diff --git a/docs/_modules/pymatgen/analysis/diffusion/analyzer.html b/docs/_modules/pymatgen/analysis/diffusion/analyzer.html index 4fbf6ae..ab52b3b 100644 --- a/docs/_modules/pymatgen/analysis/diffusion/analyzer.html +++ b/docs/_modules/pymatgen/analysis/diffusion/analyzer.html @@ -66,10 +66,12 @@

Source code for pymatgen.analysis.diffusion.analyzer

import multiprocessing import warnings +from typing import TYPE_CHECKING, Literal import numpy as np import scipy.constants as const from monty.json import MSONable +from scipy.optimize import curve_fit from pymatgen.analysis.structure_matcher import OrderDisorderElementComparator, StructureMatcher from pymatgen.core.periodic_table import get_el_sp @@ -77,6 +79,9 @@

Source code for pymatgen.analysis.diffusion.analyzer

from pymatgen.io.vasp.outputs import Vasprun from pymatgen.util.coord import pbc_diff +if TYPE_CHECKING: + from collections.abc import Sequence + __author__ = "Will Richards, Shyue Ping Ong" __version__ = "0.2" __maintainer__ = "Will Richards" @@ -950,7 +955,12 @@

Source code for pymatgen.analysis.diffusion.analyzer

[docs] -def fit_arrhenius(temps, diffusivities): +def fit_arrhenius( + temps: Sequence[float], + diffusivities: Sequence[float], + mode: Literal["linear", "exp"] = "linear", + diffusivity_errors: Sequence[float] | None = None, +) -> tuple[float, float, float | None]: """ Returns Ea, c, standard error of Ea from the Arrhenius fit. D = c * exp(-Ea/kT). @@ -959,16 +969,35 @@

Source code for pymatgen.analysis.diffusion.analyzer

temps ([float]): A sequence of temperatures. units: K diffusivities ([float]): A sequence of diffusivities (e.g., from DiffusionAnalyzer.diffusivity). units: cm^2/s + mode (str): The fitting mode. Supported modes are: + i. "linear" (default), which fits ln(D) vs 1/T. + ii. "exp", which fits D vs T. + Hint: Use "exp" with diffusivity errors if the errors are + not homoscadastic in the linear representation. Avoid using + "exp" without errors. + diffusivity_errors ([float]): A sequence of absolute errors in diffusivities. units: cm^2/s """ - t_1 = 1 / np.array(temps) - logd = np.log(diffusivities) - # Do a least squares regression of log(D) vs 1/T - a = np.array([t_1, np.ones(len(temps))]).T - w, res, _, _ = np.linalg.lstsq(a, logd, rcond=None) - w = np.array(w) - n = len(temps) - std_Ea = (res[0] / (n - 2) / (n * np.var(t_1))) ** 0.5 * const.k / const.e if n > 2 else None - return -w[0] * const.k / const.e, np.exp(w[1]), std_Ea
+ if mode not in ["linear", "exp"]: + raise ValueError("Mode must be 'linear' or 'exp'.") + if mode == "linear": + t_1 = 1 / np.array(temps) + # Do a least squares regression of log(D) vs 1/T + a = np.array([t_1, np.ones(len(temps))]).T + w, res, _, _ = np.linalg.lstsq(a, np.log(diffusivities), rcond=None) + w = np.array(w) + n = len(temps) + std_Ea = (res[0] / (n - 2) / (n * np.var(t_1))) ** 0.5 * const.k / const.e if n > 2 else None + return -w[0] * const.k / const.e, np.exp(w[1]), std_Ea + if mode == "exp": + + def arrhenius(t, Ea, c): + return c * np.exp(-Ea / (const.k / const.e * t)) + + guess = fit_arrhenius(temps, diffusivities, mode="linear")[0:2] # Use linear fit to get initial guess + + popt, pcov = curve_fit(arrhenius, temps, diffusivities, guess, diffusivity_errors) + return popt[0], popt[1], pcov[0, 0] ** 0.5 + return None
@@ -1038,7 +1067,7 @@

Source code for pymatgen.analysis.diffusion.analyzer

[docs] -def get_extrapolated_diffusivity(temps, diffusivities, new_temp): +def get_extrapolated_diffusivity(temps, diffusivities, new_temp, mode: Literal["linear", "exp"] = "linear"): """ Returns (Arrhenius) extrapolated diffusivity at new_temp. @@ -1047,11 +1076,12 @@

