from pathlib import Path
from typing import List, NamedTuple, Tuple
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from matplotlib.axes import Axes
from mendeleev import element
from sqlalchemy.exc import NoResultFound
script_path = Path(__file__).parent.absolute()
plt.style.use(str("/".join([str(script_path), "plots.mplstyle"])))
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class OrbitalsInfo(NamedTuple):
orbital: List[str]
principal_quantum_number: List[int]
orbital_letter: List[str]
azimuthal_quantum_number: List[int]
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class SlaterInfo(NamedTuple):
effective_nuclear_charge: list
screening_values: list
screening_percentage: list
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class ClementiInfo(NamedTuple):
effective_nuclear_charge: list
screening_values: list
screening_percentage: list
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def orbitals(name: str) -> OrbitalsInfo:
"""Extracts n, l, and nl notation from electronic configuration info of
the Mendeleev package.
Parameters
----------
name : str
Name or symbol for the chemical element.
Returns
-------
OrbitalsInfo
A NamedTuple containing lists with orbital representation (nl notation),
principal quantum number (n), orbital letter notation (l), and
azimuthal quantum number.
Raises
------
NoResultFound
If the provided element name or symbol is not valid.
"""
try:
elem = element(name)
except NoResultFound as e:
raise NoResultFound(f"Invalid element name or symbol: {name}") from e
dict_l = {"s": 0, "p": 1, "d": 2, "f": 3}
orbital, orbital_n, orbital_l, orbital_l_num = [], [], [], []
for (n, l), _ in elem.ec.conf.items():
orbital_n.append(n)
orbital_l.append(l)
orbital_l_num.append(dict_l.get(l, -1))
orbital.append(f"{n}{l}")
return OrbitalsInfo(orbital, orbital_n, orbital_l, orbital_l_num)
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def slater(name: str) -> SlaterInfo:
"""Calculates Slater's screening values, effective nuclear charge, and
screening percentages for each orbital of an element's electronic configuration.
Parameters
----------
name : str
Name or symbol for the chemical element.
Returns
-------
SlaterInfo
A NamedTuple containing lists of effective nuclear charge values,
screening values, and screening percentages for each orbital.
"""
orbital_info = orbitals(name)
elem = element(name)
zeff_slater = []
slater_s = []
for n, l in zip(orbital_info.principal_quantum_number, orbital_info.orbital_letter):
screening = elem.ec.slater_screening(n, l)
slater_s.append(screening)
zeff_slater.append(elem.atomic_number - screening)
slater_s_percent = [(i / elem.atomic_number) * 100 for i in slater_s]
return SlaterInfo(zeff_slater, slater_s, slater_s_percent)
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def clementi(name: str) -> ClementiInfo:
"""Calculates screening and effective nuclear charge based on values
calculated by Clementi and Raimond. No values for Z > 86.
Parameters
----------
name : str
Name or symbol for the chemical element.
Returns
-------
ClementiInfo
A NamedTuple containing lists of effective nuclear charge values,
screening values, and screening percentages for each orbital.
"""
orbital_info = orbitals(name)
elem = element(name)
zeff_clementi = []
clementi_s = []
if elem.atomic_number < 87:
for n, l in zip(
orbital_info.principal_quantum_number, orbital_info.orbital_letter
):
screening = elem.atomic_number - elem.zeff(n, l, method="clementi")
clementi_s.append(screening)
zeff_clementi.append(elem.zeff(n, l, method="clementi"))
else:
for _ in orbital_info.principal_quantum_number:
clementi_s.append(np.nan)
zeff_clementi.append(np.nan)
clementi_s_percent = [(i / elem.atomic_number) * 100 for i in clementi_s]
return ClementiInfo(zeff_clementi, clementi_s, clementi_s_percent)
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def elem_data(name: str) -> pd.DataFrame:
"""Data summary for a given element.
Parameters
----------
name : str
Name or symbol for the chemical element.
Returns
-------
pd.DataFrame
Summary of Zeff and S for a given element with Slater and Clementi
screening values.
