Merge branch 'master' into support-m2-mac

firecrown/likelihood/gauss_family/statistic/source/number_counts.py

@@ -85,9 +85,9 @@ def __init__(self, sacc_tracer: str):
         """
         super().__init__(parameter_prefix=sacc_tracer)
 
-        self.alphaz = parameters.create()
-        self.alphag = parameters.create()
-        self.z_piv = parameters.create()
+        self.alphaz = parameters.register_new_updatable_parameter()
+        self.alphag = parameters.register_new_updatable_parameter()
+        self.z_piv = parameters.register_new_updatable_parameter()
 
     def apply(
         self, tools: ModelingTools, tracer_arg: NumberCountsArgs
@@ -143,8 +143,8 @@ def __init__(self, sacc_tracer: str):
         """
         super().__init__(parameter_prefix=sacc_tracer)
 
-        self.b_2 = parameters.create()
-        self.b_s = parameters.create()
+        self.b_2 = parameters.register_new_updatable_parameter()
+        self.b_s = parameters.register_new_updatable_parameter()
 
     def apply(
         self, tools: ModelingTools, tracer_arg: NumberCountsArgs
@@ -186,11 +186,11 @@ def __init__(self, sacc_tracer: str):
         """
         super().__init__(parameter_prefix=sacc_tracer)
 
-        self.r_lim = parameters.create()
-        self.sig_c = parameters.create()
-        self.eta = parameters.create()
-        self.z_c = parameters.create()
-        self.z_m = parameters.create()
+        self.r_lim = parameters.register_new_updatable_parameter()
+        self.sig_c = parameters.register_new_updatable_parameter()
+        self.eta = parameters.register_new_updatable_parameter()
+        self.z_c = parameters.register_new_updatable_parameter()
+        self.z_m = parameters.register_new_updatable_parameter()
 
     def apply(
         self, tools: ModelingTools, tracer_arg: NumberCountsArgs
@@ -245,7 +245,7 @@ def __init__(self, sacc_tracer: str):
         """
         super().__init__(parameter_prefix=sacc_tracer)
 
-        self.mag_bias = parameters.create()
+        self.mag_bias = parameters.register_new_updatable_parameter()
 
     def apply(
         self, tools: ModelingTools, tracer_arg: NumberCountsArgs
@@ -291,7 +291,7 @@ def __init__(
         self.has_rsd = has_rsd
         self.derived_scale = derived_scale
 
-        self.bias = parameters.create()
+        self.bias = parameters.register_new_updatable_parameter()
         self.systematics = UpdatableCollection(systematics)
         self.scale = scale
         self.current_tracer_args: Optional[NumberCountsArgs] = None

firecrown/likelihood/gauss_family/statistic/source/source.py

@@ -217,7 +217,7 @@ def __init__(self, sacc_tracer: str):
         """
         super().__init__(parameter_prefix=sacc_tracer)
 
-        self.delta_z = parameters.create()
+        self.delta_z = parameters.register_new_updatable_parameter()
 
     def apply(self, tools: ModelingTools, tracer_arg: _SourceGalaxyArgsT):
         """Apply a shift to the photo-z distribution of a source."""

firecrown/likelihood/gauss_family/statistic/source/weak_lensing.py

@@ -78,7 +78,7 @@ def __init__(self, sacc_tracer: str) -> None:
         """
         super().__init__(parameter_prefix=sacc_tracer)
 
-        self.mult_bias = parameters.create()
+        self.mult_bias = parameters.register_new_updatable_parameter()
 
     def apply(
         self, tools: ModelingTools, tracer_arg: WeakLensingArgs
@@ -124,10 +124,10 @@ def __init__(self, sacc_tracer: Optional[str] = None, alphag=1.0):
         """
         super().__init__(parameter_prefix=sacc_tracer)
 
