fix new ruff UP031 errors

boxtree/bounding_box.py

@@ -39,8 +39,8 @@ def make_bounding_box_dtype(device, dimensions, coord_dtype):
         fields.append((f"max_{AXIS_NAMES[i]}", coord_dtype))
 
     dtype = np.dtype(fields)
-
-    name = "boxtree_bbox_%dd_%s_t" % (dimensions, get_type_moniker(coord_dtype))
+    type_moniker = get_type_moniker(coord_dtype)
+    name = f"boxtree_bbox_{dimensions}d_{type_moniker}_t"
 
     from pyopencl.tools import get_or_register_dtype, match_dtype_to_c_struct
     dtype, c_decl = match_dtype_to_c_struct(device, name, dtype)

boxtree/cost.py

@@ -151,7 +151,7 @@ def make_pde_aware_translation_cost_model(dim, nlevels):
     For example, this factory is used for complex Taylor and Fourier-Bessel
     expansions in 2D, and spherical harmonics (with point-and-shoot) in 3D.
     """
-    p_fmm = np.array([var("p_fmm_lev%d" % i) for i in range(nlevels)])
+    p_fmm = np.array([var(f"p_fmm_lev{i}") for i in range(nlevels)])
     ncoeffs_fmm = (p_fmm + 1) ** (dim - 1)
 
     uses_point_and_shoot = dim == 3
@@ -165,7 +165,7 @@ def make_taylor_translation_cost_model(dim, nlevels):
     """Create a cost model for FMM translation based on Taylor expansions
     in Cartesian coordinates.
     """
-    p_fmm = np.array([var("p_fmm_lev%d" % i) for i in range(nlevels)])
+    p_fmm = np.array([var(f"p_fmm_lev{i}") for i in range(nlevels)])
     ncoeffs_fmm = (p_fmm + 1) ** dim
 
     return FMMTranslationCostModel(
@@ -507,7 +507,7 @@ def cost_per_box(self, queue, traversal, level_to_order,
         result = self.zero_cost_per_box(queue, nboxes)
 
         for ilevel in range(tree.nlevels):
-            calibration_params["p_fmm_lev%d" % ilevel] = level_to_order[ilevel]
+            calibration_params[f"p_fmm_lev{ilevel}"] = level_to_order[ilevel]
 
         xlat_cost = self.translation_cost_model_factory(
             tree.dimensions, tree.nlevels
@@ -586,7 +586,7 @@ def cost_per_stage(self, queue, traversal, level_to_order,
         result = {}
 
         for ilevel in range(tree.nlevels):
-            calibration_params["p_fmm_lev%d" % ilevel] = level_to_order[ilevel]
+            calibration_params[f"p_fmm_lev{ilevel}"] = level_to_order[ilevel]
 
         xlat_cost = self.translation_cost_model_factory(
             tree.dimensions, tree.nlevels

boxtree/pyfmmlib_integration.py

@@ -1148,9 +1148,8 @@ def finalize_potentials(self, potential, template_ary):
             scale_factor = 1/(4*np.pi)
         else:
             raise NotImplementedError(
-                    "scale factor for pyfmmlib %s for %d dimensions" % (
-                        self.tree_indep.eqn_letter,
-                        self.dim))
+                    f"scale factor for pyfmmlib {self.tree_indep.eqn_letter} "
+                    f"for {self.dim} dimensions")
 
         if self.tree_indep.eqn_letter == "l" and self.dim == 2:
             potential = potential.real

boxtree/tools.py

@@ -392,7 +392,7 @@ def _to_host_device_array(attr):
 # {{{ type mangling
 
 def get_type_moniker(dtype):
-    return "%s%d" % (dtype.kind, dtype.itemsize)
+    return f"{dtype.kind}{dtype.itemsize}"
 
 # }}}
 

boxtree/traversal.py

@@ -2093,7 +2093,7 @@ def extract_level_start_box_nrs(box_list, wait_for):
         target_boxes_sep_smaller_by_source_level = []
 
         for ilevel in range(tree.nlevels):
-            fin_debug("finding separated smaller ('list 3 level %d')" % ilevel)
+            fin_debug(f"finding separated smaller ('list 3 level {ilevel}')")
 
             result, evt = knl_info.from_sep_smaller_builder(
                     *from_sep_smaller_base_args, ilevel,

boxtree/tree_build.py

@@ -1188,7 +1188,7 @@ def my_realloc_zeros_nocopy(ary, shape=nboxes_guess):
                         has_mismatch = True
 
                 assert not has_mismatch
-                print("LEVEL %d OK" % level)
+                print(f"LEVEL {level} OK")
 
                 # Cannot delete in Py 2.7: referred to from nested scope.
                 h_box_srcntgt_counts_cumul = None

boxtree/tree_build_kernels.py

@@ -152,10 +152,10 @@ def make_morton_bin_count_type(device, dimensions, particle_id_dtype,
     if srcntgts_have_extent:
         name_suffix = "_ext"
 
