fixed some issues

Author: thomasWeise

moptipy/algorithms/luby_restarts.py

@@ -28,12 +28,12 @@
 from moptipy.utils.logger import CSV_SEPARATOR, KeyValueLogSection
 
 
-@numba.njit(cache=True)
-def _luby(i: int) -> int:
+@numba.njit(cache=True, inline="always", fastmath=True, boundscheck=False)
+def luby(i: int) -> int:
     """
     Compute the Luby sequence.
 
-    >>> [_luby(ii) for ii in range(1, 65)]
+    >>> [luby(ii) for ii in range(1, 65)]
     [1, 1, 2, 1, 1, 2, 4, 1, 1, 2, 1, 1, 2, 4, 8, 1, 1, 2, 1, 1, 2, 4, 1, \
 1, 2, 1, 1, 2, 4, 8, 16, 1, 1, 2, 1, 1, 2, 4, 1, 1, 2, 1, 1, 2, 4, 8, \
 1, 1, 2, 1, 1, 2, 4, 1, 1, 2, 1, 1, 2, 4, 8, 16, 32, 1]
@@ -48,7 +48,8 @@ def _luby(i: int) -> int:
             return two_by_k_minus_one
         if i >= two_by_k:
             continue
-        return _luby((i - two_by_k_minus_one) + 1)
+        i = (i - two_by_k_minus_one) + 1
+        two_by_k = 1
 
 
 class __LubyAlgorithm(Algorithm):
@@ -98,7 +99,7 @@ def solve(self, process: Process) -> None:
                 restarts.append((process.get_consumed_fes(),
                                  process.get_consumed_time_millis()))
             index = index + 1
-            with for_fes(process, base * _luby(index)) as prc:
+            with for_fes(process, base * luby(index)) as prc:
                 als: Callable[[str, str], None] = prc.add_log_section
 
                 def __als(t: str, c: str, _a=als, _i=index) -> None:
@@ -151,7 +152,7 @@ def solve_mo(self, process: MOProcess) -> None:
                 restarts.append((process.get_consumed_fes(),
                                  process.get_consumed_time_millis()))
             index = index + 1
-            with for_fes(process, base * _luby(index)) as prc:
+            with for_fes(process, base * luby(index)) as prc:
                 als: Callable[[str, str], None] = prc.add_log_section
 
                 def __als(t: str, c: str, _a=als, _i=index) -> None:

moptipy/examples/bitstrings/labs.py

@@ -18,7 +18,7 @@
 
 `F(x) = n² / (n * E(X))`
 
-This problem is different than the other bit-string based problems, because we
+This problem is different from the other bit-string based problems, because we
 only know the optimal solutions for few, smaller instances. For larger
 instances, we only have lower bounds of the energy.
 

moptipy/operators/permutations/op1_swap2.py

@@ -46,7 +46,7 @@
 This operator performs one swap. It is similar to :class:`~moptipy.operators.\
 permutations.op1_swapn.Op1SwapN`, which performs a random number of swaps.
 """
-from typing import Callable, Final
+from typing import Final
 
 import numba  # type: ignore
 import numpy as np
@@ -56,8 +56,8 @@
 
 
 @numba.njit(cache=True, inline="always", fastmath=True, boundscheck=False)
-def swap_2(random: Generator, dest: np.ndarray,  # +book
-           x: np.ndarray) -> None:  # +book
+def swap_2(random: Generator, dest: np.ndarray,
+           x: np.ndarray) -> None:
     """
     Copy `x` into `dest` and swap two different values in `dest`.
 
@@ -87,12 +87,11 @@ def swap_2(random: Generator, dest: np.ndarray,  # +book
     # start book
     dest[:] = x[:]  # First, we copy `x` to `dest`.
     length: Final[int] = len(dest)  # Get the length of `dest`.
-    rint: Callable[[int, int], int] = random.integers  # fast call
 
-    i1: Final[int] = rint(0, length)  # first random index
+    i1: Final[int] = random.integers(0, length)  # first random index
     v1: Final = dest[i1]  # Get the value at the first index.
     while True:  # Repeat until we find a different value.
-        i2: int = rint(0, length)  # second random index
+        i2: int = random.integers(0, length)  # second random index
         v2 = dest[i2]  # Get the value at the second index.
         if v1 != v2:  # If both values different...
             dest[i2] = v1  # store v1 where v2 was

moptipy/version.py

@@ -2,4 +2,4 @@
 from typing import Final
 
 #: the version string of `moptipy`
-__version__: Final[str] = "0.9.143"
+__version__: Final[str] = "0.9.144"