"""
slater_info = slater(name)
clementi_info = clementi(name)
orbital_info = orbitals(name)
data = pd.DataFrame(
{
"n": orbital_info.principal_quantum_number,
"l": orbital_info.orbital_letter,
"l_num": orbital_info.azimuthal_quantum_number,
"Orbital": orbital_info.orbital,
"Zeff Slater": slater_info.effective_nuclear_charge,
"S Slater": slater_info.screening_values,
"% S Slater": slater_info.screening_percentage,
"Zeff Clementi": clementi_info.effective_nuclear_charge,
"S Clementi": clementi_info.screening_values,
"% S Clementi": clementi_info.screening_percentage,
}
)
data_org = data.sort_values(by=["n", "l_num"]).reset_index(drop=True)
return data_org
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def plot_slater_zeff(name: str, ax=None, **kwargs) -> Axes:
"""Plots effective nuclear charge (Slater) per orbital.
Parameters
----------
name : str
String with the element symbol.
ax : matplotlib.axes._subplots.AxesSubplot, optional
Axes for the plot. If None, a new figure and axes object is created.
**kwargs
Additional keyword arguments for the plot.
Returns
-------
matplotlib.axes._subplots.AxesSubplot
The Axes object with the plot.
"""
data = elem_data(name)
if ax is None:
fig, ax = plt.subplots()
x = data["Orbital"]
y = data["Zeff Slater"]
ax.set_ylabel("Effective nuclear charge")
ax.set_xlabel("Orbitals")
ax.set_xticks(range(len(data)))
ax.set_yticks(np.arange(0, round(max(y)) + 5, 5.0))
ax.plot(x, y, label=f"Zeff Slater {element(name).symbol}", **kwargs)
ax.legend(
loc="best",
shadow=False,
fancybox=True,
bbox_to_anchor=(1, 1),
)
return ax
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def plot_slater_screening(name: str, ax=None, **kwargs) -> Axes:
"""Plots Shielding /% (Slater) per orbital.
Parameters
----------
name : str
String with the element symbol.
ax : matplotlib.axes._subplots.AxesSubplot, optional
Axes for the plot. If None, a new figure and axes object is created.
**kwargs
Additional keyword arguments for the plot.
Returns
-------
matplotlib.axes._subplots.AxesSubplot
The Axes object with the plot.
"""
data = elem_data(name)
if ax is None:
fig, ax = plt.subplots()
x = data["Orbital"]
y = data["% S Slater"]
ax.set_ylabel("Shielding / %")
ax.set_xlabel("Orbitals")
ax.set_xticks(range(len(data)))
ax.set_yticks(np.arange(0, round(max(y)) + 5, 10.0))
ax.plot(x, y, label=f"Shielding % Slater {element(name).symbol}", **kwargs)
ax.legend(loc="best", shadow=True, fancybox=True)
return ax
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def plot_clementi_zeff(name: str, ax=None, **kwargs) -> Axes:
"""Plots effective nuclear charge (Clementi) per orbital.
Parameters
----------
name : str
String with the element symbol.
ax : matplotlib.axes._subplots.AxesSubplot, optional
Axes for the plot. If None, a new figure and axes object is created.
**kwargs
Additional keyword arguments for the plot.
Returns
-------
matplotlib.axes._subplots.AxesSubplot
The Axes object with the plot.
"""
data = elem_data(name)
if ax is None:
fig, ax = plt.subplots()
x = data["Orbital"]
y = data["Zeff Clementi"]
ax.set_ylabel("Effective nuclear charge")
ax.set_xlabel("Orbitals")
ax.set_xticks(range(len(data)))
ax.set_yticks(np.arange(0, round(max(y)) + 5, 5.0))
ax.plot(x, y, label=f"Zef Clementi {element(name).symbol}", **kwargs)
ax.legend(loc="best", shadow=False, fancybox=True, bbox_to_anchor=(1, 1))
return ax
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def plot_clementi_screening(name: str, ax=None, **kwargs) -> Axes:
"""Plots Shielding /% (Clementi) per orbital.
Parameters
----------
name : str
String with the element symbol.
ax : matplotlib.axes._subplots.AxesSubplot, optional
Axes for the plot. If None, a new figure and axes object is created.
**kwargs
Additional keyword arguments for the plot.
