add locomotion-action analyzer

analyzer/__init__.py

@@ -1,2 +1,3 @@
 from .analyzer import *
 from .biogames import *
+from .locomotion_action import *

analyzer/analyzer.py

@@ -1,5 +1,5 @@
 import json
-from collections import defaultdict
+from collections import defaultdict, Iterable
 
 from log_analyzer import LogSettings
 
@@ -11,21 +11,31 @@ class Analyzer:
 	def process(self, entry: dict) -> bool:
 		raise NotImplementedError()
 
-	def result(self) -> object:
+	def result(self) -> Iterable:
 		raise NotImplementedError()
 
+	def name(self):
+		return self.__name__
+
 
 class LocationAnalyzer(Analyzer):
+	"""
+	store spatial log entries
+	"""
 	entries = []
+	__name__ = "Location"
+
+	class Formats:
+		geojson = 0
 
 	def __init__(self, settings: LogSettings):
 		super().__init__(settings)
 
-	def result(self) -> object:
+	def result(self) -> list:
 		return self.entries
 
-	def render(self, format="geojson"):
-		if format is "geojson":
+	def render(self, format: int = Formats.geojson):
+		if format is self.Formats.geojson:
 			return json.dumps([entry['location']['coordinates'] for entry in self.entries])
 		raise NotImplementedError()
 
@@ -36,7 +46,12 @@ class LocationAnalyzer(Analyzer):
 
 
 class LogEntryCountAnalyzer(Analyzer):
-	def result(self) -> object:
+	"""
+	count occurrences of log entry types
+	"""
+	__name__ = "LogEntryCount"
+
+	def result(self) -> defaultdict:
 		return self.store
 
 	def process(self, entry: dict) -> bool:
@@ -48,3 +63,34 @@ class LogEntryCountAnalyzer(Analyzer):
 		self.store = defaultdict(lambda: 0)
 
 
+class LogEntrySequenceAnalyzer(Analyzer):
+	"""
+	store sequence of all log entry types
+	"""
+	__name__ = "LogEntrySequence"
+
+	def result(self) -> list:
+		return self.store
+
+	def process(self, entry: dict) -> bool:
+		entry_type = entry[self.settings.entry_type]
+		self.store.append(entry_type)
+		return False
+
+	def __init__(self, settings: LogSettings):
+		super().__init__(settings)
+		self.store = []
+
+
+class ActionSequenceAnalyzer(LogEntrySequenceAnalyzer):
+	"""
+	find sequence of non-spatial log entry types
+	"""
+	__name__ = "ActionSequenceAnalyzer"
+
+	def process(self, entry: dict) -> bool:
+		entry_type = entry[self.settings.entry_type]
+		if entry_type in self.settings.spatials:
+			return False
+		self.store.append(entry_type)
+		return False

analyzer/biogames.py

@@ -6,13 +6,41 @@ from .analyzer import Analyzer
 
 
 class BoardDurationAnalyzer(Analyzer):
-	def result(self) -> object:
-		return self.store
+	"""
+	calculate display duration of boards
+	"""
+	__name__ = "BoardDuration"
+
+	def render(self) -> str:
+		return "\n".join(["{}\t{}".format(entry["active"], entry["id"]) for entry in self.result()])
+
+	def result(self) -> list:
+		result = []
+		last_timestamp = None
+		last_board = None
+		for board in self.store:
+			board_id, timestamp = board["id"], board["timestamp"]
+
+			if not last_timestamp is None:
+				result.append(self.save_entry(last_board, last_timestamp, timestamp - last_timestamp))
+			last_timestamp = timestamp
+			last_board = board_id
+		# TODO: last board?
+		return result
 
 	def process(self, entry: dict) -> bool:
-		self.store[entry[self.settings.entry_type]] += 1
+		entry_type = entry[self.settings.entry_type]
+		if entry_type in self.settings.boards:
+			self.store.append(self.save_entry(entry["board_id"], entry["timestamp"]))  # TODO: make configurable
 		return False
 