-        self.ia_bias = parameters.create()
-        self.alphaz = parameters.create()
-        self.alphag = parameters.create(alphag)
-        self.z_piv = parameters.create()
+        self.ia_bias = parameters.register_new_updatable_parameter()
+        self.alphaz = parameters.register_new_updatable_parameter()
+        self.alphag = parameters.register_new_updatable_parameter(alphag)
+        self.z_piv = parameters.register_new_updatable_parameter()
 
     def apply(
         self, tools: ModelingTools, tracer_arg: WeakLensingArgs
@@ -172,9 +172,9 @@ def __init__(self, sacc_tracer: Optional[str] = None):
             as a prefix for its parameters.
         """
         super().__init__(parameter_prefix=sacc_tracer)
-        self.ia_a_1 = parameters.create()
-        self.ia_a_2 = parameters.create()
-        self.ia_a_d = parameters.create()
+        self.ia_a_1 = parameters.register_new_updatable_parameter()
+        self.ia_a_2 = parameters.register_new_updatable_parameter()
+        self.ia_a_d = parameters.register_new_updatable_parameter()
 
     def apply(
         self, tools: ModelingTools, tracer_arg: WeakLensingArgs

firecrown/likelihood/gauss_family/statistic/statistic.py

@@ -211,7 +211,7 @@ def __init__(self) -> None:
         # Data and theory will both be of length self.count
         self.count = 3
         self.data_vector: Optional[DataVector] = None
-        self.mean = firecrown.parameters.create()
+        self.mean = firecrown.parameters.register_new_updatable_parameter()
         self.computed_theory_vector = False
 
     def read(self, sacc_data: sacc.Sacc):

firecrown/likelihood/gauss_family/statistic/supernova.py

@@ -27,7 +27,7 @@ def __init__(self, sacc_tracer) -> None:
         self.sacc_tracer = sacc_tracer
         self.data_vector: Optional[DataVector] = None
         self.a: Optional[npt.NDArray[np.float64]] = None
-        self.M = parameters.create()
+        self.M = parameters.register_new_updatable_parameter()
 
     def read(self, sacc_data: sacc.Sacc):
         """Read the data for this statistic from the SACC file."""

firecrown/likelihood/gauss_family/student_t.py

@@ -31,7 +31,7 @@ def __init__(
         nu: Optional[float],
     ):
         super().__init__(statistics)
-        self.nu = parameters.create(nu)
+        self.nu = parameters.register_new_updatable_parameter(nu)
 
     def compute_loglike(self, tools: ModelingTools):
         """Compute the log-likelihood.

firecrown/models/cluster_mass_rich_proxy.py

@@ -43,12 +43,12 @@ def __init__(
         self.logMu = logMu
 
         # Updatable parameters
-        self.mu_p0 = parameters.create()
-        self.mu_p1 = parameters.create()
-        self.mu_p2 = parameters.create()
-        self.sigma_p0 = parameters.create()
-        self.sigma_p1 = parameters.create()
-        self.sigma_p2 = parameters.create()
+        self.mu_p0 = parameters.register_new_updatable_parameter()
+        self.mu_p1 = parameters.register_new_updatable_parameter()
+        self.mu_p2 = parameters.register_new_updatable_parameter()
+        self.sigma_p0 = parameters.register_new_updatable_parameter()
+        self.sigma_p1 = parameters.register_new_updatable_parameter()
+        self.sigma_p2 = parameters.register_new_updatable_parameter()
 
         self.logM_obs_min = 0.0
         self.logM_obs_max = np.inf

firecrown/parameters.py

@@ -4,6 +4,7 @@
 
 from __future__ import annotations
 from typing import Iterable, List, Dict, Set, Tuple, Optional, Iterator, Sequence
+import warnings
 from abc import ABC, abstractmethod
 
 
@@ -304,6 +305,20 @@ def get_value(self) -> float:
 def create(value: Optional[float] = None):
     """Create a new parameter, either a SamplerParameter or an InternalParameter.
 
