add goodness of fit plot #192
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@@ Coverage Diff @@
## develop #192 +/- ##
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+ Coverage 77.91% 78.04% +0.12%
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Files 32 32
Lines 2884 2910 +26
Branches 686 688 +2
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+ Hits 2247 2271 +24
Misses 461 461
- Partials 176 178 +2
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PaulJonasJost
approved these changes
Feb 1, 2023
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| slope, intercept, r_value, p_value, std_err = stats.linregress( | ||
| petab_problem.measurement_df['measurement'], | ||
| simulations_df['simulation']) # x, y |
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you calculate here the linear regression between measurement and simulation. What would it tell me if this is not a diagonal plot?
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You could see here if simulated values tend to be larger or smaller that measurement values. This plot probably won't be useful in every case. Also it gives some measure of how much off the simulation is.
It could be useful if one wants to compare different approaches to fit the model.
dilpath
approved these changes
Feb 1, 2023
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