Comments (2)
I believe @richardjgowers' refactor doesn't enable this just yet, but should be on the path towards enabling it (at least that's definitely the eventual intent of it all).
@richardjgowers might be better able to speak to what the next steps along are.
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hi @hannahbruce this is something we're working on. I've recently revamped the FEMap object, and one change is that experimental results are not required (so random numbers aren't required.). Then there's also units on all values, (no more kcal/kJ headaches) and some support for absolute calculations too, etc
So here's an example of using a csv file with no experimental results, then doing MLE to get some absolute results. This is currently using the most recent commit on this repo, and isn't quite released yet.
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Related Issues (20)
- not catching node name mismatch HOT 3
- Update readme and examples
- Add plot_bar to plotly example notebook
- Seaborn calls in WhyNotToUseR2ForDDG notebook fail
- Versioneer causing failures on conda-forge builds HOT 1
- add controllable guidelines on plots
- make FEMap a gufe tokenizable HOT 4
- base class for MLE estimation-like methods
- FEMap add to/from networkx method
- add option for get_absolute_dataframe to shift values HOT 1
- Update API docs
- Add userguide docs
- Update changelog docs
- MLE ddG errors != calculated ddG errors for open cycle
- [Question] Allow arbitrary xy tick frequency when plotting
- Refactor stats into base and derived class so we can drop in different MLE solvers? HOT 1
- the value of the x/y axis from plot_DGs function does not reflect the true DGs HOT 6
- readthedocs is deeply unhappy
- Error of exactly zero will trigger SVD failure when generating absolute values
- refactoring bootstrap stats HOT 2
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