Publish version 2.0.0a4

doc-sources/changelog.rst

@@ -4,14 +4,14 @@
 Changelog
 =========
 
-Version 2.0.0a4 (planned 2024-11-09)
-====================================
+Version 2.0.0a4 (2024-11-08)
+============================
 
 - **Changes behavior slightly** Optimize WPB model weights before evaluating and returning them
 - **Breaking** Add parameter ``weights_optimization_strategy`` to the ``ReinitializeLeastAccurate`` breeding strategy (required to fix previous point)
 - **Changes behavior slightly** Always keep the best model during WPB
 - Fix the ``universal2`` wheels for macOS to actually run on M1 Macs
-- **Changes behavior slightly** Upgrade OR-Tools from 8.2 to 9.11 (required for previous point)
+- **Changes behavior slightly** Upgrade OR-Tools from 8.2 to 9.11 on Linux and macOS (required for previous point)
 
 **Note** On Windows, the package still uses OR-Tools 8.2.
 

doc-sources/conceptual-overview/conceptual-overview.ipynb

@@ -21,7 +21,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "# Reproduction command (with lincs version 2.0.0a4.dev0): lincs classify problem.yml model.yml alternatives.csv\n",
+      "# Reproduction command (with lincs version 2.0.0a4): lincs classify problem.yml model.yml alternatives.csv\n",
       "name,Math,Physics,Literature,History,category\n",
       "A,1,1,1,1,\"Full scholarship\"\n",
       "B,1,1,1,0,\"Full scholarship\"\n",

doc-sources/get-started.rst

@@ -73,7 +73,7 @@ The generated ``problem.yml`` should look like:
 
 .. code:: yaml
 
-    # Reproduction command (with lincs version 2.0.0a4.dev0): lincs generate classification-problem 4 3 --random-seed 40
+    # Reproduction command (with lincs version 2.0.0a4): lincs generate classification-problem 4 3 --random-seed 40
     kind: classification-problem
     format_version: 1
     criteria:
@@ -144,7 +144,7 @@ It should look like:
 
 .. code:: yaml
 
-    # Reproduction command (with lincs version 2.0.0a4.dev0): lincs generate classification-model problem.yml --random-seed 41 --model-type mrsort
+    # Reproduction command (with lincs version 2.0.0a4): lincs generate classification-model problem.yml --random-seed 41 --model-type mrsort
     kind: ncs-classification-model
     format_version: 1
     accepted_values:
@@ -217,7 +217,7 @@ It should start with something like this, and contain 1000 alternatives:
 
 .. code:: text
 
-    # Reproduction command (with lincs version 2.0.0a4.dev0): lincs generate classified-alternatives problem.yml model.yml 1000 --random-seed 42 --misclassified-count 0
+    # Reproduction command (with lincs version 2.0.0a4): lincs generate classified-alternatives problem.yml model.yml 1000 --random-seed 42 --misclassified-count 0
     name,"Criterion 1","Criterion 2","Criterion 3","Criterion 4",category
     "Alternative 1",0.37454012,0.796543002,0.95071429,0.183434784,"Best category"
     "Alternative 2",0.731993914,0.779690981,0.598658502,0.596850157,"Intermediate category 1"
@@ -253,7 +253,7 @@ so it is numerically different:
 
