TST: Make data-dependent test not depend upon data.

Previously, test_complexity and test_coefficients just tested that
- required names are present in SINDy object
- when fit on some amount of data, less than 10 terms were nonzero
- These are essentially the same test, since model.complexity is just
  a wrapper around it's optimizer's complexity property

But Lorenz has 7 nonzero terms, and when I changed the data to speed up
tests, data had a few more nonzeros.

test/test_pysindy.py

@@ -546,19 +546,13 @@ def test_differentiate(data_lorenz, data_multiple_trajctories):
         model.differentiate(x)
 
 
-def test_coefficients(data_lorenz):
+def test_coefficients_equals_complexity(data_lorenz):
     x, t = data_lorenz
     model = SINDy()
     model.fit(x, t)
     c = model.coefficients()
-    assert np.count_nonzero(c) < 10
-
-
-def test_complexity(data_lorenz):
-    x, t = data_lorenz
-    model = SINDy()
-    model.fit(x, t)
-    assert model.complexity < 10
+    assert model.complexity == np.count_nonzero(c)
+    assert model.complexity < 30
 
 
 def test_simulate_errors(data_lorenz):