cleanup, improve structure

analyzers/analyzer/default.py

@@ -137,3 +137,72 @@ class ProgressAnalyzer(Analyzer):
 		if entry[self.settings.type_field] in self.settings.boards:
 			self.board[entry["timestamp"]] = entry
 		return False
+
+
+class MetaDataAnalyzer(Analyzer):
+	"""collect metadata"""
+	__name__ = "MetaDataAnalyzer"
+
+	def result(self, store: ResultStore, name=None) -> None:
+		store.add(Result(type(self), dict(self.store)))
+
+	def process(self, entry: dict) -> bool:
+		if not "metadata" in self.settings.custom:
+			return False
+		for mdata in self.settings.custom["metadata"]:
+			key = self.settings.custom["metadata"]
+			if key in entry:
+				self.store[mdata] = json_path(entry, key)
+
+	def __init__(self, settings: LogSettings) -> None:
+		super().__init__(settings)
+		self.store = {}
+
+
+def write_logentry_count_csv(LogEntryCountCSV, store, render, analyzers):
+	global cat, data, lines, csvfile
+	LogEntryCountCSV.summary = None
+	for cat in store.get_categories():
+		data = store.get_category(cat)
+		render(analyzers.LogEntryCountAnalyzer, data, name=cat)
+	if LogEntryCountCSV.summary:
+		headers = []
+		lines = []
+		for name in LogEntryCountCSV.summary:
+			data = LogEntryCountCSV.summary[name]
+			for head in data:
+				if not head in headers:
+					headers.append(head)
+			line = [name]
+			for head in headers:
+				line.append(data[head]) if head in data else line.append(0)
+			lines.append(line)
+		import csv
+
+		with open('logentrycount.csv', 'w', newline='') as csvfile:
+			writer = csv.writer(csvfile, quoting=csv.QUOTE_NONE)
+			writer.writerow(["name"] + [h.split(".")[-1] for h in headers])
+			for line in lines:
+				writer.writerow(line)
+
+
+def write_simulation_flag_csv(store):
+	global csvfile, result, i
+	from datetime import datetime
+	import json
+	json.dump(store.serializable(), open("simus.json", "w"), indent=2)
+	with open("simus.csv", "w") as csvfile:
+		csvfile.write("instanceconfig,log,simu,answered,universe_state,selected_actions,timestamp,time\n")
+		for key in store.get_store():
+			csvfile.write("{}\n".format(key))
+			for result in store.store[key]:
+				csvfile.write(",{}\n".format(result.name))
+				for i in result.get():
+					csvfile.write(",,{},{},{},{},{},{}\n".format(
+						i['answers']['@id'],
+						i['answers']['answered'],
+						len(i['answers']['universe_state']) if i['answers']['universe_state'] else 0,
+						len(i['selected_actions']) if i['selected_actions'] else 0,
+						i['timestamp'],
+						str(datetime.fromtimestamp(i['timestamp'] / 1000))
+					))