 .. code:: yaml
 
-    # Reproduction command (with lincs version 2.0.0a4.dev0): lincs learn classification-model problem.yml learning-set.csv --model-type mrsort --mrsort.strategy weights-profiles-breed --mrsort.weights-profiles-breed.models-count 9 --mrsort.weights-profiles-breed.accuracy-heuristic.random-seed 43 --mrsort.weights-profiles-breed.initialization-strategy maximize-discrimination-per-criterion --mrsort.weights-profiles-breed.weights-strategy linear-program --mrsort.weights-profiles-breed.linear-program.solver glop --mrsort.weights-profiles-breed.profiles-strategy accuracy-heuristic --mrsort.weights-profiles-breed.accuracy-heuristic.processor cpu --mrsort.weights-profiles-breed.breed-strategy reinitialize-least-accurate --mrsort.weights-profiles-breed.reinitialize-least-accurate.portion 0.5 --mrsort.weights-profiles-breed.target-accuracy 1.0
+    # Reproduction command (with lincs version 2.0.0a4): lincs learn classification-model problem.yml learning-set.csv --model-type mrsort --mrsort.strategy weights-profiles-breed --mrsort.weights-profiles-breed.models-count 9 --mrsort.weights-profiles-breed.accuracy-heuristic.random-seed 43 --mrsort.weights-profiles-breed.initialization-strategy maximize-discrimination-per-criterion --mrsort.weights-profiles-breed.weights-strategy linear-program --mrsort.weights-profiles-breed.linear-program.solver glop --mrsort.weights-profiles-breed.profiles-strategy accuracy-heuristic --mrsort.weights-profiles-breed.accuracy-heuristic.processor cpu --mrsort.weights-profiles-breed.breed-strategy reinitialize-least-accurate --mrsort.weights-profiles-breed.reinitialize-least-accurate.portion 0.5 --mrsort.weights-profiles-breed.target-accuracy 1.0
     kind: ncs-classification-model
     format_version: 1
     accepted_values:

doc-sources/get-started/get-started.ipynb

@@ -48,7 +48,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "# Reproduction command (with lincs version 2.0.0a4.dev0): lincs generate classification-problem 4 3 --random-seed 40\n",
+      "# Reproduction command (with lincs version 2.0.0a4): lincs generate classification-problem 4 3 --random-seed 40\n",
       "kind: classification-problem\n",
       "format_version: 1\n",
       "criteria:\n",
@@ -126,7 +126,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "# Reproduction command (with lincs version 2.0.0a4.dev0): lincs generate classification-model problem.yml --random-seed 41 --model-type mrsort\n",
+      "# Reproduction command (with lincs version 2.0.0a4): lincs generate classification-model problem.yml --random-seed 41 --model-type mrsort\n",
       "kind: ncs-classification-model\n",
       "format_version: 1\n",
       "accepted_values:\n",
@@ -211,7 +211,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "# Reproduction command (with lincs version 2.0.0a4.dev0): lincs generate classified-alternatives problem.yml model.yml 1000 --random-seed 42 --misclassified-count 0\n",
+      "# Reproduction command (with lincs version 2.0.0a4): lincs generate classified-alternatives problem.yml model.yml 1000 --random-seed 42 --misclassified-count 0\n",
       "name,\"Criterion 1\",\"Criterion 2\",\"Criterion 3\",\"Criterion 4\",category\n",
       "\"Alternative 1\",0.37454012,0.796543002,0.95071429,0.183434784,\"Best category\"\n",
       "\"Alternative 2\",0.731993914,0.779690981,0.598658502,0.596850157,\"Intermediate category 1\"\n",
@@ -260,7 +260,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "# Reproduction command (with lincs version 2.0.0a4.dev0): lincs learn classification-model problem.yml learning-set.csv --model-type mrsort --mrsort.strategy weights-profiles-breed --mrsort.weights-profiles-breed.models-count 9 --mrsort.weights-profiles-breed.accuracy-heuristic.random-seed 43 --mrsort.weights-profiles-breed.initialization-strategy maximize-discrimination-per-criterion --mrsort.weights-profiles-breed.weights-strategy linear-program --mrsort.weights-profiles-breed.linear-program.solver glop --mrsort.weights-profiles-breed.profiles-strategy accuracy-heuristic --mrsort.weights-profiles-breed.accuracy-heuristic.processor cpu --mrsort.weights-profiles-breed.breed-strategy reinitialize-least-accurate --mrsort.weights-profiles-breed.reinitialize-least-accurate.portion 0.5 --mrsort.weights-profiles-breed.target-accuracy 1.0\n",
+      "# Reproduction command (with lincs version 2.0.0a4): lincs learn classification-model problem.yml learning-set.csv --model-type mrsort --mrsort.strategy weights-profiles-breed --mrsort.weights-profiles-breed.models-count 9 --mrsort.weights-profiles-breed.accuracy-heuristic.random-seed 43 --mrsort.weights-profiles-breed.initialization-strategy maximize-discrimination-per-criterion --mrsort.weights-profiles-breed.weights-strategy linear-program --mrsort.weights-profiles-breed.linear-program.solver glop --mrsort.weights-profiles-breed.profiles-strategy accuracy-heuristic --mrsort.weights-profiles-breed.accuracy-heuristic.processor cpu --mrsort.weights-profiles-breed.breed-strategy reinitialize-least-accurate --mrsort.weights-profiles-breed.reinitialize-least-accurate.portion 0.5 --mrsort.weights-profiles-breed.target-accuracy 1.0\n",
       "kind: ncs-classification-model\n",
       "format_version: 1\n",
       "accepted_values:\n",

