Publish version 1.1.0a6

doc-sources/changelog.rst

@@ -4,6 +4,23 @@
 Changelog
 =========
 
+Version 1.1.0a6 (2024-02-06)
+============================
+
+- **Breaking** Rename ``max_iteration_index`` to ``max_iterations_count`` in ``...TerminateAfterIterations.__init__``
+- Make the Python API guide Jupyter Notebook downloadable
+- Expose all attributes of ``WPB.LearningData``; start to document them in our Python API guide
+- Expose parameters of EvalMaxSAT in our API and command-line interface (see ``lincs learn classification-model --help``):
+
+    - ``--ucncs.max-sat-by-separation.solver`` (for consistency, always ``"eval-max-sat"`` for now)
+    - ``--ucncs.max-sat-by-separation.eval-max-sat.nb-minimize-threads``
+    - ``--ucncs.max-sat-by-separation.eval-max-sat.timeout-fast-minimize``
+    - ``--ucncs.max-sat-by-separation.eval-max-sat.coef-minimize-time``
+    - ``--ucncs.max-sat-by-coalitions.solver`` (for consistency, always ``"eval-max-sat"`` for now)
+    - ``--ucncs.max-sat-by-coalitions.eval-max-sat.nb-minimize-threads``
+    - ``--ucncs.max-sat-by-coalitions.eval-max-sat.timeout-fast-minimize``
+    - ``--ucncs.max-sat-by-coalitions.eval-max-sat.coef-minimize-time``
+
 Version 1.1.0a5 (2024-02-01)
 ============================
 

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

@@ -21,7 +21,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "# Reproduction command (with lincs version 1.1.0a6.dev0): lincs classify problem.yml model.yml alternatives.csv\n",
+      "# Reproduction command (with lincs version 1.1.0a6): 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

@@ -75,7 +75,7 @@ The generated ``problem.yml`` should look like:
 
 .. code:: yaml
 
-    # Reproduction command (with lincs version 1.1.0a6.dev0): lincs generate classification-problem 4 3 --random-seed 40
+    # Reproduction command (with lincs version 1.1.0a6): lincs generate classification-problem 4 3 --random-seed 40
     kind: classification-problem
     format_version: 1
     criteria:
@@ -146,7 +146,7 @@ It should look like:
 
 .. code:: yaml
 
-    # Reproduction command (with lincs version 1.1.0a6.dev0): lincs generate classification-model problem.yml --random-seed 41 --model-type mrsort
+    # Reproduction command (with lincs version 1.1.0a6): lincs generate classification-model problem.yml --random-seed 41 --model-type mrsort
     kind: ncs-classification-model
     format_version: 1
     accepted_values:
@@ -219,7 +219,7 @@ It should start with something like this, and contain 1000 alternatives:
 
 .. code:: text
 
-    # Reproduction command (with lincs version 1.1.0a6.dev0): lincs generate classified-alternatives problem.yml model.yml 1000 --random-seed 42 --misclassified-count 0
+    # Reproduction command (with lincs version 1.1.0a6): 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"
@@ -255,7 +255,7 @@ so it is numerically different:
 
 .. code:: yaml
 
-    # Reproduction command (with lincs version 1.1.0a6.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 1.1.0a6): 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 1.1.0a6.dev0): lincs generate classification-problem 4 3 --random-seed 40\n",
+      "# Reproduction command (with lincs version 1.1.0a6): 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 1.1.0a6.dev0): lincs generate classification-model problem.yml --random-seed 41 --model-type mrsort\n",
+      "# Reproduction command (with lincs version 1.1.0a6): 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 1.1.0a6.dev0): lincs generate classified-alternatives problem.yml model.yml 1000 --random-seed 42 --misclassified-count 0\n",
+      "# Reproduction command (with lincs version 1.1.0a6): 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 1.1.0a6.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 1.1.0a6): 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 1.1.0a6.dev0): lincs learn classification-model problem.yml learning-set.csv --model-type ucncs --ucncs.strategy sat-by-coalitions
+    # Reproduction command (with lincs version 1.1.0a6): 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 1.1.0a6.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 1.1.0a6): 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 1.1.0a6.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 1.1.0a6): 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 1.1.0a6.dev0): lincs learn classification-model problem.yml learning-set.csv --model-type ucncs --ucncs.strategy sat-by-coalitions\n",
+      "# Reproduction command (with lincs version 1.1.0a6): 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 1.1.0a6.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 1.1.0a6): 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 1.1.0a6.dev0): lincs generate classification-problem 4 3 --random-seed 57\n",
+      "# Reproduction command (with lincs version 1.1.0a6): 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 1.1.0a6.dev0): lincs generate classification-model problem.yml --random-seed 58 --model-type mrsort\n",
+      "# Reproduction command (with lincs version 1.1.0a6): 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 1.1.0a6.dev0): lincs generate classified-alternatives problem.yml model.yml 100 --random-seed 59 --misclassified-count 0\n",
+      "# Reproduction command (with lincs version 1.1.0a6): 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 1.1.0a6.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 1.1.0a6): 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: c3efb7cd4e9892bca8f9a10959dff7ff
+config: bf6a2a9ac0817ff6464d100acb2befb2
 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 1.1.0a5 documentation</title>
+    <title>Contributors &#8212; lincs 1.1.0a6 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=f2915547"></script>
+    <script data-url_root="./" id="documentation_options" src="_static/documentation_options.js?v=c569df2d"></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" />