Generic datasets
Simulation datasets in any form.
The alchemlyb.generic module features datasets that are MD engine free and
can adopt any form.
They can be accessed using the following accessor functions:
Load data set that will fail the MBAR adaptive solver but could done by BGFS. |
Difficult case for the adaptive MBAR solver
The pymbar.mbar.MBAR can have difficulty in solving some
dataset with the adaptive method, where BFGS is needed.
The usage is like this
>>> import numpy as np
>>> from pymbar import MBAR
>>> from alchemtest.generic import load_MBAR_BGFS
>>> u_nk = np.load(load_MBAR_BGFS()['data']['u_nk'])
>>> N_k = np.load(load_MBAR_BGFS()['data']['N_k'])
>>> solver_options = {"maximum_iterations":10000,"verbose":True}
>>> solver_protocol = {"method":"adaptive","options":solver_options}
>>> mbar = MBAR(u_nk, N_k, solver_protocol=(solver_protocol,))
>>> results, errors = mbar.getFreeEnergyDifferences()
Which will give the pymbar.utils.ParameterError
>>> solver_options = {"maximum_iterations":10000,"verbose":True}
>>> solver_protocol = {"method":"BFGS","options":solver_options}
>>> mbar = MBAR(u_nk, N_k, solver_protocol=(solver_protocol,))
>>> results, errors = mbar.getFreeEnergyDifferences()
Which will work.
generic: MBAR solver stability test
u_nk and N_k files that could be calculated with MBAR using BGFS method but not the adaptive method.
Notes
- Data Set Characteristics:
- Number of Legs:
N/A
- Number of Windows:
1
- Length of Windows:
N/A
- System Size:
N/A
- Temperature:
N/A
- Pressure:
1 N/A
- Alchemical Pathway:
N/A
- Missing Values:
None
- Energy unit:
N/A
- Time unit:
N/A
- Creator:
Z. Wu
- Donor:
Ryan S. DeFeveru (defever@nd.edu)
- Date:
Oct 2021
- License:
CC0 Public Domain Dedication
This dataset was provided by @rsdefever on Github , downloaded and uploaded by Zhiyi Wu (@xiki-tempula).