[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

setup.py

@@ -1,4 +1,5 @@
 """Setup the package."""
+
 from setuptools import setup
 
 setup()

src/hmf/__init__.py

@@ -1,4 +1,5 @@
 """A package for producing halo mass functions under Spherical Collapse."""
+
 try:
     from importlib.metadata import PackageNotFoundError, version
 except ImportError:

src/hmf/_cli.py

@@ -1,4 +1,5 @@
 """Module that contains the command line app."""
+
 import click
 import importlib
 import numpy as np

src/hmf/_internals/__init__.py

@@ -2,6 +2,7 @@
 
 These define the structure of the entire library.
 """
+
 from ._cache import cached_quantity, parameter
 from ._framework import (
     Component,

src/hmf/_internals/_cache.py

@@ -6,6 +6,7 @@
 functionality of being automatically updated when a parent property is
 updated.
 """
+
 import warnings
 from copy import deepcopy
 from functools import update_wrapper
@@ -104,9 +105,9 @@ def _get_property(self):
         # if name is already there, can only be because the method has been supered.
         supered = name in activeq
         if not supered:
-            recalc_prpa[
-                name
-            ] = set()  # Empty set to which parameter names will be added
+            recalc_prpa[name] = (
+                set()
+            )  # Empty set to which parameter names will be added
             activeq.add(name)
 
         # Go ahead and calculate the value -- each parameter accessed will add itself to the index.

src/hmf/_internals/_framework.py

@@ -1,4 +1,5 @@
 """Classes defining the overall structure of the hmf framework."""
+
 import copy
 import deprecation
 import logging

src/hmf/alternatives/__init__.py

@@ -2,4 +2,5 @@
 A subpackage dedicated to providing "plugin"-style alternatives to the standard halo mass function, for example
 Warm Dark Matter cosmologies.
 """
+
 from . import wdm

src/hmf/cosmology/__init__.py

@@ -1,4 +1,5 @@
 """Cosmographic calculations, and other purely cosmological quantities, such as growth factor."""
+
 from . import cosmo
 from .cosmo import Cosmology, astropy_to_colossus
 from .growth_factor import GrowthFactor

src/hmf/cosmology/growth_factor.py

@@ -30,6 +30,7 @@ class _GrowthFactor(Cmpt):
     r"""
     General class for a growth factor calculation.
     """
+
     supported_cosmos = (cosmology.LambdaCDM,)
 
     def __init__(self, cosmo, **model_parameters):
@@ -64,6 +65,7 @@ class GrowthFactor(_GrowthFactor):
     ----------
     .. [1] Lukic et. al., ApJ, 2007, http://adsabs.harvard.edu/abs/2007ApJ...671.1160L
     """
+
     _defaults = {"dlna": 0.01, "amin": 1e-8}
 
     def __init__(self, *args, **kwargs):

src/hmf/density_field/__init__.py

@@ -2,6 +2,7 @@
 A subpackage dedicated to basic measures of the matter density field -- its 2-point structure, cosmological transfer
 functions, and filter functions which can be applied to it.
 """
+
 from . import filters, transfer, transfer_models
 from .filters import Filter
 from .halofit import halofit

src/hmf/density_field/halofit.py

@@ -6,6 +6,7 @@
 and Michael Schneider (https://code.google.com/p/chomp/). It has
 been modified to improve its integration with this package.
 """
+
 import numpy as np
 import warnings
 from scipy.integrate import simps as _simps

src/hmf/density_field/transfer.py

@@ -5,6 +5,7 @@
 calculate the transfer function, matter power spectrum and several other
 related quantities.
 """
+
 import numpy as np
 
 from .._internals._cache import cached_quantity, parameter

src/hmf/density_field/transfer_models.py

@@ -4,6 +4,7 @@
 Note that these are not transfer function "frameworks". The framework is found
 in :mod:`hmf.transfer`.
 """
+
 import numpy as np
 import pickle
 import warnings
@@ -462,9 +463,7 @@ def _set_params(self):
         self.z_eq = 2.5e4 * self.Omh2 * self.theta_cmb ** (-4)  # really 1+z
         self.k_eq = 7.46e-2 * self.Omh2 * self.theta_cmb ** (-2)  # units Mpc^-1 (no h!)
 
-        self.z_drag_b1 = (
-            0.313 * self.Omh2**-0.419 * (1.0 + 0.607 * self.Omh2**0.674)
-        )
+        self.z_drag_b1 = 0.313 * self.Omh2**-0.419 * (1.0 + 0.607 * self.Omh2**0.674)
         self.z_drag_b2 = 0.238 * self.Omh2**0.223
         self.z_drag = (
             1291.0
@@ -686,6 +685,7 @@ class attribute.
     .. math:: \Gamma \rightarrow \Gamma
               \exp\left(-\Omega_{b,0}(1 + \sqrt{2h}/\Omega_{m,0})\right).
     """
+
     _defaults = {
         "a": 2.34,
         "b": 3.89,
@@ -760,6 +760,7 @@ class attribute.
 