analyzers/render/wip.py

@@ -0,0 +1,87 @@
+def time_distribution(store):
+	# json.dump(store.serializable(), open("new.json", "w"), indent=1)
+	from collections import defaultdict
+	import json
+	import numpy as np
+
+	keys = [
+		"simu",
+		"question",
+		"image",
+		"audio",
+		"video",
+		"other",
+		"map"
+	]
+	import matplotlib.pyplot as plt
+
+	# results = []
+
+	places = defaultdict(list)
+
+	for log in store.get_all():
+		result = defaultdict(lambda: 0)
+		for i in log.get()['track']:
+			duration = i['properties']['end_timestamp'] - i['properties']['start_timestamp']
+			result[i['properties']['activity_type']] += duration
+		print(json.dumps(result, indent=4))
+		total = sum(result.values())
+		print(total)
+		percentage = defaultdict(lambda: 0)
+		minutes = defaultdict(lambda: 0)
+		for i in result:
+			percentage[i] = result[i] / total
+			minutes[i] = result[i] / 60_000
+		print(json.dumps(percentage, indent=4))
+		if not 'error' in result:
+			# places[log.get()['instance']].append(percentage)
+			places[log.get()['instance']].append(minutes)
+
+	for place in places:
+		places[place] = sorted(places[place], key=lambda item: item['map'])
+
+	dummy = [0] * len(keys)
+	results = []
+	sites = []
+	from util.meta_temp import CONFIG_NAMES
+
+	for i in places:
+		for j in places[i]:
+			ordered = []
+			for k in keys:
+				ordered.append(j[k])
+			results.append(ordered)
+		results.append(dummy)
+		sites.append(CONFIG_NAMES[i] if i in CONFIG_NAMES else "---")
+
+	size = len(results)
+	ind = np.arange(size)
+	width = 0.9
+	print(results)
+	data = list(zip(*results))
+	print(data)
+	lines = []
+	bottom = [0] * len(results)
+	for i in range(0, len(data)):
+		lines.append(plt.bar(ind, data[i], bottom=bottom, width=width)[0])
+		for k, x in enumerate(data[i]):
+			bottom[k] += x
+	plt.legend(lines, keys)
+	plt.title(", ".join(sites))
+	plt.show()
+
+	# size = len(results)
+	# ind = np.arange(size)
+	# width = 0.9
+	# print(results)
+	# data = list(zip(*results))
+	# print(data)
+	# lines = []
+	# bottom = [0] * len(results)
+	# for i in range(0, len(data)):
+	#	lines.append(plt.bar(ind, data[i], bottom=bottom, width=width)[0])
+	#	for k, x in enumerate(data[i]):
+	#		bottom[k] += x
+	# plt.legend(lines, keys)
+	# plt.title("Zwei Spiele in Filderstadt (t1=237min; t2=67min)")
+	# plt.show()

biogames2.json

@@ -67,7 +67,12 @@
         "action":"PAUSE"
       }
     },
-    "coordinates": "location.coordinates"
+    "coordinates": "location.coordinates",
+    "metadata":{
+      "timestamp": "timestamp",
+      "gamefield": "instance_id",
+      "user": "player_group_name"
+    }
   },
   "source":{
     "type": "Biogames",

log_analyzer.py

@@ -7,9 +7,12 @@ import numpy as np
 import analyzers
 from analyzers import get_renderer, Analyzer, render, Store
 from analyzers.analyzer import ResultStore
+from analyzers.analyzer.default import write_logentry_count_csv, write_simulation_flag_csv
 from analyzers.render.default import LogEntryCountCSV
+from analyzers.render.wip import time_distribution
 from analyzers.settings import LogSettings, load_settings
 from loaders import LOADERS
+from util.processing import grep, run_analysis
 
 logging.basicConfig(format='%(levelname)s %(name)s:%(message)s', level=logging.DEBUG)
 log: logging.Logger = logging.getLogger(__name__)
@@ -18,98 +21,11 @@ logging.getLogger('requests').setLevel(logging.WARN)
 logging.getLogger("urllib3").setLevel(logging.WARNING)
 
 
-def process_log(logfile: str, settings: LogSettings) -> List[Analyzer]:
-	loader = LOADERS[settings.log_format]()
-	try:
-		loader.load(logfile)
-	except BaseException as e:
-		raise RuntimeError(e)
-	analyzers: List[Analyzer] = []
-	log.debug("build analyzers")
-	for analyzer in settings.analyzers:
-		analyzers.append(analyzer(settings))
-	log.debug("process entries")
-	for entry in loader.get_entry():
-		for analyzer in analyzers:
-			try:
-				if analyzer.process(entry):
-					break
-			except KeyError as e:
-				log.exception(e)
-	return analyzers
-
-
-def run_analysis(log_ids: list, settings):
-	store: ResultStore = ResultStore()
-	for log_id in log_ids:
-		for analysis in process_log(log_id, settings):
-			log.info("* Result for " + analysis.name())
-			analysis.result(store, name=log_id)
-	return store
-
-
-def load_ids(name: str):
-	log_ids = []
-	with open(name) as src:
-		for line in src:
-			line = line.strip()
-			log_ids.append(line)
-	return log_ids
-
-
 def urach_logs(log_ids, settings):
-	#return ["data/inst_{id}.{format}".format(id=log_id, format=settings.log_format) for log_id in log_ids]
+	# return ["data/inst_{id}.{format}".format(id=log_id, format=settings.log_format) for log_id in log_ids]
 	return ["data/{id}.{format}".format(id=log_id, format=settings.log_format) for log_id in log_ids]
 
