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@ -63,17 +63,18 @@ if __name__ == '__main__':
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# "fec57041458e6cef98652df625", ]
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log_ids = []
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# with open("/home/clemens/git/ma/test/filtered") as src:
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with open("/home/clemens/git/ma/test/filtered") as src:
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for line in src:
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line = line.strip()
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log_ids.append(line)
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store: ResultStore = ResultStore()
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for log_id in log_ids:
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for analysis in process_log(log_id, settings):
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log.info("* Result for " + analysis.name())
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# print(analysis.result())
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# print(analysis.render())
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analysis.result(store)
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if False:
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with open("/home/clemens/git/ma/test/filtered_5_actions") as src:
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for line in src:
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line = line.strip()
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log_ids.append(line)
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store: ResultStore = ResultStore()
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for log_id in log_ids:
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for analysis in process_log(log_id, settings):
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log.info("* Result for " + analysis.name())
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# print(analysis.result())
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# print(analysis.render())
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analysis.result(store)
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if False:
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for r in get_renderer(analyzers.LocomotionActionAnalyzer):
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r().render(store.get_all())
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@ -120,8 +121,10 @@ if __name__ == '__main__':
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writer.writerow(line)
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if True:
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#json.dump(store.serializable(), open("new.json", "w"), indent=1)
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# json.dump(store.serializable(), open("new.json", "w"), indent=1)
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from collections import defaultdict
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import matplotlib.pyplot as plt
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from util.meta_temp import CONFIG_NAMES
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keys = [
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"simu",
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@ -130,81 +133,243 @@ if __name__ == '__main__':
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"audio",
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"video",
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"other",
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"map"
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"map",
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# "error"
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]
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import matplotlib.pyplot as plt
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#results = []
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places = defaultdict(list)
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for log in store.get_all():
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result = defaultdict(lambda: 0)
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for i in log.get()['track']:
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duration = i['properties']['end_timestamp'] - i['properties']['start_timestamp']
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result[i['properties']['activity_type']] += duration
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print(json.dumps(result, indent=4))
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total = sum(result.values())
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print(total)
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percentage = defaultdict(lambda :0)
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minutes = defaultdict(lambda:0)
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for i in result:
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percentage[i]= result[i]/total
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minutes[i] = result[i]/60_000
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print(json.dumps(percentage,indent=4))
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if not 'error' in result:
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#places[log.get()['instance']].append(percentage)
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places[log.get()['instance']].append(minutes)
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def get_data(store, relative_values=True, sort=True, show_errors=False):
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places = defaultdict(list)
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for place in places:
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places[place] = sorted(places[place], key=lambda item:item['map'])
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for log in store.get_all():
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if not log.analysis() == analyzers.ActivityMapper:
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continue
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result = defaultdict(lambda: 0)
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for i in log.get()['track']:
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duration = i['properties']['end_timestamp'] - i['properties']['start_timestamp']
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result[i['properties']['activity_type']] += duration
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print(json.dumps(result, indent=4))
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total = sum(result.values())
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print(total)
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percentage = defaultdict(lambda: 0)
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minutes = defaultdict(lambda: 0)
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for i in result:
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percentage[i] = result[i] / total
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minutes[i] = result[i] / 60_000
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print(json.dumps(percentage, indent=4))
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if not 'error' in result or show_errors:
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if relative_values:
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places[log.get()['instance']].append(percentage)
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else:
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places[log.get()['instance']].append(minutes)
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if sort:
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for place in places:
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places[place] = sorted(places[place], key=lambda item: item['map'])
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return places
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dummy = [0]*len(keys)
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results = []
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sites = []
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from util.meta_temp import CONFIG_NAMES
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for i in places:
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for j in places[i]:
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ordered = []
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from shapely.geometry import LineString
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from shapely.ops import transform
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from functools import partial
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import pyproj
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def calc_distance(coordinates):
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track = LineString(coordinates)
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project = partial(
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pyproj.transform,
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pyproj.Proj(init='EPSG:4326'),
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pyproj.Proj(init='EPSG:32633'))
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return transform(project, track).length
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def get_data_distance(store, relative_values=True, sort=True, show_errors=False):
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places = defaultdict(list)
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for log in store.get_all():
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if not log.analysis() == analyzers.ActivityMapper:
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continue
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result = defaultdict(lambda: 0)
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for i in log.get()['track']:
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coords = i['coordinates']
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if len(coords) > 1:
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distance = calc_distance(coords)
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result[i['properties']['activity_type']] += distance
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total = sum(result.values())
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percentage = defaultdict(lambda: 0)
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for i in result:
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if not total == 0:
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percentage[i] = result[i] / total
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if not 'error' in result or show_errors:
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if relative_values:
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places[log.get()['instance']].append(percentage)
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else:
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places[log.get()['instance']].append(result)
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if sort:
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for place in places:
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places[place] = sorted(places[place], key=lambda item: item['map'])
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return places
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def get_all_data(store):
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places = defaultdict(list)
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for log in store.get_all():
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if not log.analysis() == analyzers.ActivityMapper:
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continue
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result = defaultdict(lambda: defaultdict(lambda: 0))
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for i in log.get()['track']:
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coords = i['coordinates']
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if len(coords) > 1:
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distance = calc_distance(coords)
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else:
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distance = 0.1
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result["space"][i['properties']['activity_type']] += distance
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duration = i['properties']['end_timestamp'] - i['properties']['start_timestamp']
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result["time"][i['properties']['activity_type']] += duration
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total_space = sum(result["space"].values())
