changed EPS in cells.py

cd_network/cells.py

@@ -4,12 +4,14 @@
 
 from .coincidence_integral import cached_coincidence_integral, coincidence_integral
 
+EPS = 1e-15
+
 
 def ei(
-    excitatory_input: np.ndarray,
-    inhibitory_inputs: np.ndarray,
-    delta_s: float,
-    fs: float,
+        excitatory_input: np.ndarray,
+        inhibitory_inputs: np.ndarray,
+        delta_s: float,
+        fs: float,
 ) -> np.ndarray:
     """
     The general EI cell spikes whenever the excitatory input spikes and in the preceding ∆ seconds none of the
@@ -34,7 +36,7 @@ def ei(
         inhibitory_inputs = inhibitory_inputs[np.newaxis, ...]
 
     assert (
-        len(excitatory_input) == inhibitory_inputs.shape[-1]
+            len(excitatory_input) == inhibitory_inputs.shape[-1]
     ), "Length of excitatory input must match the size of inhibitory inputs along the last axis."
 
     output = excitatory_input * np.prod(
@@ -63,12 +65,12 @@ def _all_spikes_ee(inputs: np.ndarray, delta_s: float, fs: float) -> np.ndarray:
     n_inputs, samples = inputs.shape
     output = np.zeros(samples)
     for i in range(n_inputs):
-        output += inputs[i] * coincidence_prod / (coincidence_integral_outputs[i] + np.finfo(np.float64))
+        output += inputs[i] * coincidence_prod / (coincidence_integral_outputs[i] + EPS)
     return output
 
 
 def _exactly_n_spikes_ee(
-    inputs: np.ndarray, n_spikes: int, delta_s: float, fs: float
+        inputs: np.ndarray, n_spikes: int, delta_s: float, fs: float
 ) -> np.ndarray:
     """
     An all-spikes EE cell generates a spike whenever exactly n_spikes of its inputs spikes during an interval ∆.
@@ -86,7 +88,7 @@ def _exactly_n_spikes_ee(
 
     n_inputs, samples = inputs.shape
     assert (
-        n_inputs <= n_inputs
+            n_inputs <= n_inputs
     ), "n_spikes should be less than or equal to the number of inputs."
 
     output = np.zeros(samples)
@@ -152,7 +154,7 @@ def ee(inputs, n_spikes: int, delta_s: float, fs: float) -> np.ndarray:
 
     n_inputs, samples = inputs.shape
     assert (
-        n_inputs <= n_inputs
+            n_inputs <= n_inputs
     ), "n_spikes should be less than or equal to the number of inputs."
 
     output = np.zeros(samples)
@@ -163,11 +165,11 @@ def ee(inputs, n_spikes: int, delta_s: float, fs: float) -> np.ndarray:
 
 
 def cd(
-    excitatory_inputs: np.ndarray,
-    inhibitory_inputs: np.ndarray,
-    n_spikes: int,
-    delta_s: float,
-    fs: float,
+        excitatory_inputs: np.ndarray,
+        inhibitory_inputs: np.ndarray,
+        n_spikes: int,
+        delta_s: float,
+        fs: float,
 ) -> np.ndarray:
     """
     A general CD cell is defined as one with n_excitatory_inputs excitatory inputs and n_inhibitory_inputs inhibitory
@@ -205,7 +207,7 @@ def cd(
     n_inhibitory_inputs, inhibitory_samples = inhibitory_inputs.shape
 
     assert (
-        inhibitory_samples == excitatory_samples
+            inhibitory_samples == excitatory_samples
     ), "Number of samples in inhibitory and excitatory inputs must match."
 
     output = np.zeros(excitatory_samples)