dye: get things to kind of work with naive dye model

Author: nilsceberg

lib/pim/models/new/stone/dye.py

@@ -22,7 +22,8 @@ def update_weights(self, inputs: Output, dt: float):
         pass
 
     def output(self, network: Network) -> Output:
-        return network.output("CPU4") * self.weights
+        return network.output("CPU4") * self.weights * 300000
+        #return np.log10(network.output("CPU4") * self.weights) + 6 #* 30000
 
 
 class SimpleDyeLayer(DyeLayer):
@@ -37,14 +38,14 @@ def update_weights(self, inputs: Output, dt: float):
         self.weights += -self.backreaction_rate*dt + self.gain*inputs*dt
 
 class AdvancedDyeLayer(DyeLayer):
-    def __init__(self, epsilon, length, T_half, phi, c_tot):
+    def __init__(self, epsilon, length, T_half, phi, beta, c_tot):
         self.epsilon = epsilon
         self.length = length
         self.k = np.log(2) / T_half
         self.phi = phi
         self.c_tot = c_tot
 
-        self.last_c = np.zeros(16)
+        self.last_c = np.ones(16) * phi * beta / self.k
 
         super().__init__()
 
@@ -54,7 +55,7 @@ def dcdt(t, c):
             return -self.k * c + self.phi * inputs
 
 
-        solution = solve_ivp(dcdt, y0 = self.last_c, t_span=(0, dt))
+        solution = solve_ivp(dcdt, y0 = self.last_c, t_span=(0, dt*0.01))
         c = solution.y[:,-1]
         # print(c)
         self.last_c = c
@@ -98,6 +99,7 @@ def build_network(self) -> Network:
                 epsilon = self.epsilon, 
                 length = self.length, 
                 T_half = self.T_half, 
+                beta = self.beta,
                 phi = self.phi,
                 c_tot = self.c_tot
             ),
@@ -133,7 +135,7 @@ def build_cpu4_layer(self) -> Layer:
             "TB1", "TN1", "TN2",
             self.W_TN_CPU4,
             self.W_TB1_CPU4,
-            self.cpu4_mem_gain,
+            self.cpu4_mem_gain * 10,
             self.cpu4_slope,
             self.cpu4_bias,
             self.noise,

lib/pim/models/new/stone/rate.py

@@ -59,7 +59,7 @@ def output(self, network: Network) -> Output:
 
         mem_update = np.dot(self.W_TN, tn2)
         mem_update -= np.dot(self.W_TB1, tb1)
-        return noisy_sigmoid(mem_update, self.slope, self.bias, self.noise) + self.background_activity
+        return noisy_sigmoid(mem_update, self.slope, self.bias, self.noise) * self.gain + self.background_activity
 
 class CPU4Layer(Layer):
     def __init__(self, TB1, TN1, TN2, W_TN, W_TB1, gain, slope, bias, noise):

setups/dye-short.json

@@ -0,0 +1,18 @@
+{
+    "experiments": {
+        "stone": {
+            "model": "stone",
+            "T_outbound": 1500,
+            "T_inbound": 1500,
+            "noise": 0.1,
+            "cx": "dye",
+            "record": ["CPU4", "memory"],
+            "phi": 0.015,
+            "beta": 1.0,
+            "T_half": 0.29411764705882354,
+            "epsilon": 2e5,
+            "length": 50e-4,
+            "c_tot": 0.3
+        }
+    }
+}

setups/dye.json

@@ -0,0 +1,18 @@
+{
+    "experiments": {
+        "stone": {
+            "model": "stone",
+            "T_outbound": 1500,
+            "T_inbound": 1500,
+            "noise": 0.1,
+            "cx": "dye",
+            "record": ["CPU4", "memory"],
+            "phi": 0.0015,
+            "beta": 1.0,
+            "T_half": 135.91121187449906,
+            "epsilon": 2e5,
+            "length": 50e-4,
+            "c_tot": 0.3
+        }
+    }
+}

setups/stone-as-is.json

@@ -3,9 +3,10 @@
         "stone": {
             "model": "stone",
             "T_outbound": 1500,
-            "T_inbound": 1000,
+            "T_inbound": 1500,
             "noise": 0.1,
-            "cx": "pontine"
+            "cx": "pontine",
+            "record": ["CPU4-no-mem"]
         }
     }
 }