 
-def write_logentry_count_csv():
-	global cat, data, lines, csvfile
-	LogEntryCountCSV.summary = None
-	for cat in store.get_categories():
-		data = store.get_category(cat)
-		render(analyzers.LogEntryCountAnalyzer, data, name=cat)
-	if LogEntryCountCSV.summary:
-		headers = []
-		lines = []
-		for name in LogEntryCountCSV.summary:
-			data = LogEntryCountCSV.summary[name]
-			for head in data:
-				if not head in headers:
-					headers.append(head)
-			line = [name]
-			for head in headers:
-				line.append(data[head]) if head in data else line.append(0)
-			lines.append(line)
-		import csv
-
-		with open('logentrycount.csv', 'w', newline='') as csvfile:
-			writer = csv.writer(csvfile, quoting=csv.QUOTE_NONE)
-			writer.writerow(["name"] + [h.split(".")[-1] for h in headers])
-			for line in lines:
-				writer.writerow(line)
-
-
-def write_simulation_flag_csv():
-	global csvfile, result, i
-	from datetime import datetime
-	json.dump(store.serializable(), open("simus.json", "w"), indent=2)
-	with open("simus.csv", "w") as csvfile:
-		csvfile.write("instanceconfig,log,simu,answered,universe_state,selected_actions,timestamp,time\n")
-		for key in store.get_store():
-			csvfile.write("{}\n".format(key))
-			for result in store.store[key]:
-				csvfile.write(",{}\n".format(result.name))
-				for i in result.get():
-					csvfile.write(",,{},{},{},{},{},{}\n".format(
-						i['answers']['@id'],
-						i['answers']['answered'],
-						len(i['answers']['universe_state']) if i['answers']['universe_state'] else 0,
-						len(i['selected_actions']) if i['selected_actions'] else 0,
-						i['timestamp'],
-						str(datetime.fromtimestamp(i['timestamp'] / 1000))
-					))
-
-
 if __name__ == '__main__':
 	settings: LogSettings = load_settings("biogames2.json")
 	log_ids_urach: List[str] = urach_logs([
@@ -121,11 +37,19 @@ if __name__ == '__main__':
 		# "597b704fe9ace475316c345903",
 		# "e01a684aa29dff9ddd9705edf8",
 		# "fbf9d64ae0bdad0de7efa3eec6",
-		"fe1331481f85560681f86827ec",
+		"fe1331481f85560681f86827ec",  # urach
 		# "fe1331481f85560681f86827ec"]
-		"fec57041458e6cef98652df625", ]
+		"fec57041458e6cef98652df625",
-		,settings)
+	]
-	store: ResultStore = run_analysis(log_ids_urach, settings)
+		, settings)
+	log_ids_gf = grep(["9d11b749c78a57e786bf5c8d28",  # filderstadt
+					   "a192ff420b8bdd899fd28573e2",  # eichstätt
+					   "3a3d994c04b1b1d87168422309",  # stadtökologie
+					   "96f6d9cc556b42f3b2fec0a2cb7ed36e"  # oberelsbach
+					   ],
+					  "/home/clemens/git/ma/test/src",
+					  settings)
+	store: ResultStore = run_analysis(log_ids_gf, settings, LOADERS)
 	if False:
 		for r in get_renderer(analyzers.LocomotionActionAnalyzer):
 			r().render(store.get_all())
@@ -148,110 +72,12 @@ if __name__ == '__main__':
 			data = store.get_category(cat)
 			render(analyzers.SimulationOrderAnalyzer, data, name=cat)
