Add coveralls badge

README.md

@@ -5,6 +5,7 @@
 [![Documentation Status](https://readthedocs.org/projects/pysr/badge/?version=latest)](https://pysr.readthedocs.io/en/latest/?badge=latest)
 [![PyPI version](https://badge.fury.io/py/pysr.svg)](https://badge.fury.io/py/pysr)
 ![.github/workflows/CI.yml](https://github.com/MilesCranmer/PySR/workflows/.github/workflows/CI.yml/badge.svg)
+[![Coverage Status](https://coveralls.io/repos/github/MilesCranmer/PySR/badge.svg)](https://coveralls.io/github/MilesCranmer/PySR)
 
 **Parallelized symbolic regression built on Julia, and interfaced by Python.
 Uses regularized evolution, simulated annealing, and gradient-free optimization.**

test/test.py

@@ -70,5 +70,5 @@ class TestBest(unittest.TestCase):
     def test_best_lambda(self):
         X = np.random.randn(10, 2)
         y = np.cos(X[:, 0])**2
-        for f in [best_callable(), best_callable(self.equations))]:
+        for f in [best_callable(), best_callable(self.equations)]:
             np.testing.assert_almost_equal(f(X), y)