Merge pull request #105 from NNPDF/feature/composite-output

Composite Output

benchmarks/eko/benchmark_evol_to_unity.py

@@ -7,7 +7,7 @@
 from eko.couplings import Couplings
 from eko.evolution_operator import Operator
 from eko.evolution_operator.grid import OperatorGrid
-from eko.interpolation import InterpolatorDispatcher
+from eko.interpolation import InterpolatorDispatcher, XGrid
 from eko.thresholds import ThresholdsAtlas
 
 # from eko.matching_conditions.operator_matrix_element import OperatorMatrixElement
@@ -43,24 +43,34 @@ class BenchmarkBackwardForward:
     operators_card = {
         "Q2grid": [10],
         # here you need a very dense grid
-        "interpolation_xgrid": np.linspace(1e-1, 1, 30),
-        # "interpolation_xgrid": make_grid(30,30, x_min=1e-3),
-        "interpolation_polynomial_degree": 1,
-        "interpolation_is_log": True,
-        "debug_skip_singlet": False,
-        "debug_skip_non_singlet": False,
-        "ev_op_max_order": 1,
-        "ev_op_iterations": 1,
-        "backward_inversion": "exact",
-        "n_integration_cores": 1,
+        "xgrid": np.linspace(1e-1, 1, 30),
+        # "xgrid": make_grid(30,30, x_min=1e-3),
+        "configs": {
+            "interpolation_polynomial_degree": 1,
+            "interpolation_is_log": True,
+            "ev_op_max_order": (2, 0),
+            "ev_op_iterations": 1,
+            "backward_inversion": "exact",
+            "n_integration_cores": 1,
+        },
+        "debug": {
+            "skip_singlet": False,
+            "skip_non_singlet": False,
+        },
     }
     new_theory, new_operators = compatibility.update(theory_card, operators_card)
     g = OperatorGrid.from_dict(
         new_theory,
         new_operators,
         ThresholdsAtlas.from_dict(new_theory),
         Couplings.from_dict(new_theory),
-        InterpolatorDispatcher.from_dict(new_operators),
+        InterpolatorDispatcher(
+            XGrid(
+                new_operators["xgrid"],
+                log=new_operators["configs"]["interpolation_is_log"],
+            ),
+            new_operators["configs"]["interpolation_polynomial_degree"],
+        ),
     )
 
     def test_operator_grid(
@@ -72,7 +82,13 @@ def test_operator_grid(
             self.new_operators,
             ThresholdsAtlas.from_dict(self.new_theory),
             Couplings.from_dict(self.new_theory),
-            InterpolatorDispatcher.from_dict(self.new_operators),
+            InterpolatorDispatcher(
+                XGrid(
+                    self.new_operators["xgrid"],
+                    log=self.new_operators["configs"]["interpolation_is_log"],
+                ),
+                self.new_operators["configs"]["interpolation_polynomial_degree"],
+            ),
         )
         q20 = 30
         q21 = 50

benchmarks/ekobox/benchmark_evol_pdf.py

@@ -1,18 +1,17 @@
 # -*- coding: utf-8 -*-
 import pathlib
 
-import lhapdf
 import numpy as np
 import pytest
 
 from eko import basis_rotation as br
-from eko import output
 from ekobox import evol_pdf as ev_p
-from ekobox import gen_op as g_o
-from ekobox import gen_theory as g_t
+from ekobox import operators_card as oc
+from ekobox import theory_card as tc
 from ekobox.genpdf import load
 
 test_pdf = pathlib.Path(__file__).parent / "fakepdf"
+lhapdf = pytest.importorskip("lhapdf")
 
 
 @pytest.mark.isolated
@@ -22,8 +21,8 @@ def benchmark_evolve_single_member(tmp_path, cd, lhapdf_path):
         100.0,
         10000.0,
     ]
-    op = g_o.gen_op_card(q2grid)
-    theory = g_t.gen_theory_card(
+    op = oc.generate(q2grid)
+    theory = tc.generate(
         0,
         5.0,
         update={
@@ -80,10 +79,10 @@ def benchmark_evolve_single_member(tmp_path, cd, lhapdf_path):
 
 @pytest.mark.isolated
 def benchmark_evolve_more_members(tmp_path, cd, lhapdf_path):
-    op = g_o.gen_op_card(
+    op = oc.generate(
         [10, 100], update={"interpolation_xgrid": [1e-7, 0.01, 0.1, 0.2, 0.3]}
     )
-    theory = g_t.gen_theory_card(0, 1.0)
+    theory = tc.generate(0, 1.0)
     with lhapdf_path(test_pdf):
         pdfs = lhapdf.mkPDFs("myMSTW2008nlo90cl")
     d = tmp_path / "sub"
@@ -102,28 +101,3 @@ def benchmark_evolve_more_members(tmp_path, cd, lhapdf_path):
         for x in [1e-7, 0.01, 0.1, 0.2, 0.3]:
             for pid in [21, 1, 2]:
                 assert new_pdf_1.xfxQ2(pid, x, Q2) != new_pdf_2.xfxQ2(pid, x, Q2)
-
-
-@pytest.mark.isolated
-def benchmark_gen_and_dump_out(tmp_path):
-    op = g_o.gen_op_card(
-        [100.0], update={"interpolation_xgrid": [1e-7, 0.01, 0.1, 0.2, 0.3]}
-    )
-    theory = g_t.gen_theory_card(0, 1.0)
-
-    out = ev_p.gen_out(theory, op, path=tmp_path)
-
-    ops_id = f"o{op['hash'][:6]}_t{theory['hash'][:6]}"
-    outpath = f"{tmp_path}/{ops_id}.tar"
-    loaded_out = output.Output.load_tar(outpath)
-    for el, load_el in zip(
-        out["interpolation_xgrid"], loaded_out["interpolation_xgrid"]
-    ):
-        assert el == load_el
-    for el, load_el in zip(
-        out["Q2grid"][100.0]["operators"], loaded_out["Q2grid"][100.0]["operators"]
-    ):
-        np.testing.assert_allclose(
-            out["Q2grid"][100.0]["operators"],
-            loaded_out["Q2grid"][100.0]["operators"],
-        )

benchmarks/ekobox/genpdf/benchmark_flavors.py

@@ -13,38 +13,6 @@
 lhapdf = pytest.importorskip("lhapdf")
 
 
-@pytest.mark.isolated
-def benchmark_is_evolution():
-    assert genpdf.flavors.is_evolution_labels(["V", "T3"])
-    assert not genpdf.flavors.is_evolution_labels(["21", "2"])
-
-
-@pytest.mark.isolated
-def benchmark_is_pids():
-    assert not genpdf.flavors.is_pid_labels(["V", "T3"])
-    assert not genpdf.flavors.is_pid_labels(["35", "9"])
-    assert not genpdf.flavors.is_pid_labels({})
-    assert genpdf.flavors.is_pid_labels([21, 2])
-
-
-@pytest.mark.isolated
-def benchmark_flavors_pid_to_flavor():
-    flavs = genpdf.flavors.pid_to_flavor([1, 2, 21, -3])
-    for f in flavs:
-        for g in flavs:
-            if not np.allclose(f, g):
-                assert f @ g == 0
-
-
-@pytest.mark.isolated
-def benchmark_flavors_evol_to_flavor():
-    flavs = genpdf.flavors.evol_to_flavor(["S", "g", "T3", "V8"])
-    for f in flavs:
-        for g in flavs:
-            if not np.allclose(f, g):
-                assert f @ g == 0
-
-
 @pytest.mark.isolated
 def benchmark_flavors_pids_ct14(tmp_path, cd):
     with cd(tmp_path):
@@ -101,59 +69,3 @@ def benchmark_flavors_evol_ct14(tmp_path, cd):
                     np.testing.assert_allclose(
                         pdf.xfxQ2(21, x, Q2), gonly.xfxQ2(21, x, Q2)
                     )
-
-
-@pytest.mark.isolated
-def benchmark_flavors_evol_raw():
-    blocks = [
-        {
-            "Q2grid": np.array([1, 2]),
-            "xgrid": np.array([0.1, 1.0]),
-            "pids": np.array([-1, 21, 1]),
-            "data": np.array([[0.1, 0.2, 0.1]] * 4),
-        }
-    ]
-    gonly = genpdf.flavors.project(blocks, genpdf.flavors.evol_to_flavor(["g"]))
-    assert len(gonly) == 1
-    np.testing.assert_allclose(
-        gonly[0]["data"],
-        np.array(
-            [[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.2, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]] * 4
-        ),
-    )
-    Sonly = genpdf.flavors.project(blocks, genpdf.flavors.evol_to_flavor(["S"]))
-    assert len(Sonly) == 1
-    for i in [0, 1, 2, 3]:
-        # g and gamma are zero
-        np.testing.assert_allclose(Sonly[0]["data"][i][7], 0)
-        np.testing.assert_allclose(Sonly[0]["data"][i][0], 0)
-        # quark are all equal and equal to anti-quarks
-        for pid in [2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13]:
-            np.testing.assert_allclose(Sonly[0]["data"][i][pid], Sonly[0]["data"][i][1])
-
-
-@pytest.mark.isolated
-def benchmark_flavors_evol_nodata():
-    # try with a block without data
-    blocks = [
-        {
-            "Q2grid": np.array([1, 2]),
-            "xgrid": np.array([0.1, 1.0]),
-            "pids": np.array([-1, 21, 1]),
-            "data": np.array([]),
-        },
-        {
-            "Q2grid": np.array([1, 2]),
-            "xgrid": np.array([0.1, 1.0]),
-            "pids": np.array([-1, 21, 1]),
-            "data": np.array([[0.1, 0.2, 0.1]] * 4),
-        },
-    ]
-    gonly = genpdf.flavors.project(blocks, genpdf.flavors.evol_to_flavor(["g"]))
-    assert len(gonly) == 2
-    np.testing.assert_allclose(
-        gonly[1]["data"],
-        np.array(
-            [[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.2, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]] * 4
-        ),
-    )

