ENH: Expectation-Maximization Algorithm

[VincentAuriau]

No description provided.

[github-actions]

Coverage Report for Python 3.9

File	Stmts	Miss	Cover	Missing
choice_learn
__init__.py	2	0	100%
tf_ops.py	48	0	100%
choice_learn/data
__init__.py	3	0	100%
choice_dataset.py	647	33	95%	198, 250, 283, 421, 463–464, 589, 724, 738, 840, 842, 937, 957–961, 1140, 1159–1161, 1174–1176, 1204, 1209, 1218, 1235, 1276, 1288, 1302, 1341, 1356, 1361, 1390, 1403, 1438–1439
indexer.py	237	22	91%	20, 31, 45, 60–67, 202–204, 219–230, 265, 291
storage.py	161	6	96%	22, 33, 51, 56, 61, 71
store.py	72	72	0%	3–275
choice_learn/datasets
__init__.py	4	0	100%
base.py	389	214	45%	40–41, 63–70, 92–98, 120, 144–156, 226, 232–261, 266–335, 350–399, 414–446, 455–522, 609–621, 624–627, 630, 637–648, 652–665, 674–700, 708, 714, 781, 868, 913, 962, 1047, 1132
expedia.py	102	92	10%	27–301
tafeng.py	49	1	98%	50
choice_learn/datasets/data
__init__.py	0	0	100%
choice_learn/models
__init__.py	14	2	86%	15–16
base_model.py	254	12	95%	144, 186, 283, 302, 342, 349, 378, 397, 428–429, 438–439
baseline_models.py	49	0	100%
conditional_logit.py	236	21	91%	46, 49, 51, 82, 85, 88–92, 95–99, 133, 298, 335, 392, 467–473, 598, 632, 739, 743
latent_class_base_model.py	293	96	67%	55–61, 257–258, 271–277, 283, 320–325, 492–495, 600, 618–660, 667, 696, 710, 715, 723–751, 778–802, 805–831, 857–864, 885–905, 922–937, 971
latent_class_mnl.py	62	6	90%	257–261, 296
learning_mnl.py	67	3	96%	157, 182, 188
nested_logit.py	291	12	96%	55, 77, 160, 269, 351, 484, 530, 600, 679, 848, 900, 904
reslogit.py	132	11	92%	28, 30, 32, 34, 36, 285, 360, 369, 374, 382, 432
rumnet.py	236	3	99%	748–751, 982
simple_mnl.py	139	6	96%	167, 275, 347, 355, 357, 359
tastenet.py	94	56	40%	15, 64, 90–104, 140–142, 177–207, 223, 238–254, 273–289
choice_learn/toolbox
__init__.py	0	0	100%
assortment_optimizer.py	27	27	0%	4–180
gurobi_opt.py	236	236	0%	3–675
or_tools_opt.py	226	226	0%	3–666
TOTAL	4070	1157	72%

Tests	Skipped	Failures	Errors	Time
116	0 💤	0 ❌	0 🔥	4m 14s ⏱️

[github-actions]

