Example #1
0
 def __init__(self,dimensions,min=-1,max=1,noise=0):
     self.inputs=[]
     self.outputs=[]
     self.dimensions=dimensions
     self.min=min
     self.max=max
     self.array_noise=noise
     
     self.mode='direct'
     self._all_nodes=None
     self.accumulator=Accumulator(dimensions)
Example #2
0
 def __init__(self,dimensions,min=-1,max=1,noise=0):
     self.inputs=[]
     self.outputs=[]
     self.dimensions=dimensions
     self.min=min
     self.max=max
     self.array_noise=noise
     
     self.mode='direct'
     self._all_nodes=None
     self.accumulator=Accumulator(dimensions)
Example #3
0
class ArrayNode:    
    _set_array=None
    _value=None
    _array=None
#    _input=None
    _output=None
        
    def __init__(self,dimensions,min=-1,max=1,noise=0):
        self.inputs=[]
        self.outputs=[]
        self.dimensions=dimensions
        self.min=min
        self.max=max
        self.array_noise=noise
        
        self.mode='direct'
        self._all_nodes=None
        self.accumulator=Accumulator(dimensions)
        
    def clone(self):
        clone=copy.copy(self)
        clone.inputs=[]
        clone.outputs=[]
        clone.accumulator=Accumulator(self.dimensions)   
        return clone     
        
        
    def set(self,value,calc_output=True):
        if value is None:
            self._set_array=None
            self._array=None
            self._value=None
            if calc_output: self._calc_output()
        else:    
            array=numpy.array(self.value_to_array(value))
            if len(array.shape)>1: array.shape=array.shape[0]
            assert len(array)==self.dimensions
            self._set_array=array
            if calc_output: self._calc_output()
            self._array=None
            self._value=None

    def array(self):
        if self._array is None:
            if self._output is None: self._output=numpy.zeros(self.dimensions)
            self._array=self._output
        return self._array
    def value(self):
        if self._value is None:
            self._value=self.array_to_value(self.array())
        return self._value



    def _calc_output(self):
        if self._output is None: self._output=numpy.zeros(self.dimensions)
        else: self._output[:]=0
        if self._set_array is not None:
            self._output+=self._set_array
        else:
            self._output+=self.accumulator.value()    
        if self.array_noise>0:
            self._output+=numpy.random.randn(self.dimensions)*self.array_noise

    def _clear_inputs(self):
        pass
    
    def _transmit_direct_direct(self,conn,dt):
        conn.pop2.accumulator.add(conn.apply_func_weight(self._output),conn.tau,dt)
        
    def tick(self,dt=None):
        if dt is None: dt=getattr(self,'dt',None)
        nodes=self._all_nodes
        if nodes is None:
            nodes=self.all_nodes()
            for n in nodes:
                n._all_nodes=nodes
        for n in nodes:
            n._clear_inputs()
            n.accumulator.tick(dt)
        for n in nodes:
            for conn in n.outputs:
                f=getattr(n,'_transmit_%s'%conn.type())
                f(conn,dt)
        for n in nodes:
            n._calc_output()
            n._value=None
            n._array=None


    def connect(self,other,func=None,weight=None,tau=None):
        return connect(self,other,func=func,weight=weight,tau=tau)

    """    
    def all_nodes(self,list=None):
        if list is None: list=[]
        list.append(self)
        for c in self.inputs:
            if c.pop1 not in list:
                c.pop1.all_nodes(list)
        for c in self.outputs:
            if c.pop2 not in list:
                c.pop2.all_nodes(list)
        return list
    """    
    def all_nodes(self):
        all=[]
        done=set()
        work=set([self])
        while len(work)>0:
            n=work.pop()
            done.add(n)
            all.append(n)
            for a in n.inputs:
                if a.pop1 not in done: work.add(a.pop1)
            for a in n.outputs:
                if a.pop2 not in done: work.add(a.pop2)
        return all 
Example #4
0
class ArrayNode:    
    _set_array=None
    _value=None
    _array=None
#    _input=None
    _output=None
        
    def __init__(self,dimensions,min=-1,max=1,noise=0):
        self.inputs=[]
        self.outputs=[]
        self.dimensions=dimensions
        self.min=min
        self.max=max
        self.array_noise=noise
        
        self.mode='direct'
        self._all_nodes=None
        self.accumulator=Accumulator(dimensions)
        
        
    def set(self,value,calc_output=True):
        if value is None:
            self._set_array=None
            self._array=None
            self._value=None
            if calc_output: self._calc_output()
        else:    
            array=numpy.array(self.value_to_array(value))
            if len(array.shape)>1: array.shape=array.shape[0]
            assert len(array)==self.dimensions
            self._set_array=array
            if calc_output: self._calc_output()
            self._array=None
            self._value=None

    def array(self):
        if self._array is None:
            if self._output is None: self._output=numpy.zeros(self.dimensions)
            self._array=self._output
        return self._array
    def value(self):
        if self._value is None:
            self._value=self.array_to_value(self.array())
        return self._value



    def _calc_output(self):
        if self._output is None: self._output=numpy.zeros(self.dimensions)
        else: self._output[:]=0
        if self._set_array is not None:
            self._output+=self._set_array
        else:
            self._output+=self.accumulator.value()    
        if self.array_noise>0:
            self._output+=numpy.random.randn(self.dimensions)*self.array_noise

    def _clear_inputs(self):
        pass
    
    def _transmit_direct_direct(self,conn,dt):
        conn.pop2.accumulator.add(conn.apply_func_weight(self._output),conn.tau,dt)
        
    def tick(self,dt=None):
        if dt is None: dt=getattr(self,'dt',None)
        nodes=self._all_nodes
        if nodes is None:
            nodes=self.all_nodes()
            for n in nodes:
                n._all_nodes=nodes
        for n in nodes:
            n._clear_inputs()
            n.accumulator.tick(dt)
        for n in nodes:
            for conn in n.outputs:
                f=getattr(n,'_transmit_%s'%conn.type())
                f(conn,dt)
        for n in nodes:
            n._calc_output()
            n._value=None
            n._array=None


    def connect(self,other,func=None,weight=None,tau=None):
        return connect(self,other,func=func,weight=weight,tau=tau)

    """    
    def all_nodes(self,list=None):
        if list is None: list=[]
        list.append(self)
        for c in self.inputs:
            if c.pop1 not in list:
                c.pop1.all_nodes(list)
        for c in self.outputs:
            if c.pop2 not in list:
                c.pop2.all_nodes(list)
        return list
    """    
    def all_nodes(self):
        all=[]
        done=set()
        work=set([self])
        while len(work)>0:
            n=work.pop()
            done.add(n)
            all.append(n)
            for a in n.inputs:
                if a.pop1 not in done: work.add(a.pop1)
            for a in n.outputs:
                if a.pop2 not in done: work.add(a.pop2)
        return all 
 def clone(self):
     clone = copy.copy(self)
     clone.inputs = []
     clone.outputs = []
     clone.accumulator = Accumulator(self.dimensions)
     return clone