corrupted.
* Modified system test Relax_disp.verify_estimate_r2eff_err_compare_mc to include bootstrapping method. This shows there is excellent agreement between bootstrapping and estimation of errors from covariance, while relax Monte Carlo simulations are very much different. Boot strapping is the "-2": [https://gna.org/task/?7822 Task #7822]: Implement user function to estimate R<sub>2eff</sub> and associated errors for exponential curve fitting.
* Cleaned up user function for estimating R<sub>2eff</sub> errors. Extensive tests have shown, there is a very good agreement between the covariance estimation, and Monte Carlo simulations. This is indeed a very positive implementation. [https://gna.org/task/?7822 Task #7822]: Implement user function to estimate R<sub>2eff</sub> and associated errors for exponential curve fitting. [https://gna.org/bugs/?22554 Bug #22554]: The distribution of intensity with errors in Monte Carlo simulations are markedly more narrow than expected.
* Removed all junk comments from module for R<sub>2eff</sub> error estimation. The module runs perfect as it does now. [https://gna.org/task/?7822 Task #7822]: Implement user function to estimate R<sub>2eff</sub> and associated errors for exponential curve fitting. [https://gna.org/bugs/?22554 Bug #22554]: The distribution of intensity with errors in Monte Carlo simulations are markedly more narrow than expected.
* Fix for inf values being returned from C code exponential function. Values are now converted to high values. This fixes system test Relax_disp.test_finite_value. Example: x = np.array([np.inf, -np.inf, np.nan, -128, 128]), np.nan_to_num(x), array([ 1.79769313e+308, -1.79769313e+308, 0.00000000e+000, -1.28000000e+002, 1.28000000e+002]). [https://gna.org/bugs/?22552 Bug #2255]: Chi2 χ<sup>2</sup> value returned from C code curve-fitting return 0.0 for wrong parameters -> Expected influence on Monte Carlo sim. Ref: http://docs.scipy.org/doc/numpy/reference/generated/numpy.nan_to_num.html.
* Initial try to reach constrained methods in minfx through relax. This is in system test Relax_disp.verify_estimate_r2eff_err_compare_mc() This though not seem to be supported.
* Allow R<sub>2eff</sub> model to reach constrained methods in minfx through relax. This is in system test Relax_disp.verify_estimate_r2eff_err_compare_mc() This though not seem to be supported.
* Another fix for [https://gna.org/bugs/?22505 bug #22505]. This is the failure of the structure.create_diff_tensor_pdb user function when no structural data is present. Now the cdp.structure data structure is checked, when present, if it contains any data using its own empty() method.
* Fix for [https://gna.org/bugs/?22502 bug #22502]. This is the problem whereby the geometric prolate diffusion representation does not align with axis in PDB, as reported by Martin Ballaschk (https://gna.org/users/mab). This problem was not the main prolate tensor axis, but that the geometric object needed to be rotated 90 degrees about the z-axis to bring the object and axis into the same frame.
* Fix for time not extracted for CPMG experiments in target_function. [https://gna.org/bugs/?22461 Bug #22461]: NS R1rho 2-site_fit_r1 has extremely high chi2 χ<sup>2</sup> value in system test Relax_disp.test_r1rho_kjaergaard_missing_r1.* Fix for interpolating time points, when producing xmgrace files for CPMG experiments. [https://gna.org/bugs/?22461 Bug #22461]: NS R1rho 2-site_fit_r1 has extremely high chi2 χ<sup>2</sup> value in system test Relax_disp.test_r1rho_kjaergaard_missing_r1.* Correction for catastrophic implementation of Monte Carlo simulations for exponential curve-fitting R<sub>2eff</sub> values in the dispersion analysis. A wrong implemented "else if" statement, would add the intensity for the simulated intensity together with the original intensity. This means that all intensity values send to minimisation would be twice as high than usually (if spectra were not replicated). This was discovered for Monte Carlo simulations of R<sub>2eff</sub> errors in exponential fit. This will affect all analyses using full relaxation exponential curves until now. By pure luck, it seems that the effect of this would be that R<sub>2eff</sub> errors are half the value they should be. A further investigation shows, that for the selected data set, this had a minimum on influence on the fitted parameters, because the chi2 χ<sup>2</sup> value would be scaled up by a factor 4. [https://gna.org/bugs/?22554 Bug #22554]: The distribution of intensity with errors in Monte Carlo simulations are markedly more narrow than expected. [https://gna.org/task/?7822 Task #7822]: Implement user function to estimate R<sub>2eff</sub> and associated errors for exponential curve fitting.
* Added a minfx minimum version check to the dep_check module. This is to avoid problems such as that reported at [http://gna.org/bugs/?22408 bug #22408].