Move needlessly function-scoped imports to module scope

.pre-commit-config.yaml

@@ -8,7 +8,7 @@ ci:
 
 repos:
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.1.4
+    rev: v0.1.5
     hooks:
       - id: ruff
         args: [--fix]

dev_scripts/regen_libxcfunc.py

@@ -12,6 +12,7 @@
 import json
 import os
 import sys
+from copy import deepcopy
 
 
 def parse_libxc_docs(path):
@@ -46,8 +47,6 @@ def parse_section(section):
 
 def write_libxc_docs_json(xcfuncs, jpath):
     """Write json file with libxc metadata to path jpath."""
-    from copy import deepcopy
-
     xcfuncs = deepcopy(xcfuncs)
 
     # Remove XC_FAMILY from Family and XC_ from Kind to make strings more human-readable.

dev_scripts/update_pt_data.py

@@ -7,10 +7,13 @@
 
 from __future__ import annotations
 
+import collections
 import json
 import re
 from itertools import product
 
+import requests
+from bs4 import BeautifulSoup
 from monty.serialization import dumpfn, loadfn
 from ruamel import yaml
 
@@ -160,7 +163,6 @@ def update_ionic_radii():
 def parse_shannon_radii():
     with open("periodic_table.yaml") as f:
         data = yaml.load(f)
-    import collections
 
     from openpyxl import load_workbook
 
@@ -250,8 +252,6 @@ def gen_iupac_ordering():
 
 def add_electron_affinities():
     """Update the periodic table data file with electron affinities."""
-    import requests
-    from bs4 import BeautifulSoup
 
     req = requests.get("https://wikipedia.org/wiki/Electron_affinity_(data_page)")
     soup = BeautifulSoup(req.text, "html.parser")
@@ -276,9 +276,6 @@ def add_electron_affinities():
 
 def add_ionization_energies():
     """Update the periodic table data file with ground level and ionization energies from NIST."""
-    import collections
-
-    from bs4 import BeautifulSoup
 
     with open("NIST Atomic Ionization Energies Output.html") as f:
         soup = BeautifulSoup(f.read(), "html.parser")

pymatgen/analysis/bond_valence.py

@@ -117,13 +117,13 @@ class BVAnalyzer:
     is selected.
     """
 
-    CHARGE_NEUTRALITY_TOLERANCE = 0.00001
+    CHARGE_NEUTRALITY_TOLERANCE = 0.000_01
 
     def __init__(
         self,
         symm_tol=0.1,
         max_radius=4,
-        max_permutations=100000,
+        max_permutations=100_000,
         distance_scale_factor=1.015,
         charge_neutrality_tolerance=CHARGE_NEUTRALITY_TOLERANCE,
         forbidden_species=None,

pymatgen/analysis/chemenv/connectivity/connected_components.py

@@ -5,6 +5,7 @@
 import itertools
 import logging
 
+import matplotlib.pyplot as plt
 import networkx as nx
 import numpy as np
 from matplotlib.patches import Circle, FancyArrowPatch
@@ -533,7 +534,6 @@ def show_graph(
                 If not provided, the graph is not saved.
             drawing_type (str): The type of drawing to use. Can be "internal" or "external".
         """
-        import matplotlib.pyplot as plt
 
         shown_graph = self._connected_subgraph if graph is None else graph
 
@@ -550,12 +550,8 @@ def show_graph(
                 plt.savefig(save_file)
             # nx.draw(self._connected_subgraph)
         elif drawing_type == "draw_graphviz":
-            import networkx as nx
-
             nx.nx_pydot.graphviz_layout(shown_graph)
         elif drawing_type == "draw_random":
-            import networkx as nx
-
             nx.draw_random(shown_graph)
 