+	def save_entry(self, board_id: str, timestamp: int, active: int = None):
+		entry = {"id": board_id, "timestamp": timestamp}
+		if not active is None:
+			entry["active"] = active
+		return entry
+
 	def __init__(self, settings: LogSettings):
 		super().__init__(settings)
-		self.store = defaultdict(lambda: 0)
+		self.store = []
+		self.last = {}

analyzer/locomotion_action.py

@@ -0,0 +1,93 @@
+from collections import defaultdict
+
+from log_analyzer import LogSettings
+
+from .analyzer import Analyzer
+from util import combinate
+
+
+def init_filter(settings: LogSettings, state: str) -> callable:
+	# this implies OR for lists; AND for dicts
+	if type(settings.sequences[state]) in (str, list):
+		return lambda entry: entry[settings.entry_type] in settings.sequences[state]
+	else:
+		return lambda entry: combinate(settings.sequences[state], entry)
+
+
+class LocomotionActionAnalyzer(Analyzer):  # TODO
+	"""
+	calculate locomation/action times and ratio
+
+	Anything between LogEntryCache and CacheEnableAction
+		is counted as ActionTime, the rest as LocomotionTime.
+	"""
+	__name__ = "LocomotionAction"
+
+	def process(self, entry: dict) -> bool:
+		self.last_timestamp = entry["timestamp"]
+		if self.instance_start is None:
+			self.instance_start = self.last_timestamp
+		self.last = self.last_timestamp
+		if self.cache_time is None:
+			self.cache_time = self.last_timestamp
+		offset = self.last_timestamp - self.cache_time
+
+		if self.current_cache is None and self.filter_start(entry):
+			if entry['cache'] is None:
+				return False
+			self.current_cache = entry['cache']['@id']
+			self.cache_time = self.last_timestamp
+			self.locomotion.append(offset)
+			self.last = None
+		elif self.current_cache and self.filter_end(entry):
+			self.actions.append(offset)
+			self.cache_time = self.last_timestamp
+			self.current_cache = None
+			self.last = None
+
+	def result(self) -> dict:
+		if self.last is not None:
+			if self.current_cache is None:
+				self.locomotion.append(self.last - self.cache_time)
+			else:
+				self.actions.append(self.last - self.cache_time)
+		locomotion = sum(self.locomotion)
+		action = sum(self.actions)
+		return {
+			'loco_sum': locomotion,
+			'action_sum': action,
+			'loco': self.locomotion,
+			'act': self.actions,
+			'dur': (self.last_timestamp - self.instance_start)
+		}
+
+	def __init__(self, settings: LogSettings):
+		super().__init__(settings)
+		self.filter_start = init_filter(settings, "start")
+		self.filter_end = init_filter(settings, "end")
+		self.current_cache = None
+		self.cache_time = None
+		self.locomotion = []
+		self.actions = []
+		self.instance_start = None
+		self.last_timestamp = None
+		self.last = None
+
+
+class CacheSequenceAnalyzer(Analyzer):  # TODO
+	__name__ = "CacheSequence"
+
+	def process(self, entry: dict) -> bool:
+		if self.filter(entry):
+			if entry['cache']:
+				self.store.append((entry['timestamp'],entry['cache']['@id']))
+			else:
+				self.store.append((entry['timestamp'],entry['cache']))
+
+	def result(self) -> list:
+		return self.store
+
+	def __init__(self, settings: LogSettings):
+		super().__init__(settings)
+		self.store = []
+		self.filter = init_filter(settings, "start")

