Implement separate __eq__ methods (#1033)

* first commit

* remove warning in the first spin of CCL

* kernels chk ok, transfers almost done

* more tests

* finished tracer eq tests

* coverage for _repr.py

* more coverage

* more coverage

* super comprehensive tests & full coverage

* add a final extra test

* comments

* more efficient

* reinstate True if all checks pass

* use np.any for array comparison

* remove cm from FoF masses

* zero tolerance for array eq checking

* array_equal

* stray cM

* direct type comparison instead of hook

* comments

* fallback to id-checking

README.md

@@ -72,7 +72,7 @@ cosmo = ccl.Cosmology(
     transfer_function='bbks')
 
 # Define a simple binned galaxy number density curve as a function of redshift
-z_n = np.linspace(0., 1., 200)
+z_n = np.linspace(0., 1., 500)
 n = np.ones(z_n.shape)
 
 # Create objects to represent tracers of the weak lensing signal with this

pyccl/base.py

@@ -440,6 +440,15 @@ def Funlock(cls, cl, name, mutate: bool):
 unlock_instance = UnlockInstance.unlock_instance
 
 
+def is_equal(this, other):
+    """Powerful helper for equivalence checking."""
+    try:
+        np.testing.assert_equal(this, other)
+        return True
+    except AssertionError:
+        return False
+
+
 class FancyRepr:
     """Controls the usage of fancy ``__repr__` for ``CCLObjects."""
     _enabled: bool = True
@@ -590,9 +599,16 @@ def __hash__(self):
 
     def __eq__(self, other):
         # Two same-type objects are equal if their representations are equal.
-        if self.__class__ is not other.__class__:
+        if type(self) is not type(other):
             return False
-        return repr(self) == repr(other)
+        # Compare the attributes listed in `__eq_attrs__`.
+        if hasattr(self, "__eq_attrs__"):
+            for attr in self.__eq_attrs__:
+                if not is_equal(getattr(self, attr), getattr(other, attr)):
+                    return False
+            return True
+        # Fall back to default Python comparison.
+        return id(self) == id(other)
 
 
 class CCLHalosObject(CCLObject):

pyccl/core.py

@@ -67,6 +67,36 @@
 }
 
 
+def _methods_of_cosmology(cls=None, *, modules=[]):
+    """Assign all functions in ``modules`` which take ``cosmo`` as their
+    first argument as methods of the class ``cls``.
+    """
+    import functools
+    from importlib import import_module
+
+    if cls is None:
+        # called with parentheses
+        return functools.partial(_methods_of_cosmology, modules=modules)
+
+    pkg = __name__.rsplit(".")[0]
+    modules = [import_module(f".{module}", pkg) for module in modules]
+    funcs = [getmembers(module, isfunction) for module in modules]
+    funcs = [func for sublist in funcs for func in sublist]
+
+    for name, func in funcs:
+        pars = signature(func).parameters
+        if pars and list(pars)[0] == "cosmo":
+            setattr(cls, name, func)
+
+    return cls
+
+
+_modules = ["background", "bcm", "boltzmann", "cls", "correlations",
+            "covariances", "neutrinos", "pk2d", "power", "pyutils",
+            "tk3d", "tracers", "halos", "nl_pt"]
+
+
+@_methods_of_cosmology(modules=_modules)
 class Cosmology(CCLObject):
     """A cosmology including parameters and associated data.
 
@@ -198,25 +228,8 @@ class Cosmology(CCLObject):
 
     """
     from ._repr import _build_string_Cosmology as __repr__
-
-    # Go through all functions in the main package and the subpackages
-    # and make every function that takes `cosmo` as its first argument
-    # an attribute of this class.
-    from . import (background, bcm, boltzmann, cls,
-                   correlations, covariances, neutrinos,
-                   pk2d, power, pyutils, tk3d, tracers, halos, nl_pt)
-    subs = [background, boltzmann, bcm, cls, correlations, covariances,
-            neutrinos, pk2d, power, pyutils, tk3d, tracers, halos, nl_pt]
-    funcs = [getmembers(sub, isfunction) for sub in subs]
-    funcs = [func for sub in funcs for func in sub]
-    for name, func in funcs:
-        pars = list(signature(func).parameters)
-        if pars and pars[0] == "cosmo":
-            vars()[name] = func
-    # clear unnecessary locals
-    del (background, boltzmann, bcm, cls, correlations, covariances,
-         neutrinos, pk2d, power, pyutils, tk3d, tracers, halos, nl_pt,
-         subs, funcs, func, name, pars)
+    __eq_attrs__ = ("_params_init_kwargs", "_config_init_kwargs",
+                    "_accuracy_params",)
 
     def __init__(
             self, Omega_c=None, Omega_b=None, h=None, n_s=None,
@@ -1167,6 +1180,9 @@ class CosmologyCalculator(Cosmology):
             corresponding to the "HALOFIT" transformation of
             Takahashi et al. 2012 (arXiv:1208.2701).
     """
+    __eq_attrs__ = ("_params_init_kwargs", "_config_init_kwargs",
+                    "_accuracy_params", "_input_arrays",)
+
     def __init__(
             self, Omega_c=None, Omega_b=None, h=None, n_s=None,
             sigma8=None, A_s=None, Omega_k=0., Omega_g=None,
@@ -1199,6 +1215,9 @@ def __init__(
         has_pknl = pk_nonlin is not None
         has_nonlin_model = nonlinear_model is not None
 
