Ctrl+K

tmmc-lnpy

Repo Docs PyPI license PyPI version Conda (channel only) Code style: black

tmmc-lnpy#

Overview#

A package to analyze \(\ln \Pi(N)\) data from Transition Matrix Monte Carlo simulation. The main output from TMMC simulations, \(\ln \Pi(N)\), provides a means to calculate a host of thermodynamic properties. Moreover, if \(\ln \Pi(N)\) is calculated at a specific chemical potential, it can be reweighted to provide thermodynamic information at a different chemical potential

Features#

tmmc-lnpy provides a wide array of routines to analyze \(\ln \Pi(N)\). These include:

  • Reweighting to arbitrary chemical potential

  • Segmenting \(\ln \Pi(N)\) (to identify unique phases)

  • Containers for interacting with several values of \(\ln \Pi(N)\) in a vectorized way.

  • Calculating thermodynamic properties from these containers

  • Calculating limits of stability, and phase equilibrium

Status#

This package is actively used by the author. Please feel free to create a pull request for wanted features and suggestions!

Quick start#

Use one of the following

pip install tmmc-lnpy

or

conda install -c conda-forge tmmc-lnpy

Example usage#

Note that the distribution name tmmc-lnpy is different than the import name lnpy due to name clashing on pypi.

>>> import numpy as np
>>> import lnpy
>>> import lnpy.examples

>>> ref = lnpy.examples.load_example_lnpimasked("lj_sub")

>>> phase_creator = lnpy.PhaseCreator(nmax=1, ref=ref)
>>> build_phases = phase_creator.build_phases_mu([None])
>>> collection = lnpy.lnPiCollection.from_builder(
...     lnzs=np.linspace(-10, 3, 5), build_phases=build_phases
... )


# Collections are like pandas.Series
>>> collection
<class lnPiCollection>
lnz_0   phase
-10.00  0        [-10.0]
-6.75   0        [-6.75]
-3.50   0         [-3.5]
-0.25   0        [-0.25]
 3.00   0          [3.0]
dtype: object


# Access xarray backend for Grand Canonical properties with `xge` accessor
>>> collection.xge.betaOmega()
<xarray.DataArray 'betaOmega' (lnz_0: 5, phase: 1)> Size: 40B
array([[-2.3245e-02],
       [-6.0370e-01],
       [-1.8552e+02],
       [-1.5447e+03],
       [-2.9580e+03]])
Coordinates:
  * lnz_0    (lnz_0) float64 40B -10.0 -6.75 -3.5 -0.25 3.0
  * phase    (phase) int64 8B 0
    beta     float64 8B 1.372
    volume   float64 8B 512.0
Attributes:
    dims_n:         ['n_0']
    dims_lnz:       ['lnz_0']
    dims_comp:      ['component']
    dims_state:     ['lnz_0', 'beta', 'volume']
    dims_rec:       ['sample']
    standard_name:  grand_potential
    long_name:      $\beta \Omega(\mu,V,T)$
Contents