biogames2.json

@@ -1,14 +1,36 @@
 {
   "logFormat": "sqlite",
   "entryType": "@class",
-  "spatials":["de.findevielfalt.games.game2.instance.log.entry.LogEntryLocation"],
-  "actions":["...QuestionAnswerEvent", "...SimuAnswerEvent"],
+  "spatials": [
+    "de.findevielfalt.games.game2.instance.log.entry.LogEntryLocation"
+  ],
+  "actions": [
+    "...QuestionAnswerEvent",
+    "...SimuAnswerEvent"
+  ],
+  "boards": [
+    "de.findevielfalt.games.game2.instance.log.entry.ShowBoardLogEntry"
+  ],
   "analyzers": {
     "analyzer": [
-      "LocationAnalyzer"
-      ],
+      "LocationAnalyzer",
+      "LogEntryCountAnalyzer",
+      "LogEntrySequenceAnalyzer",
+      "ActionSequenceAnalyzer"
+    ],
     "analyzer.biogames": [
       "BoardDurationAnalyzer"
+    ],
+    "analyzer.locomotion_action": [
+      "LocomotionActionAnalyzer",
+      "CacheSequenceAnalyzer"
     ]
+  },
+  "sequences": {
+    "start": "de.findevielfalt.games.game2.instance.log.entry.LogEntryCache",
+    "end": {
+      "@class": "de.findevielfalt.games.game2.instance.log.entry.LogEntryInstanceAction",
+      "action.@class": "de.findevielfalt.games.game2.instance.action.CacheEnableAction"
+    }
   }
 }

log_analyzer.py

@@ -10,15 +10,19 @@ class LogSettings:
 	spatials = None
 	actions = None
 	analyzers = []
+	boards = None
+	sequences = None
 
 	def __init__(self, json_dict):
 		self.log_format = json_dict['logFormat']
 		self.entry_type = json_dict['entryType']
 		self.spatials = json_dict['spatials']
 		self.actions = json_dict['actions']
+		self.boards = json_dict['boards']
 		for mod in json_dict['analyzers']:
 			for name in json_dict['analyzers'][mod]:
 				self.analyzers.append(getattr(sys.modules[mod], name))
+		self.sequences = json_dict['sequences']
 
 	def __repr__(self):
 		return str({
@@ -26,11 +30,13 @@ class LogSettings:
 			"entryType": self.entry_type,
 			"spatials": self.spatials,
 			"actions": self.actions,
-			"analyzers": self.analyzers
+			"analyzers": self.analyzers,
+			"boards": self.boards,
+			"sequences": self.sequences,
 		})
 
 
-def load_settings(file:str) -> LogSettings:
+def load_settings(file: str) -> LogSettings:
 	return LogSettings(json.load(open(file)))
 
 
@@ -51,8 +57,17 @@ if __name__ == '__main__':
 			if analyzer.process(entry):
 				break
 	for analyzer in analyzers:
-		print("* Result for " + str(type(analyzer)))
+		print("* Result for " + analyzer.name())
 		print(analyzer.result())
-	coords = analyzers[0].render()
-	with open("test.js", "w") as out:
-		out.write("coords = "+coords)
+	#for analyzer in analyzers:
+	#	if analyzer.name() in ["LogEntryCount", "ActionSequenceAnalyzer"]:
+	#		print(json.dumps(analyzer.result(), indent=2))
+
+	#for analyzer in analyzers:
+	#	if analyzer.name() in ["BoardDuration"]:
+	#		print(json.dumps(analyzer.result(), indent=2))
+	#		print(analyzer.render())
+
+			# coords = analyzers[1].render()
+			# with open("test.js", "w") as out:
+			#	out.write("coords = "+coords)

util/__init__.py

@@ -0,0 +1 @@
+from .iter import *

util/iter.py

@@ -0,0 +1,18 @@
+def json_path(obj: dict, key: str):
+	"""Query a nested dict with a dot-separated path"""
+	if not type(obj) is dict:
+		return None
+	if "." not in key:
+		return obj[key]
+	child_key = key.split(".")
+	if child_key[0] not in obj:
+		return None
+	return json_path(obj[child_key[0]], ".".join(child_key[1:]))
+
+
+def combinate(settings: dict, entry:dict)-> bool:
+	"""combine all settings {<key>: <expected>} with entry using AND"""
+	result = True
+	for key, value in settings.items():
+		result = result and json_path(entry, key) == value
+	return result