+        self._input_arrays = {"background": background, "growth": growth,
+                              "pk_linear": pk_linear, "pk_nonlin": pk_nonlin,
+                              "nonlinear_model": nonlinear_model}
         if has_bg:
             self._init_bg(background)
         if has_dz:

pyccl/halos/concentration.py

@@ -18,7 +18,7 @@ class Concentration(CCLHalosObject):
             object that fixes the mass definition used by this c(M)
             parametrization.
     """
-    __repr_attrs__ = ("mdef",)
+    __repr_attrs__ = __eq_attrs__ = ("mdef",)
 
     def __init__(self, mass_def=None):
         if mass_def is not None:
@@ -395,7 +395,7 @@ class ConcentrationIshiyama21(Concentration):
             method. Otherwise, use the concentration found with profile
             fitting. The default is False.
     """
-    __repr_attrs__ = ("mdef", "relaxed", "Vmax",)
+    __repr_attrs__ = __eq_attrs__ = ("mdef", "relaxed", "Vmax",)
     name = 'Ishiyama21'
 
     def __init__(self, mdef=None, relaxed=False, Vmax=False):
@@ -555,7 +555,7 @@ class ConcentrationConstant(Concentration):
             the mass definition used by this c(M)
             parametrization. In this case it's arbitrary.
     """
-    __repr_attrs__ = ("mdef", "c",)
+    __repr_attrs__ = __eq_attrs__ = ("mdef", "c",)
     name = 'Constant'
 
     def __init__(self, c=1, mdef=None):

pyccl/halos/halo_model.py

@@ -53,7 +53,7 @@ class HMCalculator(CCLHalosObject):
             determines what is considered a "very large" scale.
             Default: 1E-5.
     """
-    __repr_attrs__ = ("_massfunc", "_hbias", "_mdef", "_prec",)
+    __repr_attrs__ = __eq_attrs__ = ("_massfunc", "_hbias", "_mdef", "_prec",)
 
     def __init__(self, cosmo, massfunc, hbias, mass_def,
                  log10M_min=8., log10M_max=16.,

pyccl/halos/hbias.py

@@ -27,7 +27,7 @@ class HaloBias(CCLHalosObject):
         mass_def_strict (bool): if False, consistency of the mass
             definition will be ignored.
     """
-    __repr_attrs__ = ("mdef", "mass_def_strict",)
+    __repr_attrs__ = __eq_attrs__ = ("mdef", "mass_def_strict",)
 
     def __init__(self, cosmo, mass_def=None, mass_def_strict=True):
         cosmo.compute_sigma()
@@ -190,7 +190,8 @@ class HaloBiasSheth99(HaloBias):
             the fit of Nakamura & Suto 1997. Otherwise use
             delta_crit = 1.68647.
     """
-    __repr_attrs__ = ("mdef", "mass_def_strict", "use_delta_c_fit",)
+    __repr_attrs__ = __eq_attrs__ = ("mdef", "mass_def_strict",
+                                     "use_delta_c_fit",)
     name = "Sheth99"
 
     def __init__(self, cosmo, mass_def=None,

pyccl/halos/hmfunc.py

@@ -32,7 +32,7 @@ class MassFunc(CCLHalosObject):
         mass_def_strict (bool): if False, consistency of the mass
             definition will be ignored.
     """
-    __repr_attrs__ = ("mdef", "mass_def_strict",)
+    __repr_attrs__ = __eq_attrs__ = ("mdef", "mass_def_strict",)
 
     def __init__(self, cosmo, mass_def=None, mass_def_strict=True):
         # Initialize sigma(M) splines if needed
@@ -251,7 +251,8 @@ class MassFuncSheth99(MassFunc):
             the fit of Nakamura & Suto 1997. Otherwise use
             delta_crit = 1.68647.
     """
-    __repr_attrs__ = ("mdef", "mass_def_strict", "use_delta_c_fit",)
+    __repr_attrs__ = __eq_attrs__ = ("mdef", "mass_def_strict",
+                                     "use_delta_c_fit",)
     name = 'Sheth99'
 
