# Path: stochpy/implementations/StochPyTools.py
# class Species():
# class StochPySSA_Shared(): 
#     def __init__(self):
#     def Parse(self,model_file,model_dir,IsTauleaping=False,IsNRM=False,IsDelayed = False,IsSMM = False,IsQuiet=False):
#     def SpeciesSelection(self):
#     def RateSelection(self):
#     def SetEvents(self):
#     def Propensities(self,IsTauleaping=False):
#     def BuildPropensityCodes(self, propensities = None): # 21-11-2013 
#     def HandleEvents(self,IsTauleapingStep=False):    
#     def AssignmentRules(self):
#     def rateFunc(self,rate_eval_code,r_vec):
#     def Initial_Conditions(self,IsTauleaping = False):              
#     def GenerateOutput(self,IsTauleaping = False,completion_delayed = False):


import sys,copy,time,os
from .StochPyTools import __species__,StochPySSA_Shared,np
                    self.species_to_update = self.parse.reaction_affects[self.reaction_index] # Determine vars to update                
                else:
                    self.species_to_update  = [s for s in range(self.n_species)]
               
                self.Propensities()
        
                if not settings.IsOnlyLastTimepoint:      # Store Output
                    self.GenerateOutput()
                    
            self._IsPerformEvent = False                  # set to false (or just to make sure).            
            t2 = time.time()        
            if IsStatusBar and t2-t1> 1:
                t1 = time.time()
                sys.stdout.write('\rsimulating {0:s}\r'.format('.'*nstep_counter) ) 
                sys.stdout.flush() 
                nstep_counter+=1
                if nstep_counter > 10:
                    nstep_counter = 1                
                    sys.stdout.write('\rsimulating {0:s}         '.format('.'*nstep_counter))
                    sys.stdout.flush()
        if settings.IsOnlyLastTimepoint or settings.endtime != 10**50:         
           self.GenerateOutput()        
        if IsStatusBar and t1 and not settings.quiet:  
            t1 = time.time()
            sys.stdout.write('\rsimulation done!               \n')   
            

    def RunExactTimestep(self):
        """ Perform a direct SSA time step and pre-generate M random numbers """    
        randoms = np.random.random(self.n_reactions)             # Regenerate for each time step M random numbers

# Path: stochpy/implementations/StochPyTools.py
# class Species():
# class StochPySSA_Shared(): 
#     def __init__(self):
#     def Parse(self,model_file,model_dir,IsTauleaping=False,IsNRM=False,IsDelayed = False,IsSMM = False,IsQuiet=False):
#     def SpeciesSelection(self):
#     def RateSelection(self):
#     def SetEvents(self):
#     def Propensities(self,IsTauleaping=False):
#     def BuildPropensityCodes(self, propensities = None): # 21-11-2013 
#     def HandleEvents(self,IsTauleapingStep=False):    
#     def AssignmentRules(self):
#     def rateFunc(self,rate_eval_code,r_vec):
#     def Initial_Conditions(self,IsTauleaping = False):              
#     def GenerateOutput(self,IsTauleaping = False,completion_delayed = False):


# Path: stochpy/implementations/FirstReactionMethod.py
import sys,copy,time,os
from .StochPyTools import __species__,StochPySSA_Shared,np

                    self.species_to_update = self.parse.reaction_affects[self.reaction_index] # Determine vars to update                
                else:
                    self.species_to_update  = [s for s in range(self.n_species)]
               
                self.Propensities()
        
                if not settings.IsOnlyLastTimepoint:      # Store Output
                    self.GenerateOutput()
                    
            self._IsPerformEvent = False                  # set to false (or just to make sure).            
            t2 = time.time()        
            if IsStatusBar and t2-t1> 1:
                t1 = time.time()
                sys.stdout.write('\rsimulating {0:s}\r'.format('.'*nstep_counter) ) 
                sys.stdout.flush() 
                nstep_counter+=1
                if nstep_counter > 10:
                    nstep_counter = 1                
                    sys.stdout.write('\rsimulating {0:s}         '.format('.'*nstep_counter))
                    sys.stdout.flush()
        if settings.IsOnlyLastTimepoint or settings.endtime != 10**50:         
           self.GenerateOutput()        
        if IsStatusBar and t1 and not settings.quiet:  
            t1 = time.time()
            sys.stdout.write('\rsimulation done!               \n')   
            

    def RunExactTimestep(self):
        """ Perform a direct SSA time step and pre-generate M random numbers """    
        randoms = np.random.random(self.n_reactions)             # Regenerate for each time step M random numbers

        self.randoms_log = np.log(randoms)*-1     