relax SVN archive

Adding empty API method to return errors from the reduced chi2 distribution.

Task #7882 (https://gna.org/task/?7882): Implement Monte-Carlo simulation, where errors are generated with width of standard deviation or residuals.): Implement Monte-Carlo simulation, where errors are generated with width of standard deviation or residuals.

Adding to back-end of pipe_control.error_analysis(), to modify datapoint as error drawn from the reduced chi2 gauss distribution.

Task #7882 (https://gna.org/task/?7882): Implement Monte-Carlo simulation, where errors are generated with width of standard deviation or residuals.): Implement Monte-Carlo simulation, where errors are generated with width of standard deviation or residuals.

Extension of the userfunction monte_carlo.create_data, to draw errors from the reduced chi2 gauss distribution as found by best fit.

Task #7882 (https://gna.org/task/?7882): Implement Monte-Carlo simulation, where errors are generated with width of standard deviation or residuals.): Implement Monte-Carlo simulation, where errors are generated with width of standard deviation or residuals.

Simplification of systemtest Relax_disp.test_task_7882_monte_carlo_std_residual, to just test the creation of Monte-Carlo data where errors are drawn from the reduced chi2 distribution.

Task #7882 (https://gna.org/task/?7882): Implement Monte-Carlo simulation, where errors are generated with width of standard deviation or residuals.): Implement Monte-Carlo simulation, where errors are generated with width of standard deviation or residuals.

Reverted range of commits r27213:r27202 as this was a bad implementation.

To get the distribution, one should look at the sum of squares.
But this should be from the weighted sum of squares, which is stored as chi2.
The API provides a method of model_statistics(), to get:
k - number of parameters.
n - number of data points.
chi2 - the chi-squared value.

Then reduced chi2 can be computed. chi2_red = chi2/(n-k)
And the error distribution be drawn from this.

The command used was:
svn merge -r27213:r27201 .

Task #7882 (https://gna.org/task/?7882): Implement Monte-Carlo simulation, where errors are generated with width of standard deviation or residuals.

Added 'sos' and 'sos_std' as parameter object in relaxation dispersion.

Task #7882 (https://gna.org/task/?7882): Implement Monte-Carlo simulation, where errors are generated with width of standard deviation or residuals.

Implemented in the relaxation dispersion API, the function to return errors as the standard deviation of sums squared residuals.

Task #7882 (https://gna.org/task/?7882): Implement Monte-Carlo simulation, where errors are generated with width of standard deviation or residuals.

Implemented the api_base method of return_error_sum_squares(), as raising an error if not defined for the api for the pipe_type.

Task #7882 (https://gna.org/task/?7882): Implement Monte-Carlo simulation, where errors are generated with width of standard deviation or residuals.

Extended backend in pipe_control.error_analysis.monte_carlo_create_data() to return errors as the standard deviation of the sum of squares of the residual.

Task #7882 (https://gna.org/task/?7882): Implement Monte-Carlo simulation, where errors are generated with width of standard deviation or residuals.

Extended user function monte_carlo.create_data() to accept 'method="sum_squares"', to create Monte-Carlo data.

Task #7882 (https://gna.org/task/?7882): Implement Monte-Carlo simulation, where errors are generated with width of standard deviation or residuals.