Source code for pymatgen.analysis.diffusion.analyzer

diffusivities ([float]): A sequence of diffusivities (e.g., from DiffusionAnalyzer.diffusivity). units: cm^2/s new_temp (float): desired temperature. units: K + mode (str): The fitting mode. See fit_arrhenius for details. Returns: (float) Diffusivity at extrapolated temp in cm^2/s. """ - Ea, c, _ = fit_arrhenius(temps, diffusivities) + Ea, c, _ = fit_arrhenius(temps, diffusivities, mode) return c * np.exp(-Ea / (const.k / const.e * new_temp))
@@ -1081,7 +1111,14 @@

Source code for pymatgen.analysis.diffusion.analyzer

[docs] -def get_arrhenius_plot(temps, diffusivities, diffusivity_errors=None, **kwargs): +def get_arrhenius_plot( + temps, + diffusivities, + diffusivity_errors=None, + mode: Literal["linear", "exp"] = "linear", + unit: Literal["eV", "meV"] = "meV", + **kwargs, +): r""" Returns an Arrhenius plot. @@ -1091,28 +1128,32 @@

Source code for pymatgen.analysis.diffusion.analyzer

from DiffusionAnalyzer.diffusivity). diffusivity_errors ([float]): A sequence of errors for the diffusivities. If None, no error bar is plotted. + mode (str): The fitting mode. See fit_arrhenius for details. + unit (str): The unit for the activation energy. Supported units are + "eV" and "meV". **kwargs: Any keyword args supported by matplotlib.pyplot.plot. Returns: A matplotlib.Axes object. Do ax.show() to show the plot. """ - Ea, c, _ = fit_arrhenius(temps, diffusivities) + Ea, c, _ = fit_arrhenius(temps, diffusivities, mode, diffusivity_errors) from pymatgen.util.plotting import pretty_plot ax = pretty_plot(12, 8) # log10 of the arrhenius fit - arr = c * np.exp(-Ea / (const.k / const.e * np.array(temps))) + t = np.linspace(min(temps), max(temps), 100) if mode == "exp" else np.array(temps) + arr = c * np.exp(-Ea / (const.k / const.e * t)) - t_1 = 1000 / np.array(temps) + x = 1000 / np.array(temps) if mode == "linear" else np.array(temps) - ax.plot(t_1, diffusivities, "ko", t_1, arr, "k--", markersize=10, **kwargs) + _ = ax.plot(x, diffusivities, "ko", x if mode == "linear" else t, arr, "k--", markersize=10, **kwargs) if diffusivity_errors is not None: n = len(diffusivity_errors) ax.errorbar( - t_1[0:n], + x[0:n], diffusivities[0:n], yerr=diffusivity_errors, fmt="ko", @@ -1120,16 +1161,16 @@

Source code for pymatgen.analysis.diffusion.analyzer

capthick=2, linewidth=2, ) - ax.set_yscale("log") + ax.set_yscale("log") if mode == "linear" else None ax.text( - 0.6, + 0.6 if mode == "linear" else 0.1, 0.85, - f"E$_a$ = {(Ea * 1000):.0f} meV", + f"E$_a$ = {(Ea * 1000):.0f} meV" if unit == "meV" else f"E$_a$ = {Ea:.2f} eV", fontsize=30, transform=ax.transAxes, ) ax.set_ylabel("D (cm$^2$/s)") - ax.set_xlabel("1000/T (K$^{-1}$)") + ax.set_xlabel("1000/T (K$^{-1}$)" if mode == "linear" else "T (K)") return ax
diff --git a/docs/_modules/pymatgen/analysis/diffusion/tests/test_analyzer.html b/docs/_modules/pymatgen/analysis/diffusion/tests/test_analyzer.html index d4f2a51..10d69b2 100644 --- a/docs/_modules/pymatgen/analysis/diffusion/tests/test_analyzer.html +++ b/docs/_modules/pymatgen/analysis/diffusion/tests/test_analyzer.html @@ -93,11 +93,17 @@

Source code for pymatgen.analysis.diffusion.tests.test_analyzer

temps = np.array([300, 1000, 500]) diffusivities = c * np.exp(-Ea / (k * temps)) diffusivities *= np.array([1.00601834013, 1.00803236262, 0.98609720824]) + r = fit_arrhenius(temps, diffusivities) self.assertAlmostEqual(r[0], Ea) self.assertAlmostEqual(r[1], c) self.assertAlmostEqual(r[2], 0.000895566) + r = fit_arrhenius(temps, diffusivities, mode="exp", diffusivity_errors=diffusivities * 0.01) + self.assertAlmostEqual(r[0], Ea, 5) + self.assertAlmostEqual(r[1], c, 2) + self.assertAlmostEqual(r[2], 0.000904815) + # when not enough values for error estimate r2 = fit_arrhenius([1, 2], [10, 10]) self.assertAlmostEqual(r2[0], 0) @@ -105,7 +111,12 @@