+    See register_new_updatable_parameter for details."""
+    warnings.simplefilter("always", DeprecationWarning)
+    warnings.warn(
+        "This function is named `create` and will be removed in a future version "
+        "due to its name being too generic."
+        "Use `register_new_updatable_parameter` instead.",
+        category=DeprecationWarning,
+    )
+    return register_new_updatable_parameter(value)
+
+
+def register_new_updatable_parameter(value: Optional[float] = None):
+    """Create a new parameter, either a SamplerParameter or an InternalParameter.
+
     If `value` is `None`, the result will be a `SamplerParameter`; Firecrown
     will expect this value to be supplied by the sampling framwork. If `value`
     is a `float` quantity, then Firecrown will expect this parameter to *not*

tests/likelihood/lkdir/lkmodule.py

@@ -57,7 +57,7 @@ def __init__(self, params: NamedParameters):
         parameter_prefix value and creates a sampler parameter called "sampler_param0".
         """
         super().__init__(parameter_prefix=params.get_string("parameter_prefix"))
-        self.sampler_param0 = parameters.create()
+        self.sampler_param0 = parameters.register_new_updatable_parameter()
 
     def read(self, sacc_data: sacc.Sacc) -> None:
         """This class has nothing to read."""

tests/test_parameters.py

@@ -7,6 +7,7 @@
 from firecrown.parameters import (
     DerivedParameterScalar,
     DerivedParameterCollection,
+    register_new_updatable_parameter,
     create,
     InternalParameter,
     SamplerParameter,
@@ -16,23 +17,40 @@
 def test_create_with_no_arg():
     """Calling parameters.create() with no argument should return an
     SamplerParameter"""
-    a_parameter = create()
-    assert isinstance(a_parameter, SamplerParameter)
+    with pytest.deprecated_call():
+        a_parameter = create()
+        assert isinstance(a_parameter, SamplerParameter)
 
 
 def test_create_with_float_arg():
     """Calling parameters.create() with a float argument should return a
     InternalParameter ."""
-    a_parameter = create(1.5)
+    with pytest.deprecated_call():
+        a_parameter = create(1.5)
+        assert isinstance(a_parameter, InternalParameter)
+        assert a_parameter.value == 1.5
+
+
+def test_register_new_updatable_parameter_with_no_arg():
+    """Calling parameters.create() with no argument should return an
+    SamplerParameter"""
+    a_parameter = register_new_updatable_parameter()
+    assert isinstance(a_parameter, SamplerParameter)
+
+
+def test_register_new_updatable_parameter_with_float_arg():
+    """Calling parameters.create() with a float argument should return a
+    InternalParameter ."""
+    a_parameter = register_new_updatable_parameter(1.5)
     assert isinstance(a_parameter, InternalParameter)
     assert a_parameter.value == 1.5
 
 
-def test_create_with_wrong_arg():
+def test_register_new_updatable_parameter_with_wrong_arg():
     """Calling parameters.create() with an org that is neither float nor None should
     raise a TypeError."""
     with pytest.raises(TypeError):
-        _ = create("cow")  # type: ignore
+        _ = register_new_updatable_parameter("cow")  # type: ignore
 
 
 def test_required_parameters_length():

tests/test_updatable.py

@@ -22,7 +22,7 @@ def __init__(self):
         """Initialize object with defaulted value."""
         super().__init__()
 
-        self.a = parameters.create()
+        self.a = parameters.register_new_updatable_parameter()
 
 
 class SimpleUpdatable(Updatable):
@@ -32,8 +32,8 @@ def __init__(self):
         """Initialize object with defaulted values."""
         super().__init__()
 
-        self.x = parameters.create()
-        self.y = parameters.create()
+        self.x = parameters.register_new_updatable_parameter()
+        self.y = parameters.register_new_updatable_parameter()
 
 
 class UpdatableWithDerived(Updatable):
@@ -43,8 +43,8 @@ def __init__(self):
         """Initialize object with defaulted values."""
         super().__init__()
 
