Test PR only to better view the changes

cupix/likelihood/fitter.py

@@ -10,7 +10,6 @@
 
 # our own modules
 import cupix, lace
-from lace.cosmo import camb_cosmo
 from cupix.utils.utils import create_print_function, purge_chains
 
 

cupix/likelihood/forestflow_emu.py

@@ -14,7 +14,6 @@ class FF_emulator():
     def __init__(
             self,
             z,
-            cosmo_param_dict,
             Nrealizations=3000
         ):
 
@@ -27,7 +26,6 @@ def __init__(
             "kF_Mpc"
         ]
         self.z = z
-        self.cosmo_param_dict = cosmo_param_dict 
         self.emulator_label = "forestflow_emu"
         # self.kp_Mpc = kp_Mpc
         # self.kmax_Mpc = 5 # from Forestflow paper plots, could revisit
@@ -103,4 +101,4 @@ def emulate_P3D_params(self, emu_call, zs):
                 arinyo_coeffs[key] = emu_call[key]
 
         return arinyo_coeffs
-
+

cupix/likelihood/likelihood.py

@@ -7,8 +7,6 @@
 from scipy.optimize import minimize
 from scipy.linalg import block_diag
 from cupix.likelihood.window_and_rebin import convolve_window, rebin_theta
-import lace
-from lace.cosmo import camb_cosmo
 from cupix.utils.utils import is_number_string
 from cupix.likelihood.likelihood_parameter import LikelihoodParameter, likeparam_from_dict
 import warnings

cupix/likelihood/likelihood_parameter.py

@@ -83,6 +83,8 @@ def get_new_parameter(self, value_in_cube):
 
 def likeparam_from_dict(params_dict):
     # takes a dictionary of parameter names and values, and returns a list of LikelihoodParameter objects
+    if params_dict is None:
+        return []
     like_params = []
     for name, value in params_dict.items():
         like_params.append(LikelihoodParameter(name=name, min_value=-1000, max_value=1000, value=value))
@@ -91,6 +93,8 @@ def likeparam_from_dict(params_dict):
 
 def dict_from_likeparam(like_params):
     # takes a list of LikelihoodParameter objects, and returns a dictionary of parameter names and values
+    if like_params is None:
+        return {}
     params_dict = {}
     for param in like_params:
         params_dict[param.name] = param.value
@@ -120,4 +124,4 @@ def par_index(like_param_list, par_name):
     for i, param in enumerate(like_param_list):
         if param.name == par_name:
             return i
-    raise ValueError("Parameter with name " + par_name + " not found in list of LikelihoodParameter objects.")
+    raise ValueError("Parameter with name " + par_name + " not found in list of LikelihoodParameter objects.")