-    name = "boxtree_morton_bin_count_%dd_p%s%s_t" % (
-            dimensions,
-            get_type_moniker(particle_id_dtype),
-            name_suffix)
+    type_moniker = get_type_moniker(particle_id_dtype)
+    name = (
+        f"boxtree_morton_bin_count_{dimensions}d_p{type_moniker}{name_suffix}_t"
+    )
 
     from pyopencl.tools import get_or_register_dtype, match_dtype_to_c_struct
     dtype, c_decl = match_dtype_to_c_struct(device, name, dtype)

boxtree/visualization.py

@@ -37,7 +37,7 @@ def int_to_roman(inp):
     if inp == 0:
         return "Z"
     if not 0 < inp < 4000:
-        raise ValueError("Argument must be between 1 and 3999 (got %d)" % inp)
+        raise ValueError(f"Argument must be between 1 and 3999 (got {inp})")
     ints = (1000, 900, 500, 400, 100, 90, 50, 40, 10, 9, 5, 4, 1)
     nums = ("M", "CM", "D", "CD", "C", "XC", "L", "XL", "X", "IX", "V", "IV", "I")
     result = ""
@@ -130,26 +130,28 @@ def get_tikz_for_tree(self):
 
         lines = []
 
-        lines.append(r"\def\nboxes{%d}" % self.tree.nboxes)
-        lines.append(r"\def\lastboxnr{%d}" % (self.tree.nboxes-1))
+        lines.append(r"\def\nboxes{%d}" % self.tree.nboxes)  # noqa: UP031
+        lines.append(r"\def\lastboxnr{%d}" % (self.tree.nboxes-1))  # noqa: UP031
         for ibox in range(self.tree.nboxes):
             el, eh = self.tree.get_box_extent(ibox)
+            el_0, el_1 = float(el[0]), float(el[1])
+            eh_0, eh_1 = float(eh[0]), float(eh[1])
 
             c = self.tree.box_centers[:, ibox]
+            c_0, c_1 = float(c[0]), float(c[1])
 
             lines.append(
-                    r"\coordinate (boxl%d) at (%r, %r);"
-                    % (ibox, float(el[0]), float(el[1])))
+                fr"\coordinate (boxl{ibox}) at ({el_0!r}, {el_1!r});")
             lines.append(
-                    r"\coordinate (boxh%d) at (%r, %r);"
-                    % (ibox, float(eh[0]), float(eh[1])))
+                fr"\coordinate (boxh{ibox}) at ({eh_0!r}, {eh_1!r});")
             lines.append(
-                    r"\coordinate (boxc%d) at (%r, %r);"
-                    % (ibox, float(c[0]), float(c[1])))
+                fr"\coordinate (boxc{ibox}) at ({c_0!r}, {c_1!r});")
             lines.append(
-                    rf"\def\boxsize{int_to_roman(ibox)}{{{float(eh[0]-el[0])!r}}}")
+                r"\def\boxsize%s{%r}" % (int_to_roman(ibox), eh_0 - el_0)   # noqa: UP031
+                )
             lines.append(
-                    rf"\def\boxlevel{int_to_roman(ibox)}{{{self.tree.box_levels[ibox]!r}}}")
+                r"\dev\boxlevel%s{%r}" % (int_to_roman(ibox),               # noqa: UP031
+                                          self.tree.box_levels[ibox]))
 
         lines.append(
                 r"\def\boxpath#1{(boxl#1) rectangle (boxh#1)}")

test/test_cost_model.py

@@ -95,7 +95,7 @@ def test_compare_cl_and_py_cost_model(actx_factory, nsources, ntargets, dims, dt
 
     constant_one_params = cl_cost_model.get_unit_calibration_params().copy()
     for ilevel in range(trav.tree.nlevels):
-        constant_one_params["p_fmm_lev%d" % ilevel] = 10
+        constant_one_params[f"p_fmm_lev{ilevel}"] = 10
 
     xlat_cost = make_pde_aware_translation_cost_model(dims, trav.tree.nlevels)
 

test/test_fmm.py

@@ -59,13 +59,12 @@ def get_fmmlib_ref_pot(wrangler, weights, sources_host, targets_host,
     use_dipoles = dipole_vec is not None
 
     import pyfmmlib
+
+    name = "fld" if dims == 3 else "grad"
+    dp = "_dp" if use_dipoles else ""
     fmmlib_routine = getattr(
             pyfmmlib,
-            "%spot%s%ddall%s_vec" % (
-                eqn_letter,
-                "fld" if dims == 3 else "grad",
-                dims,
-                "_dp" if use_dipoles else ""))
+            f"{eqn_letter}pot{name}{dims}dall{dp}_vec")
 
     kwargs = {}
     if dims == 3:

test/test_tree.py

@@ -431,7 +431,7 @@ def test_source_target_tree(actx_factory, dims, visualize=False):
                 pt.show()
 
             if not all_good_here:
-                print("BAD BOX %s %d" % (what, ibox))
+                print(f"BAD BOX {what} {ibox}")
 
             all_good_so_far = all_good_so_far and all_good_here
 
@@ -624,8 +624,7 @@ def test_extent_tree(actx_factory, dims, extent_norm, visualize=False):
             all_good_here = np.all(good)
 
             if not all_good_here:
-                print("BAD BOX %s %d level %d"
-                        % (what, ibox, tree.box_levels[ibox]))
+                print(f"BAD BOX {what} {ibox} level {tree.box_levels[ibox]}")
 
             all_good_so_far = all_good_so_far and all_good_here
             assert all_good_here