Upgrade to PineAPPL v1

.github/workflows/bench.yml

@@ -24,11 +24,11 @@ jobs:
           virtualenvs-create: false
           installer-parallel: true
       - name: Install dependencies
-        run: poetry install --no-interaction --no-root --with test
+        run: poetry install --no-interaction --no-root --with test -E nnpdf
       - name: Install project
         # it is required to repeat extras, otherwise they will be removed from
         # the environment
-        run: poetry install --no-interaction
+        run: poetry install --no-interaction -E nnpdf
       - name: Install task runner
         run: pip install poethepoet
       - name: Lint with pylint

benchmarks/bench_autosv.py

@@ -36,28 +36,32 @@ def benchmark_compute_ren_sv_grid(test_files, tmp_path, test_pdf, lhapdf_path):
     plusrensv_grid_path = tmp_path / name_grid
     with lhapdf_path(test_pdf):
         pdf = lhapdf.mkPDF(pdf_name)
+
     to_test_grid = pineappl.grid.Grid.read(to_test_grid_path)
     plusrensv_grid = pineappl.grid.Grid.read(plusrensv_grid_path)
-    sv_list = [(0.5, 1.0), (2.0, 1.0)]  # Only ren sv have to be tested
+    sv_list = [(0.5, 1.0, 1.0), (2.0, 1.0, 1.0)]  # Only μR have to be tested
     bin_number = to_test_grid.bins()
-    to_test_res = to_test_grid.convolve_with_one(
-        2212,
-        pdf.xfxQ2,
-        pdf.alphasQ2,
-        np.array([], dtype=bool),
-        np.array([], dtype=np.uint64),
-        np.array([], dtype=bool),
-        sv_list,
+
+    to_test_res = to_test_grid.convolve(
+        pdg_convs=to_test_grid.convolutions,
+        xfxs=[pdf.xfxQ2],
+        alphas=pdf.alphasQ2,
+        order_mask=np.array([], dtype=bool),
+        bin_indices=np.array([], dtype=np.uint64),
+        channel_mask=np.array([], dtype=bool),
+        xi=sv_list,
     ).reshape(bin_number, len(sv_list))
-    plusrensv_res = plusrensv_grid.convolve_with_one(
-        2212,
-        pdf.xfxQ2,
-        pdf.alphasQ2,
-        np.array([], dtype=bool),
-        np.array([], dtype=np.uint64),
-        np.array([], dtype=bool),
-        sv_list,
+
+    plusrensv_res = plusrensv_grid.convolve(
+        pdg_convs=plusrensv_grid.convolutions,
+        xfxs=[pdf.xfxQ2],
+        alphas=pdf.alphasQ2,
+        order_mask=np.array([], dtype=bool),
+        bin_indices=np.array([], dtype=np.uint64),
+        channel_mask=np.array([], dtype=bool),
+        xi=sv_list,
     ).reshape(bin_number, len(sv_list))
+
     rtol = 1.0e-14
     for sv in sv_list:
         for n_res, old_res in zip(

benchmarks/bench_cli.py

@@ -83,7 +83,8 @@ def benchmark_compare_cli(lhapdf_path, test_files, test_pdf):
             command,
             ["compare", str(fk_path), str(grid_path), "2", "0", "NNPDF40_nlo_as_01180"],
         )
-    assert "yll left" in result.output
+    assert "left" in result.output
+    assert "right" in result.output
 
 
 def benchmark_convolve_cli(test_files, tmp_path):

benchmarks/bench_comparator.py

@@ -1,3 +1,4 @@
+import numpy as np
 import pineappl
 
 import pineko
@@ -8,9 +9,9 @@ def benchmark_compare(lhapdf_path, test_files, test_pdf):
     grid = pineappl.grid.Grid.read(pine_path)
     fk_path = test_files / "data/fktables/208/LHCB_DY_13TEV_DIMUON.pineappl.lz4"
     fk = pineappl.fk_table.FkTable.read(fk_path)
-    pdf = "NNPDF40_nlo_as_01180"
+    pdfs = ["NNPDF40_nlo_as_01180"]
+    xi = (1.0, 1.0, 1.0)
     with lhapdf_path(test_pdf):
-        comp_table = pineko.comparator.compare(grid, fk, 2, 0, pdf, 1.0, 1.0)
+        comp_table = pineko.comparator.compare(grid, fk, 2, 0, pdfs, xi)
     errors = comp_table["permille_error"].values
-    assertions = [er < 5.0 for er in errors]
-    assert False not in assertions
+    assert np.all(errors < 5.0)

