Allow default parameter values (#194)

* Allow default values for parameters

* Default alphag to 1

* Draft of the implementation for the organization of Internal and Sampler parameters in updatable objects.

* Updated all Updatable objects to use the new Sampler/Internal parameter classes.

* Added support for lower case only parameters (CosmoSIS requirement) to ParamsMap. Added missing sacc tracer do the SNIa parameters.

* Running black.

* Removed print.

* Update updatable.py

* Fixed line too long

Co-authored-by: Sandro Dias Pinto Vitenti <vitenti@uel.br>
Co-authored-by: Marc Paterno <paterno@fnal.gov>

examples/des_y1_3x2pt/des_y1_3x2pt.py

@@ -14,7 +14,7 @@
 # Sources
 
 
-lai_systematic = wl.LinearAlignmentSystematic(sacc_tracer="")
+lai_systematic = wl.LinearAlignmentSystematic(sacc_tracer="", alphag=None)
 
 """
     Creating sources, each one maps to a specific section of a SACC file. In

examples/srd_sn/sn_srd_values.ini

@@ -21,6 +21,6 @@ w = -1.0
 wa = 0.0
 
 [firecrown_supernova_parameters]
-M=-20 -19.3 -19
+sn_ddf_sample_m=-20 -19.3 -19
 ; need to add in M to the likelihood
 

examples/srd_sn/sn_srd_values_planck_bao.ini

@@ -14,4 +14,4 @@ log1e10As =  2.9   3.0448  3.1
 sigma8_input = 0.801
 
 [firecrown_supernova_parameters]
-M=-20 -19.3 -19
+sn_ddf_sample_m=-20 -19.3 -19

examples/srd_sn/snonly_values.ini

@@ -19,5 +19,5 @@ log1e10As = 3.0448
 sigma8_input = 0.801
 
 [firecrown_supernova_parameters]
-M=-20 -19.3 -19
+sn_ddf_sample_m=-20 -19.3 -19
 

firecrown/connector/cosmosis/likelihood.py

@@ -126,6 +126,7 @@ def calculate_firecrown_params(self, sample: cosmosis.datablock) -> ParamsMap:
             if "firecrown" in section:
                 sec_dict = extract_section(sample, section)
                 firecrown_params = ParamsMap({**firecrown_params, **sec_dict})
+                firecrown_params.use_lower_case_keys(True)
         return firecrown_params
 
 

firecrown/likelihood/gauss_family/gauss_family.py

@@ -116,7 +116,7 @@ def _reset_gaussian_family(self) -> None:
         subclasses."""
 
     @final
-    def required_parameters(self) -> RequiredParameters:
+    def _required_parameters(self) -> RequiredParameters:
         """Return a RequiredParameters object containing the information for
         this Updatable.
 
@@ -125,12 +125,12 @@ def required_parameters(self) -> RequiredParameters:
 
         Derived classes must implement required_parameters_gaussian_family."""
         stats_rp = self.statistics.required_parameters()
-        stats_rp = self.required_parameters_gaussian_family() + stats_rp
+        stats_rp = self._required_parameters_gaussian_family() + stats_rp
 
         return stats_rp
 
     @abstractmethod
-    def required_parameters_gaussian_family(self):
+    def _required_parameters_gaussian_family(self):
         """Required parameters for GaussFamily subclasses."""
 
     @abstractmethod

firecrown/likelihood/gauss_family/gaussian.py

@@ -33,7 +33,7 @@ def _reset_gaussian_family(self):
         pass
 
     @final
-    def required_parameters_gaussian_family(self):
+    def _required_parameters_gaussian_family(self):
         return RequiredParameters([])
 
     @final

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

@@ -13,10 +13,10 @@
 
 from .source import Source
 from .source import Systematic
+from ..... import parameters
 from .....parameters import (
     ParamsMap,
     RequiredParameters,
-    parameter_get_full_name,
     DerivedParameterScalar,
     DerivedParameterCollection,
 )
@@ -63,23 +63,19 @@ class LinearBiasSystematic(NumberCountsSystematic):
 
