diff --git a/.gitignore b/.gitignore
index f315f45899cd3be336c0d6c26cd766bc6e6d5a33..73346d4b3ea9405ee6dc8d852a57b261ff81e7f1 100644
--- a/.gitignore
+++ b/.gitignore
@@ -5,4 +5,4 @@ src/lib/__pycache__/
src/lib/autogrid_reference_files/
src/lib/autogrids/
.ipynb_checkpoints/
-
+debugging.txt
diff --git a/src/lib/pathways/Gi.py b/src/lib/pathways/Gi.py
index 15519753edbd1b6df0a3a70d11c625220daf54d5..00bb42e4a3a6f5313237d9266e8c7d36d0f0c3a6 100644
--- a/src/lib/pathways/Gi.py
+++ b/src/lib/pathways/Gi.py
@@ -18,79 +18,87 @@ from pysb.macros import *
from pysb.macros import create_t_obs, drug_binding
from sympy import Piecewise
-
+defaultParameters = {
+ 'time_in':0,
+ 'time_out':0,
+ 'L_init':0.01,
+ 'R_init': 2,
+ 'Gi_init': 3,
+ 'AC5_init': 0.7,
+ 'Ca_cytos_free': 0.06,
+ 'ATP_init': 5000,
+ 'PDE4_init': 2,
+ 'PDE10_init': 1,
+ 'PKA_init': 1.2,
+ 'RL_kon':0.1*1E3,
+ 'RL_koff':200,
+ 'RL_Gi_kon':6.6*1E3,
+ 'RL_Gi_koff':200,
+ 'RL_Gi_decay': 60,
+ 'GaiGTP_decay': 30,
+ 'Gi_formation': 100,
+ 'AC5_ATP_kon': 0.0001*1E3,
+ 'AC5_ATP_koff': 1,
+ 'AC5_basal': 1,
+ 'AC5_reverse_basal': 0.0004,
+ 'AC5_Ca_kon': 0.001*1E3,
+ 'AC5_Ca_koff': 0.9,
+ 'AC5_Ca_ATP_kon': 7.50E-5*1E3,
+ 'AC5_Ca_ATP_koff': 1,
+ 'AC5_Ca_ATP_to_cAMP': 0.5,
+ 'AC5_Ca_ATP_to_cAMP_reverse': 0.00015,
+ 'AC5_ATP_Ca_kon': 0.001*1E3,
+ 'AC5_ATP_Ca_koff': 0.9,
+ 'AC5_GaiGTP_kon': 50*1E3,
+ 'AC5_GaiGTP_koff': 5,
+ 'AC5_GaiGTP_ATP_kon': 6.25E-5*1E3,
+ 'AC5_GaiGTP_ATP_koff': 1,
+ 'AC5_ATP_GaiGTP_kon': 50*1E3,
+ 'AC5_ATP_GaiGTP_koff': 5,
+ 'AC5_GaiGTP_ATP_to_cAMP': 0.25,
+ 'AC5_GaiGTP_ATP_to_cAMP_reverse': 0.00105,
+ 'AC5_GaiGTP_decay': 30,
+ 'AC5_GaiGTP_decay_koff': 30,
+ 'AC5_Ca_GaiGTP_kon': 50*1E3,
+ 'AC5_Ca_GaiGTP_koff': 5,
+ 'AC5_Ca_GaiGTP_ATP_kon': 5.63E-5*1E3,
+ 'AC5_Ca_GaiGTP_ATP_koff': 1,
+ 'AC5_Ca_ATP_GaiGTP_kon': 50*1E3,
+ 'AC5_Ca_ATP_GaiGTP_koff': 5,
+ 'AC5_Ca_GaiGTP_ATP_to_cAMP': 0.125,
+ 'AC5_Ca_GaiGTP_ATP_to_cAMP_reverse': 2.81E-5,
+ 'AC5_Ca_GaiGTP_decay': 30,
+ 'AC5_Ca_GaiGTP_ATP_decay': 30,
+ 'PDE4_cAMP_kon': 0.01*1E3,
+ 'PDE4_cAMP_koff': 1,
+ 'PDE4_cAMP_to_AMP': 2,
+ 'PDE10_2cAMP_kon': 1.0E-6*1E3,
+ 'PDE10_2cAMP_koff': 9,
+ 'PDE10_cAMP_kon': 0.1*1E3,
+ 'PDE10_cAMP_koff': 2,
+ 'PDE10_2cAMP_cAMP_kon': 0.13*1E3,
+ 'PDE10_2cAMP_cAMP_koff': 2,
