remove archive from gp emulator (no longer needed)

lace/cosmo/camb_cosmo.py

@@ -15,18 +15,21 @@
 
 
 def get_cosmology(
-    H0=67.0,
+    H0=67.66,
     mnu=0.0,
-    omch2=0.12,
-    ombh2=0.022,
+    omch2=0.119,
+    ombh2=0.0224,
     omk=0.0,
-    As=2.1e-09,
-    ns=0.965,
+    As=2.105e-09,
+    ns=0.9665,
     nrun=0.0,
     pivot_scalar=0.05,
     w=-1,
 ):
-    """Given set of cosmological parameters, return CAMB cosmology object."""
+    """Given set of cosmological parameters, return CAMB cosmology object.
+
+    Fiducial values for Planck 2018
+    """
 
     pars = camb.CAMBparams()
     # set background cosmology

lace/emulator/gp_emulator.py

@@ -93,15 +93,17 @@ def __init__(
                 )
 
             # read Gadget archive with the right postprocessing
-            self.archive = gadget_archive.GadgetArchive(postproc=training_set)
+            archive = gadget_archive.GadgetArchive(postproc=training_set)
 
-        elif archive != None and training_set == None:
+        elif (archive is not None) and (training_set is None):
             print("Use custom archive provided by the user")
-            self.archive = archive
+            pass
 
-        elif (archive == None) & (training_set == None):
+        elif (archive is None) & (training_set is None):
             raise (ValueError("Archive or training_set must be provided"))
-        self.kp_Mpc = self.archive.kp_Mpc
+
+        self.list_sim_cube = archive.list_sim_cube
+        self.kp_Mpc = archive.kp_Mpc
 
         emulator_label_all = [
             "Pedersen21",
@@ -277,13 +279,13 @@ def __init__(
         # GPs should probably avoid rescalings (low performance with large N)
         average = "both"
         val_scaling = 1
-        if self.archive.training_average != "both":
+        if archive.training_average != "both":
             warn("Enforce average=both in training of GP emulator")
-        if self.archive.training_val_scaling != 1:
+        if archive.training_val_scaling != 1:
             warn("Enforce val_scalinge=1 in training of GP emulator")
 
         # keep track of training data to be used in emulator
-        self.training_data = self.archive.get_training_data(
+        self.training_data = archive.get_training_data(
             emu_params=self.emu_params,
             drop_sim=self.drop_sim,
             average=average,