     @property

pymatgen/analysis/chemenv/coordination_environments/coordination_geometries.py

@@ -697,15 +697,15 @@ def pauling_stability_ratio(self):
             if self.ce_symbol in ["S:1", "L:2"]:
                 self._pauling_stability_ratio = 0.0
             else:
-                min_dist_anions = 1000000.0
-                min_dist_cation_anion = 1000000.0
+                min_dist_anions = 1_000_000
+                min_dist_cation_anion = 1_000_000
                 for ipt1 in range(len(self.points)):
                     pt1 = np.array(self.points[ipt1])
                     min_dist_cation_anion = min(min_dist_cation_anion, np.linalg.norm(pt1 - self.central_site))
                     for ipt2 in range(ipt1 + 1, len(self.points)):
                         pt2 = np.array(self.points[ipt2])
                         min_dist_anions = min(min_dist_anions, np.linalg.norm(pt1 - pt2))
-                anion_radius = min_dist_anions / 2.0
+                anion_radius = min_dist_anions / 2
                 cation_radius = min_dist_cation_anion - anion_radius
                 self._pauling_stability_ratio = cation_radius / anion_radius
         return self._pauling_stability_ratio

pymatgen/analysis/chemenv/coordination_environments/structure_environments.py

@@ -8,9 +8,12 @@
 
 from __future__ import annotations
 
-from typing import TYPE_CHECKING
-
+import matplotlib.pyplot as plt
 import numpy as np
+from matplotlib import cm
+from matplotlib.colors import Normalize
+from matplotlib.gridspec import GridSpec
+from matplotlib.patches import Polygon
 from monty.json import MontyDecoder, MSONable, jsanitize
 
 from pymatgen.analysis.chemenv.coordination_environments.coordination_geometries import AllCoordinationGeometries
@@ -19,9 +22,6 @@
 from pymatgen.analysis.chemenv.utils.defs_utils import AdditionalConditions
 from pymatgen.core import Element, PeriodicNeighbor, PeriodicSite, Species, Structure
 
-if TYPE_CHECKING:
-    import matplotlib.pyplot as plt
-
 __author__ = "David Waroquiers"
 __copyright__ = "Copyright 2012, The Materials Project"
 __credits__ = "Geoffroy Hautier"
@@ -645,11 +645,6 @@ def plot_csm_and_maps(self, isite, max_csm=8.0):
             isite: Index of the site for which the plot has to be done
             max_csm: Maximum continuous symmetry measure to be shown.
         """
-        try:
-            import matplotlib.pyplot as plt
-        except ImportError:
-            print('Plotting Chemical Environments requires matplotlib ... exiting "plot" function')
-            return
         fig = self.get_csm_and_maps(isite=isite, max_csm=max_csm)
         if fig is None:
             return
@@ -673,13 +668,6 @@ def get_csm_and_maps(
         Returns:
             Matplotlib figure and axes representing the CSM and maps.
         """
-        try:
-            import matplotlib.pyplot as plt
-            from matplotlib.gridspec import GridSpec
-        except ImportError:
-            print('Plotting Chemical Environments requires matplotlib ... exiting "plot" function')
-            return None
-
         if symmetry_measure_type is None:
             symmetry_measure_type = "csm_wcs_ctwcc"
         # Initializes the figure
@@ -826,15 +814,6 @@ def get_environments_figure(
         Returns:
             tuple[plt.Figure, plt.Axes]: matplotlib figure and axes representing the environments.
         """
-        try:
-            import matplotlib.pyplot as plt
-            from matplotlib import cm
-            from matplotlib.colors import Normalize
-            from matplotlib.patches import Polygon
-        except ImportError:
-            print('Plotting Chemical Environments requires matplotlib ... exiting "plot" function')
-            return None
-
         # Initializes the figure
         fig = plt.figure(figsize=figsize)
         ax = fig.add_subplot(111)

pymatgen/analysis/chemenv/coordination_environments/voronoi.py

@@ -5,6 +5,7 @@
 import logging
 import time
 
+import matplotlib.pyplot as plt
 import numpy as np
 from monty.json import MSONable
 from scipy.spatial import Voronoi
@@ -793,8 +794,6 @@ def get_rdf_figure(self, isite, normalized=True, figsize=None, step_function=Non
         def dp_func(dp):
             return 1.0 - 1.0 / np.power(dp, 3.0)
 
-        import matplotlib.pyplot as plt
-
         if step_function is None:
             step_function = {"type": "normal_cdf", "scale": 0.0001}
 
@@ -845,8 +844,6 @@ def get_sadf_figure(self, isite, normalized=True, figsize=None, step_function=No
         def ap_func(ap):
             return np.power(ap, -0.1)
 