doc-sources/user-guide.rst

@@ -512,7 +512,7 @@ They produce a different kind of model, with the sufficient coalitions specified
 
 .. code:: yaml
 
-    # Reproduction command (with lincs version 2.0.0a4.dev0): lincs learn classification-model problem.yml learning-set.csv --model-type ucncs --ucncs.strategy sat-by-coalitions
+    # Reproduction command (with lincs version 2.0.0a4): lincs learn classification-model problem.yml learning-set.csv --model-type ucncs --ucncs.strategy sat-by-coalitions
     kind: ncs-classification-model
     format_version: 1
     accepted_values:

doc-sources/user-guide/alglib-learning/alglib-learning.ipynb

@@ -27,7 +27,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "# Reproduction command (with lincs version 2.0.0a4.dev0): lincs learn classification-model problem.yml learning-set.csv --model-type mrsort --mrsort.strategy weights-profiles-breed --mrsort.weights-profiles-breed.models-count 9 --mrsort.weights-profiles-breed.accuracy-heuristic.random-seed 43 --mrsort.weights-profiles-breed.initialization-strategy maximize-discrimination-per-criterion --mrsort.weights-profiles-breed.weights-strategy linear-program --mrsort.weights-profiles-breed.linear-program.solver alglib --mrsort.weights-profiles-breed.profiles-strategy accuracy-heuristic --mrsort.weights-profiles-breed.accuracy-heuristic.processor cpu --mrsort.weights-profiles-breed.breed-strategy reinitialize-least-accurate --mrsort.weights-profiles-breed.reinitialize-least-accurate.portion 0.5 --mrsort.weights-profiles-breed.target-accuracy 1.0\n",
+      "# Reproduction command (with lincs version 2.0.0a4): lincs learn classification-model problem.yml learning-set.csv --model-type mrsort --mrsort.strategy weights-profiles-breed --mrsort.weights-profiles-breed.models-count 9 --mrsort.weights-profiles-breed.accuracy-heuristic.random-seed 43 --mrsort.weights-profiles-breed.initialization-strategy maximize-discrimination-per-criterion --mrsort.weights-profiles-breed.weights-strategy linear-program --mrsort.weights-profiles-breed.linear-program.solver alglib --mrsort.weights-profiles-breed.profiles-strategy accuracy-heuristic --mrsort.weights-profiles-breed.accuracy-heuristic.processor cpu --mrsort.weights-profiles-breed.breed-strategy reinitialize-least-accurate --mrsort.weights-profiles-breed.reinitialize-least-accurate.portion 0.5 --mrsort.weights-profiles-breed.target-accuracy 1.0\n",
       "kind: ncs-classification-model\n",
       "format_version: 1\n",
       "accepted_values:\n",

