Commit 4b86df6f authored by Erkka Rinne's avatar Erkka Rinne
Browse files

Merge branch 'dev'

parents fe5e0ef8 fee76e7a
......@@ -3,6 +3,9 @@ All notable changes to this project will be documented in this file.
## [Unreleased]
## [1.0.3] - 2019-02-05
### Fixed
- Only selects forecasts with positive probability for the solve
## [1.0.2] - 2019-02-04
### Added
......@@ -31,5 +34,6 @@ All notable changes to this project will be documented in this file.
### Changed
- Major updates to data structures etc.
[Unreleased]: https://gitlab.vtt.fi/backbone/backbone/compare/v1.0.2...dev
[Unreleased]: https://gitlab.vtt.fi/backbone/backbone/compare/v1.0.3...dev
[1.0.3]: https://gitlab.vtt.fi/backbone/backbone/compare/v1.0.2...v1.0.3
[1.0.2]: https://gitlab.vtt.fi/backbone/backbone/compare/v1.0...v1.0.2
......@@ -62,12 +62,14 @@ $offtext
);
// Calculate which samples are treated as parallel and the previous samples
loop(ms_initial(m, s_),
loop(ms(m, s)$(not sameas(s, s_)),
loop(ms_initial(m, s_), // Select the root sample
loop(ms(m, s)$(not sameas(s, s_)), // Select other samples than root
// If two samples share same starting time, treat them as parallel
if(msStart(m, s) = msStart(m, s - 1),
s_parallel(s) = yes;
s_parallel(s - 1) = yes;
);
// Set previous samples for samples
if(msEnd(m, s_) = msStart(m, s), ss(s, s_) = yes);
if(msEnd(m, s - 1) = msStart(m, s), ss(s, s - 1) = yes);
);
......@@ -80,13 +82,16 @@ $offtext
if (not sum(f, mf(m, f)), // unless they have been provided as input
mf(m, f)$(ord(f) <= 1 + mSettings(m, 'forecasts')) = yes; // realization needs one f, therefore 1 + number of forecasts
);
msf(m, s, f)$(ms(m, s) and mf(m, f)) = yes;
msf(m, s_parallel(s), f) = mf_central(m, f); // Parallel samples only have central forecast
// Select the forecasts included in the modes to be solved
f_solve(f)${mf(m,f) and p_mfProbability(m, f)}
= yes;
// Select combinations of models, samples and forecasts to be solved
msf(m, s, f_solve(f))$(ms(m, s) and mf(m, f)) = yes;
msf(m, s_parallel(s), f_solve(f)) = mf_central(m, f); // Parallel samples only have central forecast
// Check the modelSolves for preset patterns for model solve timings
// If not found, then use mSettings to set the model solve timings
if(sum(modelSolves(m, t_full(t)), 1) = 0,
......
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