     """
 
-    params_names = ["alphaz", "alphag", "z_piv"]
-    alphaz: float
-    alphag: float
-    z_piv: float
-
     def __init__(self, sacc_tracer: str):
         super().__init__()
 
+        self.alphaz = parameters.create()
+        self.alphag = parameters.create()
+        self.z_piv = parameters.create()
         self.sacc_tracer = sacc_tracer
 
     @final
     def _update(self, params: ParamsMap):
-        """Read the corresponding named tracer from the given collection of
-        parameters."""
-        self.alphaz = params.get_from_prefix_param(self.sacc_tracer, "alphaz")
-        self.alphag = params.get_from_prefix_param(self.sacc_tracer, "alphag")
-        self.z_piv = params.get_from_prefix_param(self.sacc_tracer, "z_piv")
+        """Perform any updates necessary after the parameters have being updated.
+
+        This implementation has nothing to do."""
 
     @final
     def _reset(self) -> None:
@@ -88,10 +84,8 @@ def _reset(self) -> None:
         This implementation has nothing to do."""
 
     @final
-    def required_parameters(self) -> RequiredParameters:
-        return RequiredParameters(
-            [parameter_get_full_name(self.sacc_tracer, pn) for pn in self.params_names]
-        )
+    def _required_parameters(self) -> RequiredParameters:
+        return RequiredParameters([])
 
     @final
     def _get_derived_parameters(self) -> DerivedParameterCollection:
@@ -130,9 +124,9 @@ class MagnificationBiasSystematic(NumberCountsSystematic):
 
     Parameters
     ----------
-    r_lim : str
+    r_lim : float
         The name of the limiting magnitude in r band filter.
-    sig_c, eta, z_c, z_m : str
+    sig_c, eta, z_c, z_m : float
         The name of the fitting parameters in Joachimi & Bridle (2010) equation
         (C.1).
 
@@ -141,27 +135,22 @@ class MagnificationBiasSystematic(NumberCountsSystematic):
     apply : apply the systematic to a source
     """
 
-    params_names = ["r_lim", "sig_c", "eta", "z_c", "z_m"]
-    r_lim: float
-    sig_c: float
-    eta: float
-    z_c: float
-    z_m: float
-
     def __init__(self, sacc_tracer: str):
         super().__init__()
 
+        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.sacc_tracer = sacc_tracer
 
     @final
     def _update(self, params: ParamsMap):
-        """Read the corresponding named tracer from the given collection of
-        parameters."""
-        self.r_lim = params.get_from_prefix_param(self.sacc_tracer, "r_lim")
-        self.sig_c = params.get_from_prefix_param(self.sacc_tracer, "sig_c")
-        self.eta = params.get_from_prefix_param(self.sacc_tracer, "eta")
-        self.z_c = params.get_from_prefix_param(self.sacc_tracer, "z_c")
-        self.z_m = params.get_from_prefix_param(self.sacc_tracer, "z_m")
+        """Perform any updates necessary after the parameters have being updated.
+
+        This implementation has nothing to do."""
 
     @final
     def _reset(self) -> None:
@@ -170,10 +159,8 @@ def _reset(self) -> None:
         This implementation has nothing to do."""
 
     @final
-    def required_parameters(self) -> RequiredParameters:
-        return RequiredParameters(
-            [parameter_get_full_name(self.sacc_tracer, pn) for pn in self.params_names]
-        )
+    def _required_parameters(self) -> RequiredParameters:
+        return RequiredParameters([])
 
     @final
     def _get_derived_parameters(self) -> DerivedParameterCollection:
@@ -217,17 +204,17 @@ class PhotoZShift(NumberCountsSystematic):
     This systematic shifts the photo-z distribution by some ammount `delta_z`.
     """
 
-    params_names = ["delta_z"]
-    delta_z: float
-
     def __init__(self, sacc_tracer: str):
         super().__init__()
 
+        self.delta_z = parameters.create()
         self.sacc_tracer = sacc_tracer
 
     @final
     def _update(self, params: ParamsMap):
-        self.delta_z = params.get_from_prefix_param(self.sacc_tracer, "delta_z")
+        """Perform any updates necessary after the parameters have being updated.
+
+        This implementation has nothing to do."""
 
