initial commit of bias theory class

soliket/bias.py

@@ -0,0 +1,56 @@
+r"""Class to calculate bias models for haloes and galaxies as cobaya Theory classes
+
+"""
+
+import numpy as np
+from typing import Sequence, Union
+from cobaya.theory import Theory
+
+class Bias(Theory):
+
+    def initialize(self):
+        kmax: float = 0  # Maximum k (1/Mpc units) for Pk, or zero if not needed
+        nonlinear: bool = False  # whether to get non-linear Pk from CAMB/Class
+        z: Union[Sequence, np.ndarray] = []  # redshift sampling
+
+    # def get_requirements(self):
+
+    def must_provide(self, **requirements):
+
+        self.kmax = max(self.kmax, options.get('kmax', self.kmax))
+        self.z = np.unique(np.concatenate(
+                            (np.atleast_1d(options.get("z", self._default_z_sampling)),
+                            np.atleast_1d(self.z))))
+
+        # Dictionary of the things needed from CAMB/CLASS
+        needs = {}
+
+        needs['Pk_grid'] = {
+                'vars_pairs': self._var_pairs or [('delta_tot', 'delta_tot')],
+                'nonlinear': (True, False) if self.nonlinear else False,
+                'z': self.z,
+                'k_max': self.kmax
+            }
+
+        return needs
+
+    # def calculate(self, state, want_derived=True, **params_values_dict):
+
+    # def get_Pkgg(self):
+
+    # def get_Pkgm(self):
+
+class Linear_bias(Bias):
+
+    params = {'b_lin' : None}
+
+    def calculate(self, state, want_derived=True, **params_values_dict):
+
+        state['Pk_gg'] = self.b_lin * self.b_lin * Pk_grid
+        state['Pk_gm'] = self.b_lin * Pk_grid
+
+    def get_Pkgg(self):
+        return self._current_state['Pk_gg']
+
+    def get_Pkgm(self):
+        return self._current_state['Pk_gm']

soliket/tests/test_bias.py

@@ -0,0 +1,29 @@
+# pytest -k bias -v .
+
+import pytest
+import numpy as np
+
+from cobaya.model import get_model
+
+def test_bias_import():
+    from soliket.bias import Bias
+
+def test_linear_bias_import():
+    from soliket.bias import Linear_bias
+
+def test_linear_bias():
+
+    from soliket.bias import Linear_bias
+
+    info = {"params": {"b_lin": 1.,
+                       "ombh2": 0.0245,
+                       "omch2": 0.1225,
+                       "tau": 0.05},
+            "likelihood": {"one" : None},
+            "theory": {#"camb" : None,
+                       "linear_bias": {"external": Linear_bias}
+                       },
+            "sampler": {"evaluate": None}
+           }
+
+    model = get_model(info)