     .. math:: \alpha = \frac{0.3\times 0.75^2}{\Omega_{m,0} h^2}.
     """
+
     _defaults = {"a": 37.1, "b": 21.1, "c": 10.8, "nu": 1.12}
 
     def lnt(self, lnk):

src/hmf/halos/mass_definitions.py

@@ -3,6 +3,7 @@
 This is primarily inspired by Benedikt Diemer's COLOSSUS code:
 https://bdiemer.bitbucket.io/colossus/halo_mass_defs.html
 """
+
 import astropy.units as u
 import numpy as np
 import scipy as sp
@@ -366,8 +367,7 @@ def h(x):
             return np.log(1.0 + x) - x / (1.0 + x)
 
     fnc = (
-        lambda x, rhos, density_threshold: rhos * h(x) * 3.0 / x**3
-        - density_threshold
+        lambda x, rhos, density_threshold: rhos * h(x) * 3.0 / x**3 - density_threshold
     )
 
     while x is None and i < len(XDELTA_GUESS_FACTORS):

src/hmf/helpers/cfg_utils.py

@@ -1,4 +1,5 @@
 """Utilities for interacting with hmf TOML configs."""
+
 from astropy.units import Quantity
 from datetime import datetime
 from inspect import signature

src/hmf/helpers/sample.py

@@ -3,6 +3,7 @@
 
 Provides routines for sampling theoretical functions, and for binning sampled data.
 """
+
 import numpy as np
 from scipy.interpolate import InterpolatedUnivariateSpline as _spline
 

src/hmf/mass_function/__init__.py

@@ -1,4 +1,5 @@
 """Subpackage for determining the halo mass function in Spherical Collapse."""
+
 from . import fitting_functions, hmf, integrate_hmf
 from .fitting_functions import PS, SMT, FittingFunction, Tinker08
 from .hmf import MassFunction

src/hmf/mass_function/fitting_functions.py

@@ -178,6 +178,7 @@ class FittingFunction(_framework.Component):
 
     In that example, we did not specify :attr:`cutmask`.
     """
+
     _pdocs = r"""
 
     Parameters
@@ -641,8 +642,7 @@ def fsigma(self):
             * (1.0 + (1.0 / (a * self.nu**2)) ** p + 0.6 * G_1 + 0.4 * G_2)
             * self.nu
             * np.exp(
-                -c * a * self.nu**2 / 2.0
-                - 0.03 * self.nu**0.6 / (self.n_eff + 3) ** 2
+                -c * a * self.nu**2 / 2.0 - 0.03 * self.nu**0.6 / (self.n_eff + 3) ** 2
             )
         )
 
@@ -1516,9 +1516,7 @@ def normalise(self):
                 * self.beta ** (-2 * self.phi)
                 * self.gamma ** (-0.5 - self.eta)
                 * (
-                    2**self.phi
-                    * self.beta ** (2 * self.phi)
-                    * sp.gamma(self.eta + 0.5)
+                    2**self.phi * self.beta ** (2 * self.phi) * sp.gamma(self.eta + 0.5)
                     + self.gamma**self.phi * sp.gamma(0.5 + self.eta - self.phi)
                 )
             )

src/hmf/mass_function/integrate_hmf.py

@@ -1,6 +1,7 @@
 """
 A supporting module that provides a routine to integrate the differential hmf in a robust manner.
 """
+
 import numpy as np
 import scipy.integrate as intg
 from scipy.interpolate import InterpolatedUnivariateSpline as _spline
@@ -64,9 +65,7 @@ def hmf_integral_gtm(M, dndm, mass_density=False):
 
     # Calculate the mass function (and its integral) from the highest M up to 10**18
     if m[-1] < m[0] * 10**18 / m[3]:
-        m_upper = np.arange(
-            np.log(m[-1]), np.log(10**18), np.log(m[1]) - np.log(m[0])
-        )
+        m_upper = np.arange(np.log(m[-1]), np.log(10**18), np.log(m[1]) - np.log(m[0]))
         mf_func = _spline(np.log(m), np.log(dndlnm), k=1)
         mf = mf_func(m_upper)
 

tests/test_genmf.py

@@ -41,6 +41,7 @@
     'transfer__k_per_logint': 0,
     'transfer__kmax':100.0
 """
+
 import pytest
 
 import numpy as np

tests/test_hmf.py

@@ -1,4 +1,5 @@
 """Tests of HMF."""
+
 from pytest import raises
 
 import numpy as np

tests/test_integrate_hmf.py

@@ -26,9 +26,7 @@ def anl_int(self, m, loghs, alpha, beta):
         return 10**loghs * gammainc((alpha + 1) / beta, (m / 10**loghs) ** beta)
 
     def anl_m_int(self, m, loghs, alpha, beta):
-        return 10 ** (2 * loghs) * gammainc(
-            (alpha + 2) / beta, (m / 10**loghs) ** beta
-        )
+        return 10 ** (2 * loghs) * gammainc((alpha + 2) / beta, (m / 10**loghs) ** beta)
 
     # def test_basic(self):
     #     m = np.logspace(10,18,500)