RC2 0.1.0

.readthedocs.yml

@@ -32,4 +32,6 @@ formats:
 # See https://docs.readthedocs.io/en/stable/guides/reproducible-builds.html
 python:
   install:
-    - requirements: docs/requirements.txt
+    - requirements: docs/requirements.txt
+    - method: pip
+      path: .

README.md

@@ -25,7 +25,7 @@ Here is a minimum working example in which a symmetric distances matrix is produ
 # Imports
 import numpy as np
 from scipy.spatial.distance import pdist, squareform
-from tspgrasp.grasp import Grasp
+from tspgrasp import Grasp
 ```
 
 ```python

docs/requirements.txt

@@ -1,9 +1,9 @@
 ipykernel
-sphinx
-sphinx_rtd_theme
-sphinxcontrib-bibtex
-pandoc
-numpydoc
-nbsphinx
-matplotlib
-urllib3==1.*
+sphinx==7.2.6
+sphinx_rtd_theme==1.3.0
+sphinxcontrib-bibtex==2.5.0
+pandoc==2.3
+numpydoc==1.6.0
+nbsphinx==0.9.3
+matplotlib==3.*
+urllib3==1.*

docs/source/api.rst

@@ -3,6 +3,8 @@
 tspgrasp
 ========
 
+The operators listed here are intended to be easily available for the user, so they can be imported directy from `tspgrap`.
+
 Grasp
 -----
 

docs/source/index.rst

@@ -42,7 +42,7 @@ Use
    # Imports
    import numpy as np
    from scipy.spatial.distance import pdist, squareform
-   from tspgrasp.grasp import Grasp
+   from tspgrasp import Grasp
 
    # Create distances matrix
    X = np.random.random((100, 2))

setup.py

@@ -16,7 +16,7 @@
     name = 'tspgrasp',
     package_dir={'': "src"},
     packages = find_packages(where='src'),
-    version = '0.1.0.rc1',
+    version = '0.1.0.rc2',
     license='Apache License 2.0',
     description = 'GRASP for TSP',
     long_description_content_type="text/markdown",

src/tspgrasp/base.py

@@ -68,7 +68,7 @@ def __call__(
             Maximum number of local search moves, by default 100000
 
         time_limit : float, optional
-            Time limit to interrupt the solution, by default float("inf")
+            Time limit (s) to interrupt the solution, by default float("inf")
 
         target : float, optional
             Taget value for objective which interrupts optimization process, by default -float("inf")

src/tspgrasp/environ.py

@@ -54,15 +54,19 @@ def __call__(self, D: np.ndarray) -> Solution:
 
 class SemiGreedy(tspconstr.SemiGreedy):
 
-    def __init__(self, seed: int = None):
-        """Greedy adaptive construction for the TSP inserting the next node at the end of the partial tour.
+    def __init__(self, alpha=(0.0, 1.0), seed=None):
+        """Greedy-randomized constructive heuristic for the TSP.
 
         Parameters
         ----------
+        alpha : tuple, optional
+            Alpha parameter - randomly generated at each iteration between range or fixed scalar.
+            Use values closer to one for a more greedy approach. By default (0.0, 1.0).
+
         seed : int, optional
             Random generator seed (differs behavior from cython to python), by default None
         """
-        super().__init__(seed)
+        super().__init__(alpha=alpha, seed=seed)
 
     def __call__(self, D: np.ndarray) -> Solution:
         """Solves a TSP based on a pairwise distances matrix.