# Path: phievo/Networks/mutation.py
# T=1.0 #typical time scale
# C=1.0 #typical concentration
# L=1.0 #typical size for diffusion
#                 E_I=log(interval[1]/min_param) #range of possible energies
# def ligand_fct(random_generator):
# def build_lists(mutation_dict):
# def sample_dictionary_ranges(key,random_generator):
# def random_parameters(Types,random_generator):
# def rand_modify(self,random_generator):
#     def __init__(self,generator = random.Random()):
#     def compute_Cseed(self):
#     def random_Species(self, Type='Species'):
#     def random_Interaction(self,Interaction_Type):
#     def remove_Interaction(self,Type):
#     def random_remove_output(self):
#     def random_add_output(self):
#     def random_change_output(self):
#     def random_duplicate(self):
#     def mutate_Node(self,Type):
#     def build_mutations(self):
#         def update_dict(self,dictionary,key,name):
#     def compute_next_mutation(self):
#     def mutate_and_integrate(self,prmt,nnetwork,tgeneration,mutation=True):
# class Mutable_Network(classes_eds2.Network):


import ipywidgets as w
import random
import re
import tempfile,os
import subprocess
    import random
from IPython.display import display
from phievo.Networks import mutation
    from phievo.Networks import mutation
        for key in self.tags.keys():
            self.tags[key].clear()
        self.message.value = ""


    def error(self,message):
        self.add_button.description = "Clear"
        self.add_button.button_style = "danger"
        self.message.value = "Error: "+message
    def get_command(self):
        tags = [tag for tag in [self.tags[key].get_tag() for key in self.tags.keys()] if tag]

        if not self.isGene.value:
            #remove tag Species from  floating Species
            tags.remove(['Species'])
        param = "\tparam = {}".format(tags_to_str(tags))
        if self.isGene.value:
            if self.g_custom.value:
                function = "\ttm_d[ind],prom_d[ind],s_d[ind] = net.new_gene({rate},{delay},param,{basal})".format(rate=self.g_rate.value,delay=self.g_delay.value,basal=self.g_basal.value)
            else:
                function = "\ttm_d[ind],prom_d[ind],s_d[ind] = net.new_custom_random_gene(param)"
        else:
            function = "\ts_d[ind] = net.new_Species(param)"

        return [param,function],tags


def empty_net():
    seed = int(random.random()*100000)
    g = random.Random(seed)

# Path: phievo/Networks/mutation.py
# T=1.0 #typical time scale
# C=1.0 #typical concentration
# L=1.0 #typical size for diffusion
#                 E_I=log(interval[1]/min_param) #range of possible energies
# def ligand_fct(random_generator):
# def build_lists(mutation_dict):
# def sample_dictionary_ranges(key,random_generator):
# def random_parameters(Types,random_generator):
# def rand_modify(self,random_generator):
#     def __init__(self,generator = random.Random()):
#     def compute_Cseed(self):
#     def random_Species(self, Type='Species'):
#     def random_Interaction(self,Interaction_Type):
#     def remove_Interaction(self,Type):
#     def random_remove_output(self):
#     def random_add_output(self):
#     def random_change_output(self):
#     def random_duplicate(self):
#     def mutate_Node(self,Type):
#     def build_mutations(self):
#         def update_dict(self,dictionary,key,name):
#     def compute_next_mutation(self):
#     def mutate_and_integrate(self,prmt,nnetwork,tgeneration,mutation=True):
# class Mutable_Network(classes_eds2.Network):


# Path: phievo/ConfigurationTools/initnetwork.py
import ipywidgets as w
import random
import re
import tempfile,os
import subprocess
    import random
from IPython.display import display
from phievo.Networks import mutation
    from phievo.Networks import mutation

        for key in self.tags.keys():
            self.tags[key].clear()
        self.message.value = ""


    def error(self,message):
        self.add_button.description = "Clear"
        self.add_button.button_style = "danger"
        self.message.value = "Error: "+message
    def get_command(self):
        tags = [tag for tag in [self.tags[key].get_tag() for key in self.tags.keys()] if tag]

        if not self.isGene.value:
            #remove tag Species from  floating Species
            tags.remove(['Species'])
        param = "\tparam = {}".format(tags_to_str(tags))
        if self.isGene.value:
            if self.g_custom.value:
                function = "\ttm_d[ind],prom_d[ind],s_d[ind] = net.new_gene({rate},{delay},param,{basal})".format(rate=self.g_rate.value,delay=self.g_delay.value,basal=self.g_basal.value)
            else:
                function = "\ttm_d[ind],prom_d[ind],s_d[ind] = net.new_custom_random_gene(param)"
        else:
            function = "\ts_d[ind] = net.new_Species(param)"

        return [param,function],tags


def empty_net():
    seed = int(random.random()*100000)
    g = random.Random(seed)

    net = mutation.Mutable_Network(g)