Source code for pymatgen.analysis.diffusion.tests.test_analyzer

assert r2[2] is None ax = get_arrhenius_plot(temps, diffusivities) - assert isinstance(ax, mpl.axes.Axes)
+ assert isinstance(ax, mpl.axes.Axes) + + ax = get_arrhenius_plot(temps, diffusivities, mode="exp", diffusivity_errors=diffusivities * 0.01, unit="eV") + assert isinstance(ax, mpl.axes.Axes) + assert ax.get_xlabel() == "T (K)" + assert ax.get_ylabel() == "D (cm$^2$/s)"
diff --git a/docs/_modules/pymatgen/analysis/diffusion/utils/edge_data_from_sc.html b/docs/_modules/pymatgen/analysis/diffusion/utils/edge_data_from_sc.html index 0d5fa99..4710602 100644 --- a/docs/_modules/pymatgen/analysis/diffusion/utils/edge_data_from_sc.html +++ b/docs/_modules/pymatgen/analysis/diffusion/utils/edge_data_from_sc.html @@ -78,7 +78,7 @@

Source code for pymatgen.analysis.diffusion.utils.edge_data_from_sc

mg: MigrationGraph, i_sc: Structure, e_sc: Structure, - data_array: list, + data_array: list | str | float, key: str = "custom_key", use_host_sg: bool = True, ) -> None: @@ -106,7 +106,10 @@

Source code for pymatgen.analysis.diffusion.utils.edge_data_from_sc

isite, esite = i_wi[0], e_wi[0] uhop_index, mh_from_sc = get_unique_hop(mg, i_sc, isite, esite, use_host_sg) add_dict = {key: data_array} - mg.add_data_to_similar_edges(target_label=uhop_index, data=add_dict, m_hop=mh_from_sc)
+ if isinstance(data_array, list): + mg.add_data_to_similar_edges(target_label=uhop_index, data=add_dict, m_hop=mh_from_sc) + else: + mg.add_data_to_similar_edges(target_label=uhop_index, data=add_dict)
diff --git a/docs/_modules/pymatgen/analysis/diffusion/utils/tests/test_edge_data_from_sc.html b/docs/_modules/pymatgen/analysis/diffusion/utils/tests/test_edge_data_from_sc.html index 0d7764d..60d43df 100644 --- a/docs/_modules/pymatgen/analysis/diffusion/utils/tests/test_edge_data_from_sc.html +++ b/docs/_modules/pymatgen/analysis/diffusion/utils/tests/test_edge_data_from_sc.html @@ -93,6 +93,16 @@

Source code for pymatgen.analysis.diffusion.utils.tests.test_edge_data_from_ key=test_key, ) + test_single_key = "test_single_key" + test_single = 100 + add_edge_data_from_sc( + mg_Li, + i_sc=input_struct_i, + e_sc=input_struct_e, + data_array=test_single, + key=test_single_key, + ) + edge_data = [] for _u, _v, d in mg_Li.m_graph.graph.edges(data=True): edge_data.append(d) diff --git a/docs/doctrees/environment.pickle b/docs/doctrees/environment.pickle index 12e9e6d..14c772f 100644 Binary files a/docs/doctrees/environment.pickle and b/docs/doctrees/environment.pickle differ diff --git a/docs/doctrees/pymatgen.analysis.diffusion.analyzer.doctree b/docs/doctrees/pymatgen.analysis.diffusion.analyzer.doctree index 6349097..f8af9dc 100644 Binary files a/docs/doctrees/pymatgen.analysis.diffusion.analyzer.doctree and b/docs/doctrees/pymatgen.analysis.diffusion.analyzer.doctree differ diff --git a/docs/doctrees/pymatgen.analysis.diffusion.utils.edge_data_from_sc.doctree b/docs/doctrees/pymatgen.analysis.diffusion.utils.edge_data_from_sc.doctree index 8b9cc19..532fa41 100644 Binary files a/docs/doctrees/pymatgen.analysis.diffusion.utils.edge_data_from_sc.doctree and b/docs/doctrees/pymatgen.analysis.diffusion.utils.edge_data_from_sc.doctree differ diff --git a/docs/pymatgen.analysis.diffusion.analyzer.html b/docs/pymatgen.analysis.diffusion.analyzer.html index 1747498..ba192eb 100644 --- a/docs/pymatgen.analysis.diffusion.analyzer.html +++ b/docs/pymatgen.analysis.diffusion.analyzer.html @@ -366,7 +366,7 @@

Navigation

-fit_arrhenius(temps, diffusivities)[source]
+fit_arrhenius(temps: Sequence[float], diffusivities: Sequence[float], mode: Literal['linear', 'exp'] = 'linear', diffusivity_errors: Sequence[float] | None = None) → tuple[float, float, float | None][source]
Returns Ea, c, standard error of Ea from the Arrhenius fit.