Returns
-------
matplotlib.axes._subplots.AxesSubplot
The Axes object with the plot.
"""
data = elem_data(name)
if ax is None:
fig, ax = plt.subplots()
x = data["Orbital"]
y = data["% S Clementi"]
ax.set_ylabel("Shielding / %")
ax.set_xlabel("Orbitals")
ax.set_xticks(range(len(data)))
ax.set_yticks(np.arange(0, round(max(y)) + 5, 10.0))
ax.plot(x, y, label=f"Shielding % Clementi {element(name).symbol}", **kwargs)
ax.legend(loc="best", shadow=True, fancybox=True)
return ax
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def plot_slater_both(name: str, ax=None) -> Tuple[Axes, Axes]:
"""Plots Effective nuclear charge and shielding /% (Slater) per orbital.
Parameters
----------
name : str
String with the element symbol.
ax : matplotlib.axes._subplots.AxesSubplot, optional
Axes for the plot. If None, a new figure and axes object is created.
Returns
-------
Tuple[matplotlib.axes._subplots.AxesSubplot, matplotlib.axes._subplots.AxesSubplot]
The Axes objects with the plot.
"""
data = elem_data(name)
if ax is None:
fig, ax = plt.subplots()
x = data["Orbital"]
y = data["Zeff Slater"]
ax.set_ylabel("Effective nuclear charge", color="C0")
ax.set_xlabel("Orbitals")
line1 = ax.plot(x, y, label=f"Zef Slater {element(name).symbol}", color="C0")
for t in ax.get_yticklabels():
t.set_color("C0")
ax.set_xticks(range(len(data)))
ax.set_yticks(np.linspace(0, round(max(y)) + 1, 5))
ax2 = ax.twinx()
y2 = data["% S Slater"]
line2 = ax2.plot(
x,
y2,
label=f"Shielding % Slater {element(name).symbol}",
color="C1",
)
for t in ax2.get_yticklabels():
t.set_color("C1")
ax2.set_ylabel("Shielding / %", color="C1")
ax2.set_yticks(np.linspace(0, round(max(y2)) + 1, 5))
lines = line1 + line2
labels = [line.get_label() for line in lines]
ax2.legend(lines, labels, loc="upper center", shadow=True, fancybox=True)
# keep only the vertical grids
ax.grid(visible=False)
ax2.grid(visible=False)
ax.grid(visible=True, which="major", axis="x")
return ax, ax2
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def plot_clementi_both(name: str, ax=None) -> Tuple[Axes, Axes]:
"""Plots Effective nuclear charge and shielding /% (Clementi) per orbital.
Parameters
----------
name : str
String with the element symbol.
ax : matplotlib.axes._subplots.AxesSubplot, optional
Axes for the plot. If None, a new figure and axes object is created.
Returns
-------
Tuple[matplotlib.axes._subplots.AxesSubplot, matplotlib.axes._subplots.AxesSubplot]
The Axes objects with the plot.
"""
data = elem_data(name)
if ax is None:
fig, ax = plt.subplots()
x = data["Orbital"]
y = data["Zeff Clementi"]
ax.set_ylabel("Effective nuclear charge", color="C0")
ax.set_xlabel("Orbitals")
line1 = ax.plot(x, y, label=f"Zef Clementi {element(name).symbol}", color="C0")
for t in ax.get_yticklabels():
t.set_color("C0")
ax.set_xticks(range(len(data)))
ax.set_yticks(np.linspace(0, round(max(y)) + 1, 5))
ax2 = ax.twinx()
y2 = data["% S Clementi"]
line2 = ax2.plot(
x,
y2,
label=f"Shielding % Clementi {element(name).symbol}",
color="C1",
)
for t in ax2.get_yticklabels():
t.set_color("C1")
ax2.set_ylabel("Shielding / %", color="C1")
ax2.set_yticks(np.linspace(0, round(max(y2)) + 1, 5))
lines = line1 + line2
labels = [line.get_label() for line in lines]
ax2.legend(lines, labels, loc="upper center", shadow=True, fancybox=True)
# keep only the vertical grids
ax.grid(visible=False)
ax2.grid(visible=False)
ax.grid(visible=True, which="major", axis="x")
return ax, ax2