Coverage Report for Python 3.10

File	Stmts	Miss	Cover	Missing
choice_learn
__init__.py	2	0	100%
tf_ops.py	48	0	100%
choice_learn/data
__init__.py	3	0	100%
choice_dataset.py	647	33	95%	198, 250, 283, 421, 463–464, 589, 724, 738, 840, 842, 937, 957–961, 1140, 1159–1161, 1174–1176, 1204, 1209, 1218, 1235, 1276, 1288, 1302, 1341, 1356, 1361, 1390, 1403, 1438–1439
indexer.py	237	22	91%	20, 31, 45, 60–67, 202–204, 219–230, 265, 291
storage.py	161	6	96%	22, 33, 51, 56, 61, 71
store.py	72	72	0%	3–275
choice_learn/datasets
__init__.py	4	0	100%
base.py	389	213	45%	38, 63–70, 92–98, 120, 144–156, 226, 232–261, 266–335, 350–399, 414–446, 455–522, 609–621, 624–627, 630, 637–648, 652–665, 674–700, 708, 714, 781, 868, 913, 962, 1047, 1132
expedia.py	102	92	10%	27–301
tafeng.py	49	1	98%	50
choice_learn/datasets/data
__init__.py	0	0	100%
choice_learn/models
__init__.py	14	2	86%	15–16
base_model.py	254	12	95%	144, 186, 283, 302, 342, 349, 378, 397, 428–429, 438–439
baseline_models.py	49	0	100%
conditional_logit.py	236	21	91%	46, 49, 51, 82, 85, 88–92, 95–99, 133, 298, 335, 392, 467–473, 598, 632, 739, 743
latent_class_base_model.py	293	96	67%	55–61, 257–258, 271–277, 283, 320–325, 492–495, 600, 618–660, 667, 696, 710, 715, 723–751, 778–802, 805–831, 857–864, 885–905, 922–937, 971
latent_class_mnl.py	62	6	90%	257–261, 296
learning_mnl.py	67	3	96%	157, 182, 188
nested_logit.py	291	12	96%	55, 77, 160, 269, 351, 484, 530, 600, 679, 848, 900, 904
reslogit.py	132	11	92%	28, 30, 32, 34, 36, 285, 360, 369, 374, 382, 432
rumnet.py	236	3	99%	748–751, 982
simple_mnl.py	139	6	96%	167, 275, 347, 355, 357, 359
tastenet.py	94	56	40%	15, 64, 90–104, 140–142, 177–207, 223, 238–254, 273–289
choice_learn/toolbox
__init__.py	0	0	100%
assortment_optimizer.py	27	27	0%	4–180
gurobi_opt.py	238	238	0%	3–675
or_tools_opt.py	226	226	0%	3–666
TOTAL	4072	1158	72%

Tests	Skipped	Failures	Errors	Time
116	0 💤	0 ❌	0 🔥	4m 17s ⏱️

[github-actions]

Coverage Report for Python 3.11

File	Stmts	Miss	Cover	Missing
choice_learn
__init__.py	2	0	100%
tf_ops.py	48	0	100%
choice_learn/data
__init__.py	3	0	100%
choice_dataset.py	647	33	95%	198, 250, 283, 421, 463–464, 589, 724, 738, 840, 842, 937, 957–961, 1140, 1159–1161, 1174–1176, 1204, 1209, 1218, 1235, 1276, 1288, 1302, 1341, 1356, 1361, 1390, 1403, 1438–1439
indexer.py	237	22	91%	20, 31, 45, 60–67, 202–204, 219–230, 265, 291
storage.py	161	6	96%	22, 33, 51, 56, 61, 71
store.py	72	72	0%	3–275
choice_learn/datasets
__init__.py	4	0	100%
base.py	389	213	45%	38, 63–70, 92–98, 120, 144–156, 226, 232–261, 266–335, 350–399, 414–446, 455–522, 609–621, 624–627, 630, 637–648, 652–665, 674–700, 708, 714, 781, 868, 913, 962, 1047, 1132
expedia.py	102	92	10%	27–301
tafeng.py	49	1	98%	50
choice_learn/datasets/data
__init__.py	0	0	100%
choice_learn/models
__init__.py	14	2	86%	15–16
base_model.py	254	12	95%	144, 186, 283, 302, 342, 349, 378, 397, 428–429, 438–439
baseline_models.py	49	0	100%
conditional_logit.py	236	21	91%	46, 49, 51, 82, 85, 88–92, 95–99, 133, 298, 335, 392, 467–473, 598, 632, 739, 743
latent_class_base_model.py	293	96	67%	55–61, 257–258, 271–277, 283, 320–325, 492–495, 600, 618–660, 667, 696, 710, 715, 723–751, 778–802, 805–831, 857–864, 885–905, 922–937, 971
latent_class_mnl.py	62	6	90%	257–261, 296
learning_mnl.py	67	3	96%	157, 182, 188
nested_logit.py	291	12	96%	55, 77, 160, 269, 351, 484, 530, 600, 679, 848, 900, 904
reslogit.py	132	11	92%	28, 30, 32, 34, 36, 285, 360, 369, 374, 382, 432
rumnet.py	236	3	99%	748–751, 982
simple_mnl.py	139	6	96%	167, 275, 347, 355, 357, 359
tastenet.py	94	56	40%	15, 64, 90–104, 140–142, 177–207, 223, 238–254, 273–289
choice_learn/toolbox
__init__.py	0	0	100%
assortment_optimizer.py	27	27	0%	4–180
gurobi_opt.py	238	238	0%	3–675
or_tools_opt.py	226	226	0%	3–666
TOTAL	4072	1158	72%