-        import matplotlib.pyplot as plt
-
         if step_function is None:
             step_function = {"type": "step_function", "scale": 0.0001}
 

pymatgen/analysis/diffraction/core.py

@@ -6,8 +6,8 @@
 import collections
 from typing import TYPE_CHECKING
 
+import matplotlib.pyplot as plt
 import numpy as np
-from matplotlib import pyplot as plt
 
 from pymatgen.core.spectrum import Spectrum
 from pymatgen.util.plotting import add_fig_kwargs, pretty_plot
@@ -186,7 +186,6 @@ def plot_structures(self, structures, fontsize=6, **kwargs):
                 long version, e.g. (1, 0, 0). If None, do not show anything.
             fontsize: (int) fontsize for peak labels.
         """
-        import matplotlib.pyplot as plt
 
         nrows = len(structures)
         fig, axes = plt.subplots(nrows=nrows, ncols=1, sharex=True, squeeze=False)

pymatgen/analysis/dimensionality.py

@@ -26,6 +26,7 @@
 import itertools
 from collections import defaultdict
 
+import networkx as nx
 import numpy as np
 from networkx.readwrite import json_graph
 
@@ -121,8 +122,6 @@ def get_structure_components(
         - "molecule_graph": If inc_molecule_graph is `True`, the site a
             MoleculeGraph object for zero-dimensional components.
     """
-    import networkx as nx  # optional dependency therefore not top level import
-
     comp_graphs = (bonded_structure.graph.subgraph(c) for c in nx.weakly_connected_components(bonded_structure.graph))
 
     components = []
@@ -261,8 +260,6 @@ def zero_d_graph_to_molecule_graph(bonded_structure, graph):
     Returns:
         (MoleculeGraph): A MoleculeGraph object of the component.
     """
-    import networkx as nx
-
     seen_indices = []
     sites = []
 

pymatgen/analysis/eos.py

@@ -1,5 +1,4 @@
-"""
-This module implements various equation of states.
+"""This module implements various equation of states.
 
 Note: Most of the code were initially adapted from ASE and deltafactor by
 @gmatteo but has since undergone major refactoring.
@@ -20,7 +19,7 @@
 from pymatgen.util.plotting import add_fig_kwargs, get_ax_fig, pretty_plot
 
 if TYPE_CHECKING:
-    from matplotlib import pyplot as plt
+    import matplotlib.pyplot as plt
 
 __author__ = "Kiran Mathew, gmatteo"
 __credits__ = "Cormac Toher"
@@ -426,12 +425,11 @@ def fit(self, min_ndata_factor=3, max_poly_order_factor=5, min_poly_order=2):
         Args:
             min_ndata_factor (int): parameter that controls the minimum number
                 of data points that will be used for fitting.
-                minimum number of data points =
-                    total data points-2*min_ndata_factor
+                minimum number of data points = total data points-2*min_ndata_factor
             max_poly_order_factor (int): parameter that limits the max order
                 of the polynomial used for fitting.
                 max_poly_order = number of data points used for fitting -
-                                 max_poly_order_factor
+                max_poly_order_factor
             min_poly_order (int): minimum order of the polynomial to be
                 considered for fitting.
         """

pymatgen/analysis/graphs.py

@@ -1041,9 +1041,7 @@ def as_dict(self):
 
     @classmethod
     def from_dict(cls, d):
-        """
-        As in pymatgen.core.Structure except
-        restoring graphs using `from_dict_of_dicts`
+        """As in pymatgen.core.Structure except restoring graphs using from_dict_of_dicts
         from NetworkX to restore graph information.
         """
         struct = Structure.from_dict(d["structure"])

pymatgen/analysis/local_env.py

@@ -301,7 +301,7 @@ def get_cn(
                 'take_max_species' will use Fe as the site specie.
 
         Returns:
-            cn (int or float): coordination number.
+            cn (float): coordination number.
         """
         structure = _handle_disorder(structure, on_disorder)
         siw = self.get_nn_info(structure, n)
@@ -4009,7 +4009,7 @@ def get_cn(self, structure: Structure, n: int, **kwargs) -> float:  # type: igno
                 'take_max_species' will use Fe as the site specie.
 
         Returns:
-            cn (int or float): coordination number.
+            cn (float): coordination number.
         """
         use_weights = kwargs.get("use_weights", False)
         if self.weighted_cn != use_weights: