Exposes more Python methods for pineko

pineappl_py/src/fk_table.rs

@@ -89,6 +89,22 @@ impl PyFkTable {
         Ok(self.fk_table.table().into_pyarray_bound(py))
     }
 
+    /// Get the type(s) of convolution(s) for the current FK table.
+    ///
+    /// Returns
+    /// list(PyConv):
+    ///     list of convolution type with the corresponding PIDs
+    #[getter]
+    #[must_use]
+    pub fn convolutions(&self) -> Vec<PyConv> {
+        self.fk_table
+            .grid()
+            .convolutions()
+            .iter()
+            .map(|conv| PyConv { conv: conv.clone() })
+            .collect()
+    }
+
     /// Get number of bins.
     ///
     /// Returns

pineappl_py/src/grid.rs

@@ -641,6 +641,7 @@ impl PyGrid {
     /// Returns
     /// list(PyConv):
     ///     list of convolution type with the corresponding PIDs
+    #[getter]
     #[must_use]
     pub fn convolutions(&self) -> Vec<PyConv> {
         self.grid
@@ -721,6 +722,5 @@ pub fn register(parent_module: &Bound<'_, PyModule>) -> PyResult<()> {
         "import sys; sys.modules['pineappl.grid'] = m"
     );
     m.add_class::<PyGrid>()?;
-    m.add_class::<PyOrder>()?;
     parent_module.add_submodule(&m)
 }

pineappl_py/tests/conftest.py

@@ -3,9 +3,9 @@
 import subprocess
 from typing import List
 
-from pineappl.boc import Channel, Kinematics, ScaleFuncForm, Scales
+from pineappl.boc import Channel, Kinematics, ScaleFuncForm, Scales, Order
 from pineappl.convolutions import Conv
-from pineappl.grid import Grid, Order
+from pineappl.grid import Grid
 from pineappl.interpolation import (
     Interp,
     InterpolationMethod,

pineappl_py/tests/test_bin.py

@@ -1,10 +1,9 @@
 import numpy as np
 import pytest
 
-from pineappl.boc import Channel
+from pineappl.boc import Channel, Order
 from pineappl.bin import BinRemapper
 from pineappl.convolutions import Conv, ConvType
-from pineappl.grid import Order
 
 
 class TestBinRemapper:
@@ -38,7 +37,9 @@ def test_binremapper(self, fake_grids):
         bin_dims = g.bin_dimensions()
         bin_limits = [
             (left, right)
-            for left, right in zip(g.bin_left(bin_dims - 1), g.bin_right(bin_dims - 1))
+            for left, right in zip(
+                g.bin_left(bin_dims - 1), g.bin_right(bin_dims - 1)
+            )
         ]
         normalizations = [10.0 for _ in g.bin_normalizations()]
 

pineappl_py/tests/test_fk_table.py

@@ -7,10 +7,9 @@
 import numpy as np
 import tempfile
 
-from pineappl.boc import Channel
+from pineappl.boc import Channel, Order
 from pineappl.convolutions import Conv, ConvType
 from pineappl.fk_table import FkAssumptions, FkTable
-from pineappl.grid import Order
 from pineappl.import_subgrid import ImportSubgridV1
 
 
@@ -147,6 +146,14 @@ def test_polarized_convolution(
         fk_table = download_objects(f"{fkname}")
         fk = FkTable.read(fk_table)
 
+        # Check the FK table convolutions
+        convolutions = fk.convolutions
+        assert len(convolutions) == 2
+        assert convolutions[0].conv_type.polarized
+        assert not convolutions[0].conv_type.time_like
+        assert not convolutions[1].conv_type.polarized
+        assert not convolutions[1].conv_type.time_like
+
         # Convolution object of the 1st hadron - Polarized
         h1 = ConvType(polarized=True, time_like=False)
         h1_conv = Conv(conv_type=h1, pid=2212)

pineappl_py/tests/test_grid.py

@@ -6,11 +6,11 @@
 from numpy.random import Generator, PCG64
 
 from pineappl.bin import BinRemapper
-from pineappl.boc import Channel, Kinematics, Scales
+from pineappl.boc import Channel, Kinematics, Scales, Order
 from pineappl.convolutions import Conv, ConvType
 from pineappl.evolution import OperatorSliceInfo
 from pineappl.fk_table import FkTable
-from pineappl.grid import Grid, Order
+from pineappl.grid import Grid
 from pineappl.import_subgrid import ImportSubgridV1
 from pineappl.pids import PidBasis
 
@@ -221,7 +221,7 @@ def test_grid(
         g = Grid.read(grid)
 
         # Get the types of convolutions for this grid
-        for conv in g.convolutions():
+        for conv in g.convolutions:
             assert isinstance(conv, Conv)
 
         # Check that the scalings work, ie run without error
@@ -334,7 +334,7 @@ def test_polarized_convolution(
         g = Grid.read(grid)
 
         # Check the Grid convolutions - can be used to construct `grid.convolve`
-        convolutions = g.convolutions()
+        convolutions = g.convolutions
         assert len(convolutions) == 2
         assert convolutions[0].conv_type.polarized
         assert not convolutions[0].conv_type.time_like