-        self.A = parameters.create()
-        self.B = parameters.create()
+        self.A = parameters.register_new_updatable_parameter()
+        self.B = parameters.register_new_updatable_parameter()
 
     def _get_derived_parameters(self) -> DerivedParameterCollection:
         derived_scale = DerivedParameterScalar("Section", "Name", self.A + self.B)
@@ -132,7 +132,9 @@ def test_updatable_collection_insertion():
 
 def test_set_sampler_parameter():
     my_updatable = MinimalUpdatable()
-    my_updatable.set_sampler_parameter("the_meaning_of_life", parameters.create())
+    my_updatable.set_sampler_parameter(
+        "the_meaning_of_life", parameters.register_new_updatable_parameter()
+    )
 
     assert hasattr(my_updatable, "the_meaning_of_life")
     assert my_updatable.the_meaning_of_life is None
@@ -143,21 +145,27 @@ def test_set_sampler_parameter_rejects_internal_parameter():
 
     with pytest.raises(TypeError):
         my_updatable.set_sampler_parameter(
-            "the_meaning_of_life", parameters.create(42.0)
+            "the_meaning_of_life", parameters.register_new_updatable_parameter(42.0)
         )
 
 
 def test_set_sampler_parameter_rejects_duplicates():
     my_updatable = MinimalUpdatable()
-    my_updatable.set_sampler_parameter("the_meaning_of_life", parameters.create())
+    my_updatable.set_sampler_parameter(
+        "the_meaning_of_life", parameters.register_new_updatable_parameter()
+    )
 
     with pytest.raises(ValueError):
-        my_updatable.set_sampler_parameter("the_meaning_of_life", parameters.create())
+        my_updatable.set_sampler_parameter(
+            "the_meaning_of_life", parameters.register_new_updatable_parameter()
+        )
 
 
 def test_set_internal_parameter():
     my_updatable = MinimalUpdatable()
-    my_updatable.set_internal_parameter("the_meaning_of_life", parameters.create(42.0))
+    my_updatable.set_internal_parameter(
+        "the_meaning_of_life", parameters.register_new_updatable_parameter(42.0)
+    )
 
     assert hasattr(my_updatable, "the_meaning_of_life")
     assert my_updatable.the_meaning_of_life == 42.0
@@ -166,27 +174,33 @@ def test_set_internal_parameter():
 def test_set_internal_parameter_rejects_sampler_parameter():
     my_updatable = MinimalUpdatable()
     with pytest.raises(TypeError):
-        my_updatable.set_internal_parameter("sampler_param", parameters.create())
+        my_updatable.set_internal_parameter(
+            "sampler_param", parameters.register_new_updatable_parameter()
+        )
 
 
 def test_set_internal_parameter_rejects_duplicates():
     my_updatable = MinimalUpdatable()
-    my_updatable.set_internal_parameter("the_meaning_of_life", parameters.create(42.0))
+    my_updatable.set_internal_parameter(
+        "the_meaning_of_life", parameters.register_new_updatable_parameter(42.0)
+    )
 
     with pytest.raises(ValueError):
         my_updatable.set_internal_parameter(
-            "the_meaning_of_life", parameters.create(42.0)
+            "the_meaning_of_life", parameters.register_new_updatable_parameter(42.0)
         )
 
     with pytest.raises(ValueError):
         my_updatable.set_internal_parameter(
-            "the_meaning_of_life", parameters.create(41.0)
+            "the_meaning_of_life", parameters.register_new_updatable_parameter(41.0)
         )
 
 
 def test_update_rejects_internal_parameters():
     my_updatable = MinimalUpdatable()
-    my_updatable.set_internal_parameter("the_meaning_of_life", parameters.create(42.0))
+    my_updatable.set_internal_parameter(
+        "the_meaning_of_life", parameters.register_new_updatable_parameter(42.0)
+    )
     assert hasattr(my_updatable, "the_meaning_of_life")
 
     params = ParamsMap({"a": 1.1, "the_meaning_of_life": 34.0})