     def __init__(self, cosmo, mass_def=None, mass_def_strict=True,
@@ -393,7 +394,7 @@ class MassFuncDespali16(MassFunc):
         mass_def_strict (bool): if False, consistency of the mass
             definition will be ignored.
     """
-    __repr_attrs__ = ("mdef", "mass_def_strict", "ellipsoidal",)
+    __repr_attrs__ = __eq_attrs__ = ("mdef", "mass_def_strict", "ellipsoidal",)
     name = 'Despali16'
 
     def __init__(self, cosmo, mass_def=None, mass_def_strict=True,
@@ -456,7 +457,7 @@ class MassFuncTinker10(MassFunc):
         norm_all_z (bool): should we normalize the mass function
             at z=0 or at all z?
     """
-    __repr_attrs__ = ("mdef", "mass_def_strict", "norm_all_z",)
+    __repr_attrs__ = __eq_attrs__ = ("mdef", "mass_def_strict", "norm_all_z",)
     name = 'Tinker10'
 
     def __init__(self, cosmo, mass_def=None, mass_def_strict=True,
@@ -539,7 +540,7 @@ class MassFuncBocquet16(MassFunc):
             using dark-matter-only simulations. Otherwise, include
             baryonic effects (default).
     """
-    __repr_attrs__ = ("mdef", "mass_def_strict", "hydro",)
+    __repr_attrs__ = __eq_attrs__ = ("mdef", "mass_def_strict", "hydro",)
     name = 'Bocquet16'
 
     def __init__(self, cosmo, mass_def=None, mass_def_strict=True,

pyccl/halos/massdef.py

@@ -3,6 +3,7 @@
 from ..background import species_types, rho_x, omega_x
 from ..base import CCLHalosObject
 import numpy as np
+from functools import cached_property
 
 
 def mass2radius_lagrangian(cosmo, M):
@@ -84,7 +85,7 @@ class MassDef(CCLHalosObject):
             If `None`, no c(M) relation will be attached to this mass
             definition (and hence one can't translate into other definitions).
     """
-    __repr_attrs__ = ("name",)
+    __repr_attrs__ = __eq_attrs__ = ("name",)
 
     def __init__(self, Delta, rho_type, c_m_relation=None):
         # Check it makes sense
@@ -106,7 +107,7 @@ def __init__(self, Delta, rho_type, c_m_relation=None):
         else:
             self._concentration_init(c_m_relation)
 
-    @property
+    @cached_property
     def name(self):
         """Give a name to this mass definition."""
         if isinstance(self.Delta, (int, float)):
@@ -286,3 +287,12 @@ def MassDefVir(c_m='Klypin11'):
         c_m (string): concentration-mass relation.
     """
     return MassDef('vir', 'critical', c_m_relation=c_m)
+
+
+def MassDefFof():
+    r""":math:`\Delta = \rm FoF` mass definition.
+
+    Args:
+        c_m (string): concentration-mass relation.
+    """
+    return MassDef('fof', 'matter')

pyccl/halos/profiles.py

@@ -53,10 +53,6 @@ def __init__(self):
                                  'plaw_fourier': -1.5,
                                  'plaw_projected': -1.}
 
-    __eq__ = object.__eq__
-
-    __hash__ = object.__hash__  # TODO: remove once __eq__ is replaced.
-
     @unlock_instance(mutate=True)
     def update_precision_fftlog(self, **kwargs):
         """ Update any of the precision parameters used by
@@ -535,7 +531,7 @@ class HaloProfileGaussian(HaloProfile):
         rho0 (:obj:`function`): the amplitude of the profile.
             It should have the same signature as `r_scale`.
     """
-    __repr_attrs__ = ("r_s", "rho_0", "precision_fftlog",)
+    __repr_attrs__ = __eq_attrs__ = ("r_s", "rho_0", "precision_fftlog",)
     name = 'Gaussian'
 
     def __init__(self, r_scale, rho0):
@@ -582,7 +578,7 @@ class HaloProfilePowerLaw(HaloProfile):
             profile. The signature of this function should
             be `f(cosmo, a)`.
     """
-    __repr_attrs__ = ("r_s", "tilt", "precision_fftlog",)
+    __repr_attrs__ = __eq_attrs__ = ("r_s", "tilt", "precision_fftlog",)
     name = 'PowerLaw'
 
     def __init__(self, r_scale, tilt):
@@ -654,8 +650,9 @@ class HaloProfileNFW(HaloProfile):
             truncated at :math:`r = R_\\Delta` (i.e. zero at larger
             radii.
     """
-    __repr_attrs__ = ("cM", "fourier_analytic", "projected_analytic",
-                      "cumul2d_analytic", "truncated", "precision_fftlog",)
+    __repr_attrs__ = __eq_attrs__ = (
+        "fourier_analytic", "projected_analytic",
+        "cumul2d_analytic", "truncated", "cM", "precision_fftlog",)
     name = 'NFW'
 