benchmarks/bench_evolve.py

@@ -112,19 +112,20 @@ def benchmark_evolve_grid(tmp_path, lhapdf_path, test_files, test_pdf):
     with eko.EKO.edit(eko_path) as eko_op:
         with lhapdf_path(test_pdf):
             pineko.evolve.evolve_grid(
-                pinegrid,
-                eko_op,
-                target_path,
-                max_as,
-                max_al,
-                1.0,
-                1.0,
+                grid=pinegrid,
+                operators=[eko_op],
+                fktable_path=target_path,
+                max_as=max_as,
+                max_al=max_al,
+                xir=1.0,
+                xif=1.0,
+                xia=1.0,
                 assumptions=assumptions,
-                comparison_pdf1="NNPDF40_nnlo_as_01180",
+                comparison_pdfs=["NNPDF40_nnlo_as_01180"],
             )
             # check metadata is there - fixes https://github.com/NNPDF/pineko/issues/70
             fk = pineappl.fk_table.FkTable.read(target_path)
-            kvs = fk.key_values()
+            kvs = fk.metadata
             assert "results_fk" in kvs
             assert "eko_theory_card" in kvs
             assert json.dumps(eko_op.theory_card.raw) == kvs["eko_theory_card"]

benchmarks/bench_kfactor.py

@@ -23,31 +23,31 @@ def benchmark_kfactor_inclusion(test_files, tmp_path, test_pdf, lhapdf_path):
     with lhapdf_path(test_pdf):
         pdf = lhapdf.mkPDF(pdf_name)
     pluskfactor_grid = pineappl.grid.Grid.read(pluskfactor_grid_path)
-    sv_list = [(1.0, 1.0)]  # Only ren sv have to be tested
+    sv_list = [(1.0, 1.0, 1.0)]  # Only ren sv have to be tested
     bin_number = pluskfactor_grid.bins()
-    order_mask_nloQCD = pineappl.grid.Order.create_mask(
-        pluskfactor_grid.orders(), 2, 0, True
+    order_mask_nloQCD = pineappl.boc.Order.create_mask(
+        orders=pluskfactor_grid.orders(), max_as=2, max_al=0, logs=True
     )
-    order_mask_nnloQCD = pineappl.grid.Order.create_mask(
-        pluskfactor_grid.orders(), 3, 0, True
+    order_mask_nnloQCD = pineappl.boc.Order.create_mask(
+        orders=pluskfactor_grid.orders(), max_as=3, max_al=0, logs=True
     )
-    to_test_res_nlo = pluskfactor_grid.convolve_with_one(
-        2212,
-        pdf.xfxQ2,
-        pdf.alphasQ2,
-        order_mask_nloQCD,
-        np.array([], dtype=np.uint64),
-        np.array([], dtype=bool),
-        sv_list,
+    to_test_res_nlo = pluskfactor_grid.convolve(
+        pdg_convs=pluskfactor_grid.convolutions,
+        xfxs=[pdf.xfxQ2],
+        alphas=pdf.alphasQ2,
+        order_mask=order_mask_nloQCD,
+        bin_indices=np.array([], dtype=np.uint64),
+        channel_mask=np.array([], dtype=bool),
+        xi=sv_list,
     ).reshape(bin_number, len(sv_list))
-    to_test_res_nnlo = pluskfactor_grid.convolve_with_one(
-        2212,
-        pdf.xfxQ2,
-        pdf.alphasQ2,
-        order_mask_nnloQCD,
-        np.array([], dtype=np.uint64),
-        np.array([], dtype=bool),
-        sv_list,
+    to_test_res_nnlo = pluskfactor_grid.convolve(
+        pdg_convs=pluskfactor_grid.convolutions,
+        xfxs=[pdf.xfxQ2],
+        alphas=pdf.alphasQ2,
+        order_mask=order_mask_nnloQCD,
+        bin_indices=np.array([], dtype=np.uint64),
+        channel_mask=np.array([], dtype=bool),
+        xi=sv_list,
     ).reshape(bin_number, len(sv_list))
     centrals_kfactor, _ = kfactor.read_from_file(
         test_files / "data" / "kfactors" / "CF_QCD_ATLAS_TTB_8TEV_LJ_TRAP.dat"

benchmarks/bench_regression.py

@@ -125,7 +125,7 @@ def benchmark_regression(tmp_path, dataset):
         fkt = FkTable.read(
             tmp_path / "data" / "fktables" / str(THEORYID) / f"{grid_name}.pineappl.lz4"
         )
-        result.append(fkt.convolve_with_one(2212, pdf.xfxQ2))
+        result.append(fkt.convolve(pdg_convs=fkt.convolutions, xfxs=[pdf.xfxQ2]))
     result = np.concatenate(result)
 
     if not regression_path.exists():

benchmarks/bench_theory.py

@@ -171,9 +171,9 @@ def benchmark_fk(test_files, test_configs):
     )
     theory_obj_hera.opcard(grid_name, pathlib.Path(test_files / grid_path), tcard)
 
-    theory_obj_hera.fk(grid_name, grid_path, tcard, pdf1=None, pdf2=None)
+    theory_obj_hera.fk(grid_name, grid_path, tcard, pdfs=None)
     # test overwrite function
-    theory_obj_hera.fk(grid_name, grid_path, tcard, pdf1=None, pdf2=None)
+    theory_obj_hera.fk(grid_name, grid_path, tcard, pdfs=None)
     log_path = pathlib.Path(test_files / "logs/fk/400-HERA_NC_225GEV_EP_SIGMARED.log")
     if os.path.exists(log_path):
         os.remove(log_path)