doc-sources/user-guide/gpu-learning/gpu-learning.ipynb

@@ -27,7 +27,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "# Reproduction command (with lincs version 2.0.0a4.dev0): lincs learn classification-model problem.yml learning-set.csv --model-type mrsort --mrsort.strategy weights-profiles-breed --mrsort.weights-profiles-breed.models-count 9 --mrsort.weights-profiles-breed.accuracy-heuristic.random-seed 43 --mrsort.weights-profiles-breed.initialization-strategy maximize-discrimination-per-criterion --mrsort.weights-profiles-breed.weights-strategy linear-program --mrsort.weights-profiles-breed.linear-program.solver glop --mrsort.weights-profiles-breed.profiles-strategy accuracy-heuristic --mrsort.weights-profiles-breed.accuracy-heuristic.processor gpu --mrsort.weights-profiles-breed.breed-strategy reinitialize-least-accurate --mrsort.weights-profiles-breed.reinitialize-least-accurate.portion 0.5 --mrsort.weights-profiles-breed.target-accuracy 1.0\n",
+      "# Reproduction command (with lincs version 2.0.0a4): lincs learn classification-model problem.yml learning-set.csv --model-type mrsort --mrsort.strategy weights-profiles-breed --mrsort.weights-profiles-breed.models-count 9 --mrsort.weights-profiles-breed.accuracy-heuristic.random-seed 43 --mrsort.weights-profiles-breed.initialization-strategy maximize-discrimination-per-criterion --mrsort.weights-profiles-breed.weights-strategy linear-program --mrsort.weights-profiles-breed.linear-program.solver glop --mrsort.weights-profiles-breed.profiles-strategy accuracy-heuristic --mrsort.weights-profiles-breed.accuracy-heuristic.processor gpu --mrsort.weights-profiles-breed.breed-strategy reinitialize-least-accurate --mrsort.weights-profiles-breed.reinitialize-least-accurate.portion 0.5 --mrsort.weights-profiles-breed.target-accuracy 1.0\n",
       "kind: ncs-classification-model\n",
       "format_version: 1\n",
       "accepted_values:\n",

doc-sources/user-guide/sat-learning/sat-learning.ipynb

@@ -22,7 +22,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "# Reproduction command (with lincs version 2.0.0a4.dev0): lincs learn classification-model problem.yml learning-set.csv --model-type ucncs --ucncs.strategy sat-by-coalitions\n",
+      "# Reproduction command (with lincs version 2.0.0a4): lincs learn classification-model problem.yml learning-set.csv --model-type ucncs --ucncs.strategy sat-by-coalitions\n",
       "kind: ncs-classification-model\n",
       "format_version: 1\n",
       "accepted_values:\n",
@@ -58,7 +58,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "# Reproduction command (with lincs version 2.0.0a4.dev0): lincs learn classification-model problem.yml learning-set.csv --model-type ucncs --ucncs.strategy max-sat-by-separation --ucncs.max-sat-by-separation.solver eval-max-sat --ucncs.max-sat-by-separation.eval-max-sat.nb-minimize-threads 0 --ucncs.max-sat-by-separation.eval-max-sat.timeout-fast-minimize 60 --ucncs.max-sat-by-separation.eval-max-sat.coef-minimize-time 2\n",
+      "# Reproduction command (with lincs version 2.0.0a4): lincs learn classification-model problem.yml learning-set.csv --model-type ucncs --ucncs.strategy max-sat-by-separation --ucncs.max-sat-by-separation.solver eval-max-sat --ucncs.max-sat-by-separation.eval-max-sat.nb-minimize-threads 0 --ucncs.max-sat-by-separation.eval-max-sat.timeout-fast-minimize 60 --ucncs.max-sat-by-separation.eval-max-sat.coef-minimize-time 2\n",
       "kind: ncs-classification-model\n",
       "format_version: 1\n",
       "accepted_values:\n",