     def __init__(self, c_M_relation,
@@ -851,7 +848,8 @@ class HaloProfileEinasto(HaloProfile):
         alpha (float, 'cosmo'): Set the Einasto alpha parameter or set to
             'cosmo' to calculate the value from cosmology. Default: 'cosmo'
     """
-    __repr_attrs__ = ("cM", "truncated", "alpha", "precision_fftlog",)
+    __repr_attrs__ = __eq_attrs__ = ("truncated", "alpha",
+                                     "cM", "precision_fftlog",)
     name = 'Einasto'
 
     def __init__(self, c_M_relation, truncated=True, alpha='cosmo'):
@@ -961,8 +959,9 @@ class HaloProfileHernquist(HaloProfile):
             truncated at :math:`r = R_\\Delta` (i.e. zero at larger
             radii.
     """
-    __repr_attrs__ = ("cM", "fourier_analytic", "projected_analytic",
-                      "cumul2d_analytic", "truncated", "precision_fftlog",)
+    __repr_attrs__ = __eq_attrs__ = (
+        "fourier_analytic", "projected_analytic", "cumul2d_analytic",
+        "truncated", "cM", "precision_fftlog",)
     name = 'Hernquist'
 
     def __init__(self, c_M_relation,
@@ -1193,9 +1192,9 @@ class HaloProfilePressureGNFW(HaloProfile):
         Profile threshold, in units of :math:`R_{\\mathrm{500c}}`.
         Defaults to :math:`+\\infty`.
     """
-    __repr_attrs__ = ("mass_bias", "P0", "c500", "alpha", "alpha_P", "beta",
-                      "gamma", "P0_hexp", "qrange", "nq", "x_out",
-                      "precision_fftlog",)
+    __repr_attrs__ = __eq_attrs__ = (
+        "mass_bias", "P0", "c500", "alpha", "alpha_P", "beta", "gamma",
+        "P0_hexp", "qrange", "nq", "x_out", "precision_fftlog",)
     name = 'GNFW'
 
     def __init__(self, mass_bias=0.8, P0=6.41,
@@ -1472,10 +1471,11 @@ class HaloProfileHOD(HaloProfile):
         ns_independent (bool): drop requirement to only form
             satellites when centrals are present.
     """
-    __repr_attrs__ = ("cM", "lMmin_0", "lMmin_p", "siglM_0", "siglM_p",
-                      "lM0_0", "lM0_p", "lM1_0", "lM1_p", "alpha_0", "alpha_p",
-                      "fc_0", "fc_p", "bg_0", "bg_p", "bmax_0", "bmax_p",
-                      "a_pivot", "ns_independent", "precision_fftlog",)
+    __repr_attrs__ = __eq_attrs__ = (
+        "lMmin_0", "lMmin_p", "siglM_0", "siglM_p", "lM0_0", "lM0_p", "lM1_0",
+        "lM1_p", "alpha_0", "alpha_p", "fc_0", "fc_p", "bg_0", "bg_p",
+        "bmax_0", "bmax_p", "a_pivot", "ns_independent",
+        "cM", "precision_fftlog",)
     name = 'HOD'
     is_number_counts = True
 

pyccl/halos/profiles_2pt.py

@@ -23,15 +23,11 @@ class Profile2pt(CCLHalosObject):
             Defaults to ``r_corr=0``, returning simply the product
             of the fourier profiles.
     """
-    __repr_attrs__ = ("r_corr",)
+    __repr_attrs__ = __eq_attrs__ = ("r_corr",)
 
     def __init__(self, r_corr=0.):
         self.r_corr = r_corr
 
-    __eq__ = object.__eq__
-
-    __hash__ = object.__hash__  # TODO: remove once __eq__ is replaced.
-
     def update_parameters(self, r_corr=None):
         """ Update any of the parameters associated with this 1-halo
         2-point correlator. Any parameter set to `None` won't be updated.

pyccl/halos/profiles_cib.py

@@ -77,8 +77,9 @@ class HaloProfileCIBShang12(HaloProfile):
         L0 (float): luminosity scale (in
             :math:`{\\rm Jy}\\,{\\rm Mpc}^2\\,M_\\odot^{-1}`).
     """
-    __repr_attrs__ = ("cM", "nu", "alpha", "T0", "beta", "gamma", "s_z",
-                      "l10meff", "sigLM", "Mmin", "L0", "precision_fftlog",)
+    __repr_attrs__ = __eq_attrs__ = (
+        "nu", "alpha", "T0", "beta", "gamma", "s_z",
+        "l10meff", "sigLM", "Mmin", "L0", "cM", "precision_fftlog",)
     name = 'CIBShang12'
     _one_over_4pi = 0.07957747154