Tests	Skipped	Failures	Errors	Time
116	0 💤	0 ❌	0 🔥	4m 42s ⏱️

[github-actions]

Coverage Report for Python 3.12

File	Stmts	Miss	Cover	Missing
choice_learn
__init__.py	2	0	100%
tf_ops.py	48	0	100%
choice_learn/data
__init__.py	3	0	100%
choice_dataset.py	647	33	95%	198, 250, 283, 421, 463–464, 589, 724, 738, 840, 842, 937, 957–961, 1140, 1159–1161, 1174–1176, 1204, 1209, 1218, 1235, 1276, 1288, 1302, 1341, 1356, 1361, 1390, 1403, 1438–1439
indexer.py	237	22	91%	20, 31, 45, 60–67, 202–204, 219–230, 265, 291
storage.py	161	6	96%	22, 33, 51, 56, 61, 71
store.py	72	72	0%	3–275
choice_learn/datasets
__init__.py	4	0	100%
base.py	389	213	45%	38, 63–70, 92–98, 120, 144–156, 226, 232–261, 266–335, 350–399, 414–446, 455–522, 609–621, 624–627, 630, 637–648, 652–665, 674–700, 708, 714, 781, 868, 913, 962, 1047, 1132
expedia.py	102	92	10%	27–301
tafeng.py	49	1	98%	50
choice_learn/datasets/data
__init__.py	0	0	100%
choice_learn/models
__init__.py	14	2	86%	15–16
base_model.py	254	12	95%	144, 186, 283, 302, 342, 349, 378, 397, 428–429, 438–439
baseline_models.py	49	0	100%
conditional_logit.py	236	21	91%	46, 49, 51, 82, 85, 88–92, 95–99, 133, 298, 335, 392, 467–473, 598, 632, 739, 743
latent_class_base_model.py	293	96	67%	55–61, 257–258, 271–277, 283, 320–325, 492–495, 600, 618–660, 667, 696, 710, 715, 723–751, 778–802, 805–831, 857–864, 885–905, 922–937, 971
latent_class_mnl.py	62	6	90%	257–261, 296
learning_mnl.py	67	3	96%	157, 182, 188
nested_logit.py	291	12	96%	55, 77, 160, 269, 351, 484, 530, 600, 679, 848, 900, 904
reslogit.py	132	11	92%	28, 30, 32, 34, 36, 285, 360, 369, 374, 382, 432
rumnet.py	236	3	99%	748–751, 982
simple_mnl.py	139	6	96%	167, 275, 347, 355, 357, 359
tastenet.py	94	56	40%	15, 64, 90–104, 140–142, 177–207, 223, 238–254, 273–289
choice_learn/toolbox
__init__.py	0	0	100%
assortment_optimizer.py	27	27	0%	4–180
gurobi_opt.py	238	238	0%	3–675
or_tools_opt.py	226	226	0%	3–666
TOTAL	4072	1158	72%

Tests	Skipped	Failures	Errors	Time
116	0 💤	0 ❌	0 🔥	5m 29s ⏱️