refactor threaded worker function

src/cubepy/integration.py

@@ -255,7 +255,7 @@ def tiled_rule(center, halfwidth, vol, evtidx):
         lens = np.roll(np.cumsum(np.array(list(map(lambda x: x.shape[1], c_sp))), 0), 1)
         lens[0] = 0
 
-        def tile_rule_worker(iter, c, h, v, e):
+        def rule_worker(iter, c, h, v, e):
             end = iter + c.shape[1]
             val, err, sub = rule(_f(e), c, h, v)
             value[:, iter:end] = val
@@ -267,7 +267,7 @@ def tile_rule_worker(iter, c, h, v, e):
         else:
             max_workers = parallel
         with ThreadPoolExecutor(max_workers=max_workers) as exec:
-            exec.map(tile_rule_worker, lens, c_sp, h_sp, v_sp, e_sp)
+            exec.map(rule_worker, lens, c_sp, h_sp, v_sp, e_sp)
 
         return value, error, split_dim
 

tests/test_models.py

@@ -69,15 +69,15 @@ def us_std_atm_density(z, earth_radius=6371):
         z = np.asarray(z)
 
         h = z * earth_radius / (z + earth_radius)
-        i = np.searchsorted(H_b, h, side="right") - 1
+        i = np.searchsorted(H_b, h, side="right") - 1  # <--!!
 
         deltah = h - H_b[i]
 
         temperature = T_b[i] + Lm_b[i] * deltah
 
         mask = Lm_b[i] == 0
         pressure = np.full(z.shape, P_b[i])
-        pressure[mask] *= np.exp(-gmr * deltah[mask] / T_b[i][mask])
+        pressure[mask] *= np.exp(-gmr * deltah[mask] / T_b[i][mask])  # <--!!
         pressure[~mask] *= (T_b[i][~mask] / temperature[~mask]) ** (
             gmr / Lm_b[i][~mask]
         )