more coverage

tests/test_cost.py

@@ -621,6 +621,18 @@ def test_BinnedNLL_bad_input_6():
         BinnedNLL([[1]], [[1, 2], [3, 4]], lambda x, a: 0, use_pdf="numerical")
 
 
+def test_BinnedNLL_bad_input_7():
+    with pytest.raises(ValueError, match="xe must be iterable"):
+        BinnedNLL([0, 1], 0, lambda x, a: 0)
+
+
+def test_BinnedNLL_bad_input_8():
+    with pytest.raises(ValueError, match="use_pdf and grad cannot be used together"):
+        BinnedNLL(
+            [0, 1], [1, 2, 3], lambda x, a: 0, grad=lambda x, a: [1], use_pdf="numeric"
+        )
+
+
 def test_BinnedNLL_ndof_zero():
     c = BinnedNLL([1], [0, 1], lambda x, scale: expon_cdf(x, scale))
     m = Minuit(c, scale=1)

tests/test_minuit.py

@@ -1727,3 +1727,32 @@ def cost(a, b):
     # check that cost.errordef value is still overridden
     m.hesse()
     assert_allclose(m.errors, [2, 2])
+
+
+def test_mnprofile_bad_cost():
+    def fn(a, b):
+        if b > 0:
+            return a**2
+        return (a - 0.1) ** 2
+
+    m = Minuit(fn, 1, 2)
+    # test iterative fitting with custom precision
+    # m.precision = 1e-18
+    m.migrad()
+    with pytest.warns(IMinuitWarning, match="MIGRAD fails to converge"):
+        m.mnprofile("a")
+
+
+def test_migrad_iterative_with_precision():
+    def fn(a, b):
+        return 0
+
+    m1 = Minuit(fn, 1, 2)
+    m1.precision = 1e-7
+    m1.migrad(iterate=5)
+
+    m2 = Minuit(fn, 1, 2)
+    m2.precision = 1e-7
+    m2.migrad(iterate=1)
+
+    assert m2.fmin.nfcn < m1.fmin.nfcn