Merge pull request #25 from AutoResearch/add-standard-operators-and_f…

…unctions

Add standard operators and functions

README.md

@@ -1,16 +1,25 @@
-# Quickstart Guide
+# Equation Tree
 
-You will need:
+The Equation Tree package is an equation toolbox with symbolic regression in mind. It represents
+expressions as incomplete binary trees and has various features tailored towards testing symbolic
+regression algorithms or training models. The main features are:
 
-- `python` 3.8 or greater: [https://www.python.org/downloads/](https://www.python.org/downloads/)
+- Equation sampling (including priors)
+- Feature Extraction from equation distributions
+- Distance metrics between equations
 
 
-```shell
-pip install -U equation-tree
-```
+## Getting Started
 
+Check out the documentation at 
+[https://autoresearch.github.io/equation-tree](https://autoresearch.github.io/equation-tree).
 
-Check your installation by running:
-```shell
-python -c "from equation_tree import EquationTree"
-```
+## About
+
+This project is in active development by
+the <a href="https://musslick.github.io/AER_website/Research.html">Autonomous Empirical Research
+Group</a>
+(package developer: <a href="https://younesstrittmatter.github.io/">Younes Strittmatter</a>,
+PI: <a href="https://smusslick.com/">Sebastian Musslick</a>. This research program is supported by
+Schmidt Science Fellows, in partnership with the Rhodes Trust, as well as the Carney BRAINSTORM
+program at Brown University.

dev/burn.py

@@ -0,0 +1,65 @@
+from equation_tree.sample import burn
+from equation_tree.defaults import DEFAULT_PRIOR
+
+prior_0 = {
+    'structures': {'[0, 1, 1]': .3, '[0, 1, 2]': .3, '[0, 1, 2, 3, 2, 3, 1]': .4},
+    'features': {'constants': .2, 'variables': .8},
+    'functions': {'sin': .5, 'cos': .5},
+    'operators': {'+': .8, '-': .2}
+}
+
+
+
+prior_1 = {
+    'structures': {'[0, 1, 1]': .3, '[0, 1, 2]': .3, '[0, 1, 2, 3, 2, 3, 1]': .4},
+    'features': {'constants': .2, 'variables': .8},
+    'functions': {'sin': .5, 'cos': .5},
+    'operators': {'+': .5, '-': .5},
+    'function_conditionals': {
+        'sin': {
+            'features': {'constants': 0., 'variables': 1.},
+            'functions': {'sin': 0., 'cos': 1.},
+            'operators': {'+': .5, '-': .5}
+        },
+        'cos': {
+            'features': {'constants': 0., 'variables': 1.},
+            'functions': {'cos': 1., 'sin': 0.},
+            'operators': {'+': 0., '-': 1.}
+        }
+    },
+    'operator_conditionals': {
+        '+': {
+            'features': {'constants': .5, 'variables': .5},
+            'functions': {'sin': 1., 'cos': 0.},
+            'operators': {'+': 1., '-': 0.}
+        },
+        '-': {
+            'features': {'constants': .3, 'variables': .7},
+            'functions': {'cos': .5, 'sin': .5},
+            'operators': {'+': .9, '-': .1}
+        }
+    },
+}
+
+# import random
+for _ in range(1, 5):
+    burn(DEFAULT_PRIOR,
+         _,
+         "../src/equation_tree/data/_hashed_probabilities.json",
+         10_000,
+         0.5,
+         )
+    burn(
+        prior_0,
+        2,
+        "../src/equation_tree/data/_hashed_probabilities.json",
+        10_000,
+        0.5,
+    )
+    burn(
+        prior_1,
+        2,
+        "../src/equation_tree/data/_hashed_probabilities.json",
+        10_000,
+        0.5,
+    )