add sympy support; which can transfer your network into sympy expression;

add visualize in genome;
add related tests.

tensorneat/utils/graph.py

@@ -5,6 +5,7 @@ Only used in feed-forward networks.
 
 import jax
 from jax import jit, Array, numpy as jnp
+from typing import Tuple, Set, List, Union
 
 from .tools import fetch_first, I_INF
 
@@ -41,6 +42,60 @@ def topological_sort(nodes: Array, conns: Array) -> Array:
     return res
 
 
+def topological_sort_python(
+    nodes: Union[Set[int], List[int]],
+    conns: Union[Set[Tuple[int, int]], List[Tuple[int, int]]],
+) -> Tuple[List[int], List[List[int]]]:
+    # a python version of topological_sort, use python set to store nodes and conns
+    # returns the topological order of the nodes and the topological layers
+    # written by gpt4 :)
+
+    # Make a copy of the input nodes and connections
+    nodes = nodes.copy()
+    conns = conns.copy()
+
+    # Initialize the in-degree of each node to 0
+    in_degree = {node: 0 for node in nodes}
+
+    # Compute the in-degree for each node
+    for conn in conns:
+        in_degree[conn[1]] += 1
+
+    topo_order = []
+    topo_layer = []
+
+    # Find all nodes with in-degree 0
+    zero_in_degree_nodes = [node for node in nodes if in_degree[node] == 0]
+
+    while zero_in_degree_nodes:
+
+        for node in zero_in_degree_nodes:
+            nodes.remove(node)
+
+        zero_in_degree_nodes = sorted(
+            zero_in_degree_nodes
+        )  # make sure the topo_order is from small to large
+
+        topo_layer.append(zero_in_degree_nodes.copy())
+
+        for node in zero_in_degree_nodes:
+            topo_order.append(node)
+
+            # Iterate over all connections and reduce the in-degree of connected nodes
+            for conn in list(conns):
+                if conn[0] == node:
+                    in_degree[conn[1]] -= 1
+                    conns.remove(conn)
+
+        zero_in_degree_nodes = [node for node in nodes if in_degree[node] == 0]
+
+    # Check if there are still connections left indicating a cycle
+    if conns or nodes:
+        raise ValueError("Graph has at least one cycle, topological sort not possible")
+
+    return topo_order, topo_layer
+
+
 @jit
 def check_cycles(nodes: Array, conns: Array, from_idx, to_idx) -> Array:
     """