TST: add test for ampgo method

tests/test_ampgo.py

@@ -0,0 +1,55 @@
+import numpy as np
+from numpy.testing import assert_allclose
+
+import lmfit
+
+
+def test_ampgo_Alpine02():
+    """Test AMPGO algorithm on Alpine02 function."""
+
+    global_optimum = [7.91705268, 4.81584232]
+    fglob = -6.12950
+
+    def residual_Alpine02(params):
+        x0 = params['x0'].value
+        x1 = params['x1'].value
+        return np.prod(np.sqrt(x0) * np.sin(x0)) * np.prod(np.sqrt(x1) *
+                                                           np.sin(x1))
+
+    pars = lmfit.Parameters()
+    pars.add_many(('x0', 1., True, 0.0, 10.0),
+                  ('x1', 1., True, 0.0, 10.0))
+
+    mini = lmfit.Minimizer(residual_Alpine02, pars)
+    out = mini.minimize(method='ampgo')
+    out_x = np.array([out.params['x0'].value, out.params['x1'].value])
+
+    assert_allclose(out.chisqr, fglob, rtol=1e-5)
+    assert_allclose(min(out_x), min(global_optimum), rtol=1e-3)
+    assert_allclose(max(out_x), max(global_optimum), rtol=1e-3)
+    assert('global' in out.ampgo_msg)
+
+
+
+def test_ampgo_Alpine02_maxfunevals():
+    """Test AMPGO algorithm on Alpine02 function."""
+
+    def residual_Alpine02(params):
+        x0 = params['x0'].value
+        x1 = params['x1'].value
+        return np.prod(np.sqrt(x0) * np.sin(x0)) * np.prod(np.sqrt(x1) *
+                                                           np.sin(x1))
+
+    pars = lmfit.Parameters()
+    pars.add_many(('x0', 1., True, 0.0, 10.0),
+                  ('x1', 1., True, 0.0, 10.0))
+
+    mini = lmfit.Minimizer(residual_Alpine02, pars)
+    kws = {'maxfunevals': 50}
+    out = mini.minimize(method='ampgo', **kws)
+    assert('function' in out.ampgo_msg)
+
+
+if __name__ == '__main__':
+    test_ampgo_Alpine02()
+    test_ampgo_Alpine02_maxfunevals()