doc-sources/user-guide/synthetic-data/synthetic-data.ipynb

@@ -14,7 +14,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "# Reproduction command (with lincs version 2.0.0a4.dev0): lincs generate classification-problem 4 3 --random-seed 57\n",
+      "# Reproduction command (with lincs version 2.0.0a4): lincs generate classification-problem 4 3 --random-seed 57\n",
       "kind: classification-problem\n",
       "format_version: 1\n",
       "criteria:\n",
@@ -63,7 +63,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "# Reproduction command (with lincs version 2.0.0a4.dev0): lincs generate classification-model problem.yml --random-seed 58 --model-type mrsort\n",
+      "# Reproduction command (with lincs version 2.0.0a4): lincs generate classification-model problem.yml --random-seed 58 --model-type mrsort\n",
       "kind: ncs-classification-model\n",
       "format_version: 1\n",
       "accepted_values:\n",
@@ -101,7 +101,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "# Reproduction command (with lincs version 2.0.0a4.dev0): lincs generate classified-alternatives problem.yml model.yml 100 --random-seed 59 --misclassified-count 0\n",
+      "# Reproduction command (with lincs version 2.0.0a4): lincs generate classified-alternatives problem.yml model.yml 100 --random-seed 59 --misclassified-count 0\n",
       "name,\"Criterion 1\",\"Criterion 2\",\"Criterion 3\",\"Criterion 4\",category\n",
       "\"Alternative 1\",0.924035132,0.804616809,0.157870576,0.637420833,\"Best category\"\n",
       "\"Alternative 2\",0.866915047,0.979161799,0.0841569453,0.397855282,\"Best category\"\n",
@@ -224,7 +224,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "# Reproduction command (with lincs version 2.0.0a4.dev0): lincs learn classification-model problem.yml learning-set.csv --model-type mrsort --mrsort.strategy weights-profiles-breed --mrsort.weights-profiles-breed.models-count 9 --mrsort.weights-profiles-breed.accuracy-heuristic.random-seed 60 --mrsort.weights-profiles-breed.initialization-strategy maximize-discrimination-per-criterion --mrsort.weights-profiles-breed.weights-strategy linear-program --mrsort.weights-profiles-breed.linear-program.solver glop --mrsort.weights-profiles-breed.profiles-strategy accuracy-heuristic --mrsort.weights-profiles-breed.accuracy-heuristic.processor cpu --mrsort.weights-profiles-breed.breed-strategy reinitialize-least-accurate --mrsort.weights-profiles-breed.reinitialize-least-accurate.portion 0.5 --mrsort.weights-profiles-breed.target-accuracy 1.0\n",
+      "# Reproduction command (with lincs version 2.0.0a4): lincs learn classification-model problem.yml learning-set.csv --model-type mrsort --mrsort.strategy weights-profiles-breed --mrsort.weights-profiles-breed.models-count 9 --mrsort.weights-profiles-breed.accuracy-heuristic.random-seed 60 --mrsort.weights-profiles-breed.initialization-strategy maximize-discrimination-per-criterion --mrsort.weights-profiles-breed.weights-strategy linear-program --mrsort.weights-profiles-breed.linear-program.solver glop --mrsort.weights-profiles-breed.profiles-strategy accuracy-heuristic --mrsort.weights-profiles-breed.accuracy-heuristic.processor cpu --mrsort.weights-profiles-breed.breed-strategy reinitialize-least-accurate --mrsort.weights-profiles-breed.reinitialize-least-accurate.portion 0.5 --mrsort.weights-profiles-breed.target-accuracy 1.0\n",
       "kind: ncs-classification-model\n",
       "format_version: 1\n",
       "accepted_values:\n",

docs/.buildinfo

@@ -1,4 +1,4 @@
 # Sphinx build info version 1
 # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
-config: cded3a427bff386c9945aacc676c5163
+config: b8b49b2c9835f2e65ccc23820533afe5
 tags: 645f666f9bcd5a90fca523b33c5a78b7

docs/README.html

@@ -5,11 +5,11 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="viewport" content="width=device-width, initial-scale=1" />
 
-    <title>Contributors &#8212; lincs 2.0.0a3 documentation</title>
+    <title>Contributors &#8212; lincs 2.0.0a4 documentation</title>
     <link rel="stylesheet" type="text/css" href="_static/pygments.css?v=4f649999" />
     <link rel="stylesheet" type="text/css" href="_static/alabaster.css?v=039e1c02" />
     <link rel="stylesheet" type="text/css" href="_static/graphviz.css?v=eafc0fe6" />
-    <script data-url_root="./" id="documentation_options" src="_static/documentation_options.js?v=50df3787"></script>
+    <script data-url_root="./" id="documentation_options" src="_static/documentation_options.js?v=9b56a74a"></script>
     <script src="_static/doctools.js?v=888ff710"></script>
     <script src="_static/sphinx_highlight.js?v=4825356b"></script>
     <link rel="index" title="Index" href="genindex.html" />