relax SVN archive

To systemtest Relax_disp.test_task_7882_monte_carlo_std_residual(), added tests for creation of Monte-Carlo data
by different methods.

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.

Added to pipe_control.error_analysis.monte_carlo_create_data() the creation of datapoints for a fixed 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.

In backend pipe_control.error_analysis.monte_carlo_create_data() added the argument 'fixed_error' to allow for fixed input of error to the gauss distribution.

Inserted a range of checks, to make sure function behaves as expected.

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.

Extended the user function 'monte_carlo.create_data', to allow for the defition of the STD to use in gauss distribution.

This is for creation of Monte-Carlo simulations, where one has perhaps gained information about the expected errors of the datapoints, which is not measured.

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.

Added test of argument "distribution" in Ãpipe_control.error_analysis.monte_carlo_create_data().

This is to make sure that a wrong argument is not passed into the function.

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.

To systemtest Relax_disp.test_task_7882_monte_carlo_std_residual(), adding test for raise of errors, if the R2eff model is selected.

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

Raising an error, if the R2eff model is used, and drawing errors from the fit.

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

Change to systemtest Relax_disp.x_test_task_7882_kex_conf()

This is just a temporary systemtest, to check for local minima.

This is method in regression book of Graphpad: http://www.graphpad.com/faq/file/Prism4RegressionBook.pdf
Page: 109-111.

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

Temporary test of making a confidence interval as described in fitting guide.

This is systemtest Relax_disp.x_test_task_7882_kex_conf, which is not activated by default.

Running the test, interestingely shows, there is a possibility for a lower global kex.
But the value only differ from kex=1826 to kex=1813.

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.

Added API function in relaxation dispersion to return error structure 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.