Add tests to check merging of orders

Author: Radonirinaunimi

pineappl_py/tests/test_grid.py

@@ -600,6 +600,80 @@ def test_fix_convolution(
             expected_results,
         )
 
+    def test_fix_convolution_dis(self, fake_grids, pdf):
+        channels = [Channel([([i], 0.1)]) for i in range(-5, 5)]
+
+        g = fake_grids.grid_with_generic_convolution(
+            nb_convolutions=1,
+            channels=channels,
+            orders=ORDERS,
+            convolutions=[CONVOBJECT],
+        )
+
+        with pytest.raises(BaseException) as err_func:
+            g.fix_convolution(conv_idx=0, xfx=pdf.unpolarized_pdf)
+        assert "cannot fix the last convolution" in str(err_func.value)
+
+    def test_fix_convolution_wrong_index(self, fake_grids, pdf):
+        channels = [Channel([([i, -i], 0.1)]) for i in range(-5, 5)]
+
+        g = fake_grids.grid_with_generic_convolution(
+            nb_convolutions=2,
+            channels=channels,
+            orders=ORDERS,
+            convolutions=[CONVOBJECT, CONVOBJECT],
+        )
+
+        with pytest.raises(BaseException) as err_func:
+            g.fix_convolution(conv_idx=4, xfx=pdf.unpolarized_pdf)
+        assert "convolution index 4 out of bounds (max: 1)" in str(err_func.value)
+
+    def test_fix_convolution_logxia(self, fake_grids, pdf):
+        rndgen = Generator(PCG64(seed=1234))
+        binning = [1e-2, 1e-1, 0.5, 1]
+
+        channels = [Channel([([i, -i, i], 0.1)]) for i in range(-5, 5)]
+        orders = [Order(2, 0, 0, 0, 0), Order(2, 0, 0, 0, 1)]
+
+        convbools = [(False, False), (False, False), (False, True)]
+        hpids = [2212, 2212, 211]
+        convtypes = [ConvType(polarized=p, time_like=t) for p, t in convbools]
+        convolutions = [
+            Conv(convolution_types=c, pid=p) for c, p in zip(convtypes, hpids)
+        ]
+
+        g = fake_grids.grid_with_generic_convolution(
+            nb_convolutions=len(convolutions),
+            channels=channels,
+            orders=orders,
+            convolutions=convolutions,
+            bins=binning,
+        )
+
+        # Fill with non-empty subgrids
+        _q2grid = np.geomspace(1e3, 1e5, 5)
+        _xgrid = np.geomspace(1e-5, 1, 4)
+        comb_nodes = [_q2grid] + [_xgrid for _ in convolutions]
+        ntuples = [np.array(list(kins)) for kins in itertools.product(*comb_nodes)]
+        obs = [rndgen.uniform(binning[0], binning[-1]) for _ in ntuples]
+        for pto in range(len(ORDERS)):
+            for channel_id in range(len(channels)):
+                g.fill_array(
+                    order=pto,
+                    observables=obs,
+                    channel=channel_id,
+                    ntuples=ntuples,
+                    weights=np.repeat(1, len(obs)),
+                )
+
+        # Fix the Fragmentation Function
+        g_fix = g.fix_convolution(conv_idx=2, xfx=pdf.ff_set)
+        orders_fix = g_fix.orders()
+
+        # Check that the orders have been merged
+        assert len(orders_fix) == 1
+        assert orders_fix[0].as_tuple() == (2, 0, 0, 0, 0)
+
     def test_many_convolutions(self, fake_grids, pdf, nb_convolutions: int = 3):
         """Test for fun many convolutions."""
         expected_results = [