     @final
     def _reset(self) -> None:
@@ -236,10 +223,8 @@ def _reset(self) -> None:
         This implementation has nothing to do."""
 
     @final
-    def required_parameters(self) -> RequiredParameters:
-        return RequiredParameters(
-            [parameter_get_full_name(self.sacc_tracer, pn) for pn in self.params_names]
-        )
+    def _required_parameters(self) -> RequiredParameters:
+        return RequiredParameters([])
 
     @final
     def _get_derived_parameters(self) -> DerivedParameterCollection:
@@ -265,10 +250,6 @@ def apply(self, cosmo: pyccl.Cosmology, tracer_arg: NumberCountsArgs):
 class NumberCounts(Source):
     """Source class for number counts."""
 
-    params_names = ["bias", "mag_bias"]
-    bias: float
-    mag_bias: Optional[float]
-
     systematics: UpdatableCollection
     tracer_arg: NumberCountsArgs
 
@@ -286,9 +267,11 @@ def __init__(
 
         self.sacc_tracer = sacc_tracer
         self.has_rsd = has_rsd
-        self.has_mag_bias = has_mag_bias
         self.derived_scale = derived_scale
 
+        self.bias = parameters.create()
+        self.mag_bias = parameters.create(None if has_mag_bias else 0.0)
+
         self.systematics = UpdatableCollection([])
         if systematics:
             for systematic in systematics:
@@ -301,37 +284,18 @@ def __init__(
 
     @final
     def _update_source(self, params: ParamsMap):
-        self.bias = params.get_from_prefix_param(self.sacc_tracer, "bias")
-
-        if self.has_mag_bias:
-            self.mag_bias = params.get_from_prefix_param(self.sacc_tracer, "mag_bias")
-        else:
-            self.mag_bias = None
+        """Perform any updates necessary after the parameters have being updated.
 
+        This implementation must update all contained Updatable instances."""
         self.systematics.update(params)
 
     @final
     def _reset_source(self) -> None:
         self.systematics.reset()
 
     @final
-    def required_parameters(self) -> RequiredParameters:
-        if self.has_mag_bias:
-            rp = RequiredParameters(
-                [
-                    parameter_get_full_name(self.sacc_tracer, pn)
-                    for pn in self.params_names
-                ]
-            )
-        else:
-            rp = RequiredParameters(
-                [
-                    parameter_get_full_name(self.sacc_tracer, pn)
-                    for pn in self.params_names
-                    if pn != "mag_bias"
-                ]
-            )
-        return rp + self.systematics.required_parameters()
+    def _required_parameters(self) -> RequiredParameters:
+        return self.systematics.required_parameters()
 
     @final
     def _get_derived_parameters(self) -> DerivedParameterCollection:
@@ -382,7 +346,7 @@ def create_tracer(self, cosmo: pyccl.Cosmology):
             mag_bias=tracer_args.mag_bias,
         )
 
-        if self.mag_bias is not None:
+        if self.mag_bias != 0.0:
             mag_bias = np.ones_like(tracer_args.z) * self.mag_bias
             tracer_args = NumberCountsArgs(
                 scale=tracer_args.scale,
@@ -395,7 +359,7 @@ def create_tracer(self, cosmo: pyccl.Cosmology):
         for systematic in self.systematics:
             tracer_args = systematic.apply(cosmo, tracer_args)
 
-        if self.has_mag_bias:
+        if self.mag_bias != 0.0:
             tracer = pyccl.NumberCountsTracer(
                 cosmo,
                 has_rsd=self.has_rsd,

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

@@ -27,8 +27,6 @@ class Source(Updatable):
 
     Parameters
     ----------
-    scale : 1.0, optional
-        The default scale for this source.
     systematics : list of str, optional
         A list of the source-level systematics to apply to the source. The
         default of `None` implies no systematics.