 	if False:
-		write_logentry_count_csv()
+		write_logentry_count_csv(LogEntryCountCSV, store, render, analyzers)
 	if False:
-		write_simulation_flag_csv()
+		write_simulation_flag_csv(store)
-
-
-	def calc_distance(geojson: str):
-		from shapely.geometry import LineString
-		from shapely.ops import transform
-		from functools import partial
-		import pyproj
-		track = LineString(json.loads(geojson)['coordinates'])
-		project = partial(
-			pyproj.transform,
-			pyproj.Proj(init='EPSG:4326'),
-			pyproj.Proj(init='EPSG:32633'))
-		return transform(project, track).length
-
-
-	if False:
-		# json.dump(store.serializable(), open("new.json", "w"), indent=1)
-		from collections import defaultdict
-
-		keys = [
-			"simu",
-			"question",
-			"image",
-			"audio",
-			"video",
-			"other",
-			"map"
-		]
-		import matplotlib.pyplot as plt
-
-		# results = []
-
-		places = defaultdict(list)
-
-		for log in store.get_all():
-			result = defaultdict(lambda: 0)
-			for i in log.get()['track']:
-				duration = i['properties']['end_timestamp'] - i['properties']['start_timestamp']
-				result[i['properties']['activity_type']] += duration
-			print(json.dumps(result, indent=4))
-			total = sum(result.values())
-			print(total)
-			percentage = defaultdict(lambda: 0)
-			minutes = defaultdict(lambda: 0)
-			for i in result:
-				percentage[i] = result[i] / total
-				minutes[i] = result[i] / 60_000
-			print(json.dumps(percentage, indent=4))
-			if not 'error' in result:
-				# places[log.get()['instance']].append(percentage)
-				places[log.get()['instance']].append(minutes)
-
-		for place in places:
-			places[place] = sorted(places[place], key=lambda item: item['map'])
-
-		dummy = [0] * len(keys)
-		results = []
-		sites = []
-		from util.meta_temp import CONFIG_NAMES
-
-		for i in places:
-			for j in places[i]:
-				ordered = []
-				for k in keys:
-					ordered.append(j[k])
-				results.append(ordered)
-			results.append(dummy)
-			sites.append(CONFIG_NAMES[i] if i in CONFIG_NAMES else "---")
-
-		size = len(results)
-		ind = np.arange(size)
-		width = 0.9
-		print(results)
-		data = list(zip(*results))
-		print(data)
-		lines = []
-		bottom = [0] * len(results)
-		for i in range(0, len(data)):
-			lines.append(plt.bar(ind, data[i], bottom=bottom, width=width)[0])
-			for k, x in enumerate(data[i]):
-				bottom[k] += x
-		plt.legend(lines, keys)
-		plt.title(", ".join(sites))
-		plt.show()
-
-	# size = len(results)
-	# ind = np.arange(size)
-	# width = 0.9
-	# print(results)
-	# data = list(zip(*results))
-	# print(data)
-	# lines = []
-	# bottom = [0] * len(results)
-	# for i in range(0, len(data)):
-	#	lines.append(plt.bar(ind, data[i], bottom=bottom, width=width)[0])
-	#	for k, x in enumerate(data[i]):
-	#		bottom[k] += x
-	# plt.legend(lines, keys)
-	# plt.title("Zwei Spiele in Filderstadt (t1=237min; t2=67min)")
-	# plt.show()
 