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total_time = sum(result["time"].values())
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percentage = defaultdict(lambda: defaultdict(lambda: 0))
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for i in result["space"]:
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if not total_space == 0:
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percentage[i]["space"] = result["space"][i] / total_space
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else:
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percentage[i]["space"] = 0
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if not total_time == 0:
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percentage[i]["time"] = result["time"][i] / total_time
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else:
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percentage[i]["time"] = 0
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print(percentage)
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if not 'error' in result:
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places[log.get()['instance']].append(percentage)
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return places
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def stack_data(keys, places):
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dummy = [0] * len(keys)
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results = []
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sites = []
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for i in places:
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for j in places[i]:
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ordered = []
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for k in keys:
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ordered.append(j[k])
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results.append(ordered)
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results.append(dummy)
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sites.append(CONFIG_NAMES[i] if i in CONFIG_NAMES else "---")
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return results, sites
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def plot_data(places, keys):
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results, sites = stack_data(keys, places)
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size = len(results)
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print("{} elements total".format(size))
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ind = np.arange(size)
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width = 1
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# print(results)
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data = list(zip(*results))
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# print(data)
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lines = []
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bottom = [0] * size
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for i in range(0, len(data)):
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lines.append(plt.bar(ind, data[i], bottom=bottom, width=width)[0])
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for k, x in enumerate(data[i]):
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bottom[k] += x
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plt.legend(lines, keys)
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plt.title(", ".join(sites))
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plt.show()
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colors = {
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"simu": "blue",
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"question": "orange",
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"image": "green",
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"audio": "red",
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"video": "purple",
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"other": "brown",
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"map": "violet",
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# "error":"grey"
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}
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markers = [".", "o", "x", "s", "*", "D", "p", ",", "<", ">", "^", "v", "1", "2", "3", "4"]
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def plot_time_space(time_data, space_data, keys):
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# assuming time_data and space_data are in same order!
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marker = 0
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for id in time_data:
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for k in keys:
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ordered.append(j[k])
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results.append(ordered)
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results.append(dummy)
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sites.append(CONFIG_NAMES[i] if i in CONFIG_NAMES else "---")
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for i in range(len(time_data[id])):
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print(time_data[id][i][k], space_data[id][i][k])
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plt.plot(time_data[id][i][k], space_data[id][i][k], color=colors[k], marker=markers[marker])
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marker += 1
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plt.show()
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size = len(results)
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ind = np.arange(size)
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width=0.9
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print(results)
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data = list(zip(*results))
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print(data)
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lines = []
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bottom = [0]*len(results)
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for i in range(0, len(data)):
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lines.append(plt.bar(ind,data[i], bottom=bottom, width=width)[0])
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for k,x in enumerate(data[i]):
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bottom[k] += x
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plt.legend(lines, keys)
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plt.title(", ".join(sites))
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plt.show()
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# plt.cla()
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# plt.clf()
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# plt.close()
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#size = len(results)
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#ind = np.arange(size)
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#width = 0.9
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#print(results)
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#data = list(zip(*results))
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#print(data)
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#lines = []
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#bottom = [0] * len(results)
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#for i in range(0, len(data)):
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# lines.append(plt.bar(ind, data[i], bottom=bottom, width=width)[0])
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# for k, x in enumerate(data[i]):
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# bottom[k] += x
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#plt.legend(lines, keys)
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#plt.title("Zwei Spiele in Filderstadt (t1=237min; t2=67min)")
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#plt.show()
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def plot_time_space_rel(combined, keys):
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groups = defaultdict(list)
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keys = list(keys)
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keys.remove("other")
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for k in keys:
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for id in sorted(combined):
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group = 0.0
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count = 0
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for item in combined[id]:
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if k in item:
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time = item[k]["time"]
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distance = item[k]["space"]
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if time > 0:
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group += (distance / time)
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count+=1
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else:
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print("div by zero", distance, time)
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if count > 0:
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groups[k].append(group/count)
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else:
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groups[k].append(0.0)
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ind = np.arange(len(combined.keys()))
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width = .7 / len(groups)
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print(ind)
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print(json.dumps(groups, indent=1))
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bars = []
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fig, ax = plt.subplots()
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for k in groups:
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print(groups[k])
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if not len(groups[k]):
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groups[k].append(0)
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bars.append(ax.bar(ind, groups[k], width, color=colors[k]))
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ind = ind + width
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ax.set_xticks(ind + width / 2)
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ax.set_xticklabels(list([CONFIG_NAMES[i] if i in CONFIG_NAMES else "---" for i in sorted(combined.keys())]))
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plt.legend(bars, keys)
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print(combined.keys())
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print([CONFIG_NAMES[i] if i in CONFIG_NAMES else "---" for i in sorted(combined.keys())])
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plt.show()
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# spatial_data = get_data_distance(store,relative_values=False)
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# temporal_data = get_data(store,relative_values=False)
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# spatial_data_rel = get_data_distance(store,relative_values=True)
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# temporal_data_rel = get_data(store,relative_values=True)
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#temporal_data_rel = json.load(open("temporal_rel.json"))
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#spatial_data_rel = json.load(open("spatial_rel.json"))
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# import IPython
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# IPython.embed()
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#print(json.dumps(get_all_data(store)))
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# json.dump(get_all_data(store), open("combined.json", "w"))
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combined = json.load(open("combined.json"))
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plot_time_space_rel(combined, keys)
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#plot_time_space_rel(temporal_data_rel, spatial_data_rel, keys)
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# plot_data(data, keys)
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# plot_data(get_data_distance(store,relative_values=False), keys)
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# for analyzers in analyzers:
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# if analyzers.name() in ["LogEntryCount", "ActionSequenceAnalyzer"]:
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Clemens Klug