benchmarks/ekobox/genpdf/benchmark_init.py

@@ -14,32 +14,6 @@
 lhapdf = pytest.importorskip("lhapdf")
 
 
-@pytest.mark.isolated
-def benchmark_genpdf_exceptions(tmp_path, cd):
-    # using a wrong label and then a wrong parent pdf
-    with cd(tmp_path):
-        with pytest.raises(TypeError):
-            genpdf.generate_pdf(
-                "test_genpdf_exceptions1",
-                ["f"],
-                {
-                    21: lambda x, Q2: 3.0 * x * (1.0 - x),
-                    2: lambda x, Q2: 4.0 * x * (1.0 - x),
-                },
-            )
-        with pytest.raises(ValueError):
-            genpdf.generate_pdf(
-                "test_genpdf_exceptions2",
-                ["g"],
-                10,
-            )
-        with pytest.raises(FileExistsError):
-            genpdf.install_pdf("foo")
-
-        with pytest.raises(TypeError):
-            genpdf.generate_pdf("debug", [21], info_update=(10, 15, 20))
-
-
 @pytest.mark.isolated
 def benchmark_genpdf_no_parent_and_install(tmp_path, cd):
     with cd(tmp_path):

benchmarks/lha_paper_bench.py

@@ -224,8 +224,8 @@ def benchmark_sv(self, pto):
     obj = BenchmarkVFNS()
     # obj = BenchmarkFFNS()
 
-    # obj.benchmark_plain(0)
-    obj.benchmark_sv(2)
+    obj.benchmark_plain(0)
+    # obj.benchmark_sv(2)
 
     # # VFNS benchmarks with LHA settings
     # programs = ["LHA", "pegasus", "apfel"]

doc/source/code/IO.rst

@@ -199,7 +199,7 @@ The ``Q2grid`` values are the actual tensor for the requested :math:`Q^2`. Each
 - ``operators`` a :py:obj:`dict` with all evolution kernel operators where the key indicates which distribution is generated by which other one
   and the value represents the eko in matrix representation - this can either be the plain list representation or the binary representation
   (as provided by :py:meth:`numpy.ndarray.tobytes`)
-- ``operator_errors`` a :py:obj:`dict` with the integration errors associated to the respective operators following the same conventions as
+- ``errors`` a :py:obj:`dict` with the integration errors associated to the respective operators following the same conventions as
   the ``operator`` dictionary
 
 Each element (|EKO|) is a rank-4 tensor with the indices ordered in the following way: ``EKO[pid_out][x_out][pid_in][x_in]`` where ``pid_out`` and ``x_out``

doc/source/conf.py

@@ -103,6 +103,9 @@
 # The name of the Pygments (syntax highlighting) style to use.
 pygments_style = None
 
+# Criterion to sort class members
+autodoc_member_order = "bysource"
+
 # A string to be included at the beginning of all files
 shared = here / "shared"
 rst_prolog = "\n".join(