+	if True:
+		time_distribution(store)
 
 
 # for analyzers in analyzers:

static/progress/my.js

@@ -1,12 +1,10 @@
-//$.getJSON("data/ff8f1e8f-6cf5-4a7b-835b-5e2226c1e771_03b9b6b4-c8ab-4182-8902-1620eebe8889.json", function (data) {
+$.getJSON("data/ff8f1e8f-6cf5-4a7b-835b-5e2226c1e771_03b9b6b4-c8ab-4182-8902-1620eebe8889.json", function (data) {    //urach
-$.getJSON("data/ff8f1e8f-6cf5-4a7b-835b-5e2226c1e771_de7df5b5-edd5-4070-840f-68854ffab9aa.json", function (data) {
+//$.getJSON("data/ff8f1e8f-6cf5-4a7b-835b-5e2226c1e771_de7df5b5-edd5-4070-840f-68854ffab9aa.json", function (data) {  //urach
+//$.getJSON("data/90278021-4c57-464e-90b1-d603799d07eb_07da99c9-398a-424f-99fc-2701763a63e9.json", function (data) {  //eichstätt
+//$.getJSON("data/13241906-cdae-441a-aed0-d57ebeb37cac_d33976a6-8a56-4a63-b492-fe5427dbf377.json", function (data) {  //stadtökologie
+//$.getJSON("data/5e64ce07-1c16-4d50-ac4e-b3117847ea43_2f664d7b-f0d8-42f5-8731-c034ef86703e.json", function (data) {  //filderstadt
     var images = {};
     var tiles = {
-        "osm": L.tileLayer('http://{s}.tile.osm.org/{z}/{x}/{y}.png', {
-            maxNativeZoom: 19,
-            maxZoom: 24,
-            attribution: '&copy; <a href="http://osm.org/copyright">OpenStreetMap</a> contributors',
-        }),
         "openstreetmap": L.tileLayer('https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png', {
             maxNativeZoom: 19,
             maxZoom: 24,
@@ -17,13 +15,13 @@ $.getJSON("data/ff8f1e8f-6cf5-4a7b-835b-5e2226c1e771_de7df5b5-edd5-4070-840f-688
             maxZoom: 24,
             attribution: 'Tiles &copy; Esri &mdash; Source: Esri, i-cubed, USDA, USGS, AEX, GeoEye, Getmapping, Aerogrid, IGN, IGP, UPR-EGP, and the GIS User Community'
         }),
-        "google sat": L.tileLayer('http://{s}.google.com/vt/lyrs=s&x={x}&y={y}&z={z}', {
+        "google sat": L.tileLayer('https://{s}.google.com/vt/lyrs=s&x={x}&y={y}&z={z}', {
             maxNativeZoom: 20,
             maxZoom: 24,
             subdomains: ['mt0', 'mt1', 'mt2', 'mt3']
         })
     };
-    var map = L.map("mainMap", {layers: [tiles.osm]});
+    var map = L.map("mainMap", {layers: [tiles.openstreetmap]});
 
     function styleTrack(feature) {
         var styles = {};

util/geo.py

@@ -0,0 +1,12 @@
+def calc_distance(geojson: str):
+	from shapely.geometry import LineString
+	from shapely.ops import transform
+	from functools import partial
+	import pyproj
+	import json
+	track = LineString(json.loads(geojson)['coordinates'])
+	project = partial(
+		pyproj.transform,
+		pyproj.Proj(init='EPSG:4326'),
+		pyproj.Proj(init='EPSG:32633'))
+	return transform(project, track).length

util/processing.py

@@ -0,0 +1,57 @@
+import logging
+from typing import List
+
+from analyzers.analyzer import ResultStore, Analyzer
+from analyzers.settings import LogSettings
+
+log: logging.Logger = logging.getLogger(__name__)
+
+
+def process_log(logfile: str, settings: LogSettings, loaders) -> List[Analyzer]:
+	loader = loaders[settings.log_format]()
+	try:
+		loader.load(logfile)
+	except BaseException as e:
+		raise RuntimeError(e)
+	analyzers: List[Analyzer] = []
+	log.debug("build analyzers")
+	for analyzer in settings.analyzers:
+		analyzers.append(analyzer(settings))
+	log.debug("process entries")
+	for entry in loader.get_entry():
+		for analyzer in analyzers:
+			try:
+				if analyzer.process(entry):
+					break
+			except KeyError as e:
+				log.exception(e)
+	return analyzers
+
+
+def run_analysis(log_ids: list, settings, loaders):
+	store: ResultStore = ResultStore()
+	for log_id in log_ids:
+		for analysis in process_log(log_id, settings, loaders):
+			log.info("* Result for " + analysis.name())
+			analysis.result(store, name=log_id)
+	return store
+
+
+def load_ids(name: str):
+	log_ids = []
+	with open(name) as src:
+		for line in src:
+			line = line.strip()
+			log_ids.append(line)
+	return log_ids
+
+
+def grep(log_ids, source, settings):
+	logs = []
+	with open(source) as src:
+		lines = src.readlines()
+		for id in log_ids:
+			for line in lines:
+				if id in line:
+					logs.append(line.strip())
+	return logs