mirror of
https://github.com/deunix-educ/aventuriers-des-mots.git
synced 2026-10-13 02:11:58 +02:00
Denis Defolie
109 lines
5.0 KiB
GDScript
109 lines
5.0 KiB
GDScript
extends GutTest
|
|
## Coherence des « tableaux » (data/curriculum/) avec le reste des donnees.
|
|
|
|
|
|
func test_school_levels_match_the_schemas() -> void:
|
|
for schema_name in ["save", "rule", "curriculum", "dictation", "exercise_multiple_choice"]:
|
|
var schema := DataLoader.load_schema(schema_name)
|
|
var enum_values: Array = []
|
|
if schema_name == "save":
|
|
enum_values = schema["properties"]["school_level"]["enum"]
|
|
else:
|
|
enum_values = schema["properties"]["level"]["enum"]
|
|
assert_eq(enum_values, SchoolLevels.ALL as Array, "schema %s" % schema_name)
|
|
|
|
|
|
func test_backdrop_enum_matches_available_art() -> void:
|
|
var schema := DataLoader.load_schema("curriculum")
|
|
var enum_values: Array = schema["properties"]["backdrop"]["enum"]
|
|
var kinds: Array = BackdropKinds.kinds()
|
|
enum_values.sort()
|
|
kinds.sort()
|
|
assert_eq(enum_values, kinds)
|
|
for kind in BackdropKinds.kinds():
|
|
assert_true(
|
|
ResourceLoader.exists(BackdropKinds.TEXTURES[kind]), "decor manquant : %s" % kind
|
|
)
|
|
assert_true(SoundCatalog.MUSIC_IDS.has(BackdropKinds.music_for(kind)))
|
|
|
|
|
|
func test_every_rule_belongs_to_exactly_one_region_of_its_level() -> void:
|
|
var owners := {}
|
|
for level in SchoolLevels.ALL:
|
|
for region in ExerciseEngine.get_regions_for_level(level):
|
|
assert_between(
|
|
ExerciseEngine.get_regions_for_level(level).size(), 1, 3, "3 tableaux maximum"
|
|
)
|
|
for rule_id: String in region["rule_ids"]:
|
|
assert_false(owners.has(rule_id), "regle dans deux tableaux : %s" % rule_id)
|
|
owners[rule_id] = region["region_id"]
|
|
var rule := ExerciseEngine.get_rule(rule_id)
|
|
assert_false(rule.is_empty(), "regle inconnue : %s" % rule_id)
|
|
assert_eq(rule.get("level", ""), level, "niveau de %s" % rule_id)
|
|
for mission in ExerciseEngine.get_missions():
|
|
assert_true(
|
|
owners.has(mission["rule_id"]), "mission hors tableau : %s" % mission["mission_id"]
|
|
)
|
|
|
|
|
|
func test_regions_have_a_child_facing_title_and_unique_order() -> void:
|
|
for level in SchoolLevels.ALL:
|
|
var orders := {}
|
|
for region in ExerciseEngine.get_regions_for_level(level):
|
|
assert_true(region.has("region_title"), "titre manquant : %s" % region["region_id"])
|
|
var order := int(region.get("order", 1))
|
|
assert_false(orders.has(order), "numero de tableau en double dans %s" % level)
|
|
orders[order] = true
|
|
|
|
|
|
func test_school_levels_helpers() -> void:
|
|
assert_eq(SchoolLevels.previous("CE1"), "")
|
|
assert_eq(SchoolLevels.previous("CM1"), "CE2")
|
|
assert_eq(SchoolLevels.previous("n_importe_quoi"), "")
|
|
assert_true(SchoolLevels.rank("CM2") > SchoolLevels.rank("CE2"))
|
|
|
|
|
|
func test_correct_answer_position_is_not_always_the_same() -> void:
|
|
# Une regle dont la bonne reponse est toujours au meme rang se devine sans
|
|
# lire : les QCM d'une regle doivent varier la position de la bonne reponse.
|
|
var positions: Dictionary = {}
|
|
for rule_id: String in ExerciseEngine._rules:
|
|
for exercise: Dictionary in ExerciseEngine._candidates_for(rule_id, "multiple_choice"):
|
|
if not positions.has(rule_id):
|
|
positions[rule_id] = {}
|
|
positions[rule_id][int(exercise["correct_answer"])] = true
|
|
assert_gt(positions.size(), 5)
|
|
for rule_id: String in positions:
|
|
assert_gt(
|
|
(positions[rule_id] as Dictionary).size(),
|
|
1,
|
|
"bonne reponse toujours au meme rang : %s" % rule_id
|
|
)
|
|
|
|
|
|
func test_elided_wrong_tokens_keep_the_same_prefix_unless_the_word_changes() -> void:
|
|
# Regression : « j'achèterai » avait pour attendu « achèterais » (sans « j' »),
|
|
# donc la reponse naturelle « j'achèterais » etait refusee. Un mot touche avec
|
|
# elision doit avoir un attendu qui garde le prefixe d'elision, sauf si c'est
|
|
# l'elision elle-meme qui est l'objet de l'exercice (la/l'a, qu'elle/quelle...).
|
|
for rule_id: String in ExerciseEngine._rules:
|
|
for exercise: Dictionary in ExerciseEngine._candidates_for(rule_id, "sentence_correction"):
|
|
for token: Dictionary in exercise["tokens"]:
|
|
if token.get("correct", true):
|
|
continue
|
|
var text: String = token["text"]
|
|
var expected: String = token["expected"]
|
|
if not text.contains("'") or expected.contains("'"):
|
|
continue
|
|
# Le mot change de nature (ex. « Qu'elle » -> « Quelle ») : seules
|
|
# les corrections ou l'elision est conservee sont concernees.
|
|
var prefix := text.split("'")[0]
|
|
var stem := text.substr(prefix.length() + 1)
|
|
assert_false(
|
|
expected.to_lower().begins_with(stem.substr(0, 3).to_lower()),
|
|
(
|
|
"%s : attendu « %s » sans le prefixe de « %s »"
|
|
% [exercise["id"], expected, text]
|
|
)
|
|
)
|