D = c * exp(-Ea/kT).

@@ -377,6 +377,18 @@

Navigation

  • temps ([float]) – A sequence of temperatures. units: K

  • diffusivities ([float]) – A sequence of diffusivities (e.g., from DiffusionAnalyzer.diffusivity). units: cm^2/s

    • +

  • mode (str) –

    +
    The fitting mode. Supported modes are:
      +

    1. ”linear” (default), which fits ln(D) vs 1/T.

      2. +

    2. ”exp”, which fits D vs T.

      3. +
    +
    +
    +

    Hint: Use “exp” with diffusivity errors if the errors are +not homoscadastic in the linear representation. Avoid using +“exp” without errors.

    +

    • +

  • diffusivity_errors ([float]) – A sequence of absolute errors in diffusivities. units: cm^2/s

    • @@ -384,7 +396,7 @@

    Navigation

    -get_arrhenius_plot(temps, diffusivities, diffusivity_errors=None, **kwargs)[source]
    +get_arrhenius_plot(temps, diffusivities, diffusivity_errors=None, mode: Literal['linear', 'exp'] = 'linear', unit: Literal['eV', 'meV'] = 'meV', **kwargs)[source]

    Returns an Arrhenius plot.

    Parameters:
    @@ -394,6 +406,9 @@

    Navigation

    from DiffusionAnalyzer.diffusivity).

  • diffusivity_errors ([float]) – A sequence of errors for the diffusivities. If None, no error bar is plotted.

    • +

  • mode (str) – The fitting mode. See fit_arrhenius for details.

    • +

  • unit (str) – The unit for the activation energy. Supported units are +“eV” and “meV”.

  • **kwargs – Any keyword args supported by matplotlib.pyplot.plot.

    • @@ -486,7 +501,7 @@

    Navigation

    -get_extrapolated_diffusivity(temps, diffusivities, new_temp)[source]
    +get_extrapolated_diffusivity(temps, diffusivities, new_temp, mode: Literal['linear', 'exp'] = 'linear')[source]

    Returns (Arrhenius) extrapolated diffusivity at new_temp.

    Parameters:
    @@ -495,6 +510,7 @@

    Navigation

  • diffusivities ([float]) – A sequence of diffusivities (e.g., from DiffusionAnalyzer.diffusivity). units: cm^2/s

  • new_temp (float) – desired temperature. units: K

    • +

  • mode (str) – The fitting mode. See fit_arrhenius for details.

    • Returns:
    diff --git a/docs/pymatgen.analysis.diffusion.utils.edge_data_from_sc.html b/docs/pymatgen.analysis.diffusion.utils.edge_data_from_sc.html index 3247fe9..08a132f 100644 --- a/docs/pymatgen.analysis.diffusion.utils.edge_data_from_sc.html +++ b/docs/pymatgen.analysis.diffusion.utils.edge_data_from_sc.html @@ -50,7 +50,7 @@

    Navigation

    Function to add edge data to MigrationGraph through 2 SC structures.

    -add_edge_data_from_sc(mg: MigrationGraph, i_sc: Structure, e_sc: Structure, data_array: list, key: str = 'custom_key', use_host_sg: bool = True) → None[source]
    +add_edge_data_from_sc(mg: MigrationGraph, i_sc: Structure, e_sc: Structure, data_array: list | str | float, key: str = 'custom_key', use_host_sg: bool = True) → None[source]

    Add a data entry and key to edges within FullPathMapper object with the same hop_label. These hops are equivalent by symmetry to the 2 positions given in the supercell structures.

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100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -56,7 +56,7 @@ dependencies = [ "ase", "seaborn" ] -version = "2024.6.27" +version = "2024.7.15" [project.urls] Homepage = "http://materialsvirtuallab.github.io/pymatgen-analysis-diffusion/" diff --git a/tasks.py b/tasks.py index 67dae48..9667e7c 100644 --- a/tasks.py +++ b/tasks.py @@ -74,6 +74,7 @@ def set_ver(ctx): ) with open("pyproject.toml", "w") as f: f.write("\n".join(lines)) + f.write("\n") ctx.run("ruff format pyproject.toml")