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@amr8004 In the SS-Ti64 branch, you can now find builders of callables that accept the YAML config file describing a constraint and configure a corresponding template script.
The philosophy is that these will belong to unique (name + YAML-hash + elements) modules, like SSTi64_67d784_NiCrFeV, for each elemental space of your problem and will have all constraints built in; thus, things like if density > MAX: return False or [len(gridPhases[i]['Phases']) != 0 and len(set(gridPhases[i]['Phases']).difference(feasiblePhases)) == 0 and gridPhases[i] != [] for i in range(len(gridPhases))] will belong inside them, rather than be repetitively included in the Jupyter notebook.
The modules will be packaged by AMMap into ZIP files that can be (a) run directly by AMMap in a plug-and-play fashion, and (b) be used to enable easy reproducibility of results in scientific publications.
The text was updated successfully, but these errors were encountered:
@amr8004 In the SS-Ti64 branch, you can now find builders of callables that accept the
YAML
config file describing a constraint and configure a corresponding template script.The philosophy is that these will belong to unique (name +
YAML
-hash + elements) modules, likeSSTi64_67d784_NiCrFeV
, for each elemental space of your problem and will have all constraints built in; thus, things likeif density > MAX: return False
or[len(gridPhases[i]['Phases']) != 0 and len(set(gridPhases[i]['Phases']).difference(feasiblePhases)) == 0 and gridPhases[i] != [] for i in range(len(gridPhases))]
will belong inside them, rather than be repetitively included in the Jupyter notebook.The modules will be packaged by
AMMap
into ZIP files that can be (a) run directly byAMMap
in a plug-and-play fashion, and (b) be used to enable easy reproducibility of results in scientific publications.The text was updated successfully, but these errors were encountered: