Update aa_synthesis_sensitivity variant for rev kcat parameter (#1211)

* Include rev kcat parameter and update FACTORS in aa_synthesis_sensitivity variant
* Better check for if a variant needs to be run

models/ecoli/sim/variants/aa_synthesis_sensitivity.py

@@ -10,11 +10,16 @@
 	sim_data.process.metabolism.aa_reverse_kms
 	sim_data.process.metabolism.aa_degradation_kms
 
-Expected variant indices (dependent on length of FACTORS and sim_data.molecule_groups.amino_acids):
-	0-6: range of values for first parameter, first amino acid, first media condition
-	0-34: range of parameters and values for first amino acid, first media condition
-	0-734: range of parameters and values over all amino acids for first media condition
-	0-1469: all changes
+Expected variant indices (dependent on length of FACTORS, PARAMETERS,
+sim_data.molecule_groups.amino_acids and MEDIA_IDS as noted below each group):
+	0-5: range of values for first parameter, first amino acid, first media condition
+		# FACTORS
+	0-35: range of parameters and values for first amino acid, first media condition
+		# FACTORS x # PARAMETERS
+	0-755: range of parameters and values over all amino acids for first media condition
+		# FACTORS x # PARAMETERS x # amino acids
+	0-1511: all changes
+		# FACTORS x # PARAMETERS x # amino acids x # MEDIA_IDS
 
 TODO:
 	- Run this for all AA additions or just Glt and control?
@@ -25,8 +30,8 @@
 import numpy as np
 
 
-FACTORS = [0, 0.1, 0.5, 1.5, 2, 5, 10]  # TODO: run factor of 1 once for each media condition
-PARAMETERS = ['aa_kcats', 'aa_kis', 'aa_upstream_kms', 'aa_reverse_kms', 'aa_degradation_kms']
+FACTORS = [0, 0.1, 0.5, 2, 5, 10]  # TODO: run factor of 1 once for each media condition
+PARAMETERS = ['aa_kcats_fwd', 'aa_kcats_rev', 'aa_kis', 'aa_upstream_kms', 'aa_reverse_kms', 'aa_degradation_kms']
 N_PARAM_VALUES = len(FACTORS) * len(PARAMETERS)
 MEDIA_IDS = [5, 19]  # Glt and control for now (need to update the analysis plot if changed)
 
@@ -59,7 +64,7 @@ def aa_synthesis_sensitivity(sim_data, index):
 	aa_idx = get_aa_index(index, sim_data)
 	param, factor = get_adjustment(index)
 	values = getattr(sim_data.process.metabolism, param)
-	if np.all(values[aa_idx] == values[aa_idx] * factor):
+	if np.all(~np.isfinite(values[aa_idx])) or np.all(values[aa_idx] == 0):
 		# Skip sims for parameters that are 0 or inf and will not be updated
 		raise ValueError('No change to params - not running variant sims.')
 	values[aa_idx] *= factor