Fix bug with Int32 rounding of equation age

README.md

@@ -327,6 +327,7 @@ pd.DataFrame, Results dataframe, giving complexity, MSE, and equations
 ## Algorithmic performance ideas:
 
 - [ ] Idea: use gradient of equation with respect to each operator (perhaps simply add to each operator) to tell which part is the most "sensitive" to changes. Then, perhaps insert/delete/mutate on that part of the tree?
+- [ ] Start populations staggered; so that there is more frequent printing (and pops that start a bit later get hall of fame already)?
 - [ ] Consider adding mutation for constant<->variable
 - [ ] Implement more parts of the original Eureqa algorithms: https://www.creativemachineslab.com/eureqa.html
 - [ ] Experiment with freezing parts of model; then we only append/delete at end of tree.

julia/sr.jl

@@ -41,8 +41,8 @@ function debug(verbosity, string...)
     verbosity > 0 ? println(string...) : nothing
 end
 
-function getTime()::Int32
-    return round(Int32, 1e3*(time()-1.6e9))
+function getTime()::Integer
+    return round(Integer, 1e3*(time()-1.6e9))
 end
 
 # Define a serialization format for the symbolic equations:
@@ -526,7 +526,7 @@ end
 mutable struct PopMember
     tree::Node
     score::Float32
-    birth::Int32
+    birth::Integer
 
     PopMember(t::Node) = new(t, scoreFunc(t), getTime())
     PopMember(t::Node, score::Float32) = new(t, score, getTime())

setup.py

@@ -5,7 +5,7 @@ with open("README.md", "r") as fh:
 
 setuptools.setup(
     name="pysr", # Replace with your own username
-    version="0.3.17",
+    version="0.3.18",
     author="Miles Cranmer",
     author_email="[email protected]",
     description="Simple and efficient symbolic regression",