fullrmc.Examples.get_examples_path()

Get distribution examples directory path in the standard distribution.

Returns: path (string): directory path in a form of a string.
fullrmc.Examples.find_example(name)

Return example’s path given its name.

Parameters: name (string): The name of the example. path (None, string): The path of the example if found. None if example is not found.
fullrmc.Examples.get_available_examples()

Get all available examples as delivered in the standard distribution.

Returns: examples (list): List of examples paths.
fullrmc.Examples.print_available_examples()

Print all available examples path in the standard distribution.

# Available examples¶

It is not allowed to use any of the examples materials’ outside of the scope of this tutorial. Experimental data and models distributed in the examples are even wrong or tricked to serve the purpose of learning fullrmc.

Herein is a list of all available examples in the standard distribution. A short description of each example is shown in the list below. It is recommended not to run any example from within fullrmc. But copy the example folder to any safe place such as one’s home directory and run it from there. To locate an example and copy it, one can do the following:

# import find_example
from fullrmc.Examples import find_example
# search for an examples. e.g. atomicNiTi
print(find_example('atomicNiTi'))

>>> '../site-packages/fullrmc/Examples/atomicNiTi'


In all examples, run.py is the name of the file that must be executed from the command line as the following:

python run.py


Examples folder name is used as the click-able items in the following list.

Constraints:

Generators:

• translations: Used show how to use translation generators.
• rotations: To show how to use rotation generators.
• agitations: To show how to use agitation generators.

Fitting modes:

• docking: To show how to move one group of atoms towards another.
• explore: This is a simulation of a molecule exploring a cavity.
• refine: This is a simulation of a molecule refining its position in a cavity.
• ExploreCO2: This is a fit of CO2 gas in critical condition.

Selectors:

• MLSelection: In this example we show that reinforcement machine learning can help increasing accepted moves ratio.

Benchmarks:

Real systems:

• atomicNiTi: Fitting a Ni-Ti memory shape binary compound.
• molecularTHF: This is a tetrahydrofuran electrolyte system fitting.
• SiOxNanosphere: This is an isolated silicon oxide nanosphere fitting.
• NiMnCoLiO: This is a fake Nickel Manganese Cobalt Lithium oxide composite used to demonstrate how to remove atoms from system.

Frames:

• frames: Fitting the same Ni-Ti memory shape binary compound as in example atomicNiTi. But in this example we define different frames and build different fitting processes all contained in the same engine.