+ 'PDE10_cAMP_decay': 3,
+ 'PDE10_2cAMP_cAMP_decay': 10,
+ 'PKA_cAMP2_kon': 0.00026*1E3,
+ 'PKA_cAMP2_koff': 1,
+ 'PKA_cAMP4_kon': 0.000346*1E3,
+ 'PKA_cAMP4_koff': 1,
+ 'PKA_activation': 10*1E3,
+ 'PKA_activation_reverse': 0.025
+}
def network(LR=None, kinetics=True, **kwargs):
- defaultKwargs = {
- 'time_in':0,
- 'time_out':0,
- 'L_init':0.01,
- 'R_init': 2,
- 'Gi_init': 3,
- 'AC5_init': 0.7,
- 'Ca_cytos_free': 0.06,
- 'ATP_init': 5000,
- 'PDE4_init': 2,
- 'PDE10_init': 1,
- 'PKA_init': 1.2,
- 'RL_kon':0.1*1E3,
- 'RL_koff':200,
- 'RL_Gi_kon':6.6*1E3,
- 'RL_Gi_koff':200,
- 'RL_Gi_decay': 60,
- 'GaiGTP_decay': 30,
- 'Gi_formation': 100,
- 'AC5_ATP_kon': 0.0001*1E3,
- 'AC5_ATP_koff': 1,
- 'AC5_basal': 1,
- 'AC5_reverse_basal': 0.0004,
- 'AC5_Ca_kon': 0.001*1E3,
- 'AC5_Ca_koff': 0.9,
- 'AC5_Ca_ATP_kon': 7.50E-5*1E3,
- 'AC5_Ca_ATP_koff': 1,
- 'AC5_Ca_ATP_to_cAMP': 0.5,
- 'AC5_Ca_ATP_to_cAMP_reverse': 0.00015,
- 'AC5_ATP_Ca_kon': 0.001*1E3,
- 'AC5_ATP_Ca_koff': 0.9,
- 'AC5_GaiGTP_kon': 50*1E3,
- 'AC5_GaiGTP_koff': 5,
- 'AC5_GaiGTP_ATP_kon': 6.25E-5*1E3,
- 'AC5_GaiGTP_ATP_koff': 1,
- 'AC5_ATP_GaiGTP_kon': 50*1E3,
- 'AC5_ATP_GaiGTP_koff': 5,
- 'AC5_GaiGTP_ATP_to_cAMP': 0.25,
- 'AC5_GaiGTP_ATP_to_cAMP_reverse': 0.00105,
- 'AC5_GaiGTP_decay': 30,
- 'AC5_GaiGTP_decay_koff': 30,
- 'AC5_Ca_GaiGTP_kon': 50*1E3,
- 'AC5_Ca_GaiGTP_koff': 5,
- 'AC5_Ca_GaiGTP_ATP_kon': 5.63E-5*1E3,
- 'AC5_Ca_GaiGTP_ATP_koff': 1,
- 'AC5_Ca_ATP_GaiGTP_kon': 50*1E3,
- 'AC5_Ca_ATP_GaiGTP_koff': 5,
- 'AC5_Ca_GaiGTP_ATP_to_cAMP': 0.125,
- 'AC5_Ca_GaiGTP_ATP_to_cAMP_reverse': 2.81E-5,
- 'AC5_Ca_GaiGTP_decay': 30,
- 'AC5_Ca_GaiGTP_ATP_decay': 30,
- 'PDE4_cAMP_kon': 0.01*1E3,
- 'PDE4_cAMP_koff': 1,
- 'PDE4_cAMP_to_AMP': 2,
- 'PDE10_2cAMP_kon': 1.0E-6*1E3,
- 'PDE10_2cAMP_koff': 9,
- 'PDE10_cAMP_kon': 0.1*1E3,
- 'PDE10_cAMP_koff': 2,
- 'PDE10_2cAMP_cAMP_kon': 0.13*1E3,
- 'PDE10_2cAMP_cAMP_koff': 2,
- 'PDE10_cAMP_decay': 3,
- 'PDE10_2cAMP_cAMP_decay': 10,
- 'PKA_cAMP2_kon': 0.00026*1E3,
- 'PKA_cAMP2_koff': 1,
- 'PKA_cAMP4_kon': 0.000346*1E3,
- 'PKA_cAMP4_koff': 1,
- 'PKA_activation': 10*1E3,
- 'PKA_activation_reverse': 0.025
- }
- parameters={**defaultKwargs, **kwargs}
+
+ parameters={**defaultParameters, **kwargs}
+ def myeval(x):
+ try:
+ y = eval(x)
+ except:
+ y=x
+ return y
+
+ parameters = dict(zip(parameters.keys(), map(myeval, parameters.values())))
#Start a model
Model()
diff --git a/src/lib/pathways/Gq.py b/src/lib/pathways/Gq.py
index ea4c9585fb8a38c7cabb4cb4784c5e8f34b0ff95..e3f15b51a79f685a36151210bae8744abf98fc1a 100644
--- a/src/lib/pathways/Gq.py
+++ b/src/lib/pathways/Gq.py
@@ -31,10 +31,7 @@ __email__ = "rui.ribeiro@univr.it"
__status__ = "Production"
USAGE = __doc__.format(__author__, __email__)
-
-def network(LR=None, kinetics=True, **kwargs):
-
- defaultKwargs = {
+defaultParameters = {
'time_in':0,
'time_out':0,
'L_init':0,
@@ -76,7 +73,17 @@ def network(LR=None, kinetics=True, **kwargs):
'DAG_decay':0.15,
}
- parameters={**defaultKwargs, **kwargs}
+def network(LR=None, kinetics=True, **kwargs):
+
+ parameters={**defaultParameters, **kwargs}
+ def myeval(x):
+ try:
+ y = eval(x)
+ except:
+ y=x
+ return y
+
+ parameters = dict(zip(parameters.keys(), map(myeval, parameters.values())))
#Start a model
Model()
diff --git a/src/lib/pathways/Gs.py b/src/lib/pathways/Gs.py
index 2f23250ff0b91b4b49e159488c66a07526f46f0f..c1e2af0da6cbd165bf1785f35ca8afcac1b240f5 100644
--- a/src/lib/pathways/Gs.py
+++ b/src/lib/pathways/Gs.py
@@ -19,10 +19,7 @@ from pysb.macros import *
from sympy import Piecewise
from pysb.macros import create_t_obs, drug_binding
-
-def network(LR=None, kinetics=True, **kwargs):
-
- defaultKwargs = {
+defaultParameters = {
'time_in':0,
'time_out':0,
'L_init':0.01,
@@ -91,8 +88,21 @@ def network(LR=None, kinetics=True, **kwargs):
'PKA_activation': 10*1E3,
'PKA_activation_reverse': 0.01
}
- parameters={**defaultKwargs, **kwargs}
+
+def network(LR=None, kinetics=True, **kwargs):
+
+ parameters={**defaultParameters, **kwargs}
+ def myeval(x):
+ try:
+ y = eval(x)
+ except:
+ y=x
+ return y
+
+ parameters = dict(zip(parameters.keys(), map(myeval, parameters.values())))
+
+
#Start a model
Model()
diff --git a/src/lib/pathways/__pycache__/Gs.cpython-39.pyc b/src/lib/pathways/__pycache__/Gs.cpython-39.pyc
index 5a2fd0988d52e19212fe139ec90a2fdf3167f03d..f2526a339a1f76d36c791c488a40bd6551e3282a 100644
Binary files a/src/lib/pathways/__pycache__/Gs.cpython-39.pyc and b/src/lib/pathways/__pycache__/Gs.cpython-39.pyc differ