/
GeneralProcessing.py
125 lines (94 loc) · 4.63 KB
/
GeneralProcessing.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import os
import joblib
from utils import normalize_MPU9250_data, split_df, get_intervals_from_moments, EventIntervals
from GeneralAnalyser import GeneralAnalyser, plot_measurements
plt.interactive(True)
pd.options.display.max_columns = 15
pic_prefix = 'pic/'
sessions_dict = joblib.load('data/sessions_dict')
# sessions_dict = joblib.load('data/data_dict')
gamedata_dict = joblib.load('data/gamedata_dict_old')
# gamedata_dict.update(gamedata_dict_update)
sensors_columns_dict = {
'hrm': ['hrm'],
'datalog': ['resistance', 'muscle_activity'],
# 'datalog': ['muscle_activity'],
'envibox': ['co2', 'temperature', 'humidity'],
'eyetracker': ['gaze_x', 'gaze_y'],
'mxy': ['mouse_dx', 'mouse_dy'],
'schairlog': ['acc_x', 'acc_y', 'acc_z', 'gyro_x', 'gyro_y', 'gyro_z'],
}
total_len = sum([len(value) for value in sensors_columns_dict.values()])
sensors_list = list(sensors_columns_dict.keys())
sensors_columns_list = []
for sensor in sensors_columns_dict:
for column in sensors_columns_dict[sensor]:
sensors_columns_list.append([sensor, column])
for session_id, session_data_dict in sessions_dict.items():
df_dict = {}
if not set(sensors_list).issubset(set(session_data_dict.keys())):
print("not set(sensors_list).issubset(set(session_data_dict.keys()))")
### If not all the sensors provided
continue # TODO: THIS IS DANGEROUS AND SHOULD BE UNCOMMENTED BACK
# pass
if session_id not in gamedata_dict:
continue
print("Processing!")
moments_kills = gamedata_dict[session_id]['times_kills']
moments_death = gamedata_dict[session_id]['times_is_killed']
duration = 1
# intervals_shootout = gamedata_dict[session_id]['shootout_times_start_end']
intervals_kills = get_intervals_from_moments(moments_kills, interval_start=-duration, interval_end=duration)
intervals_death = get_intervals_from_moments(moments_death, interval_start=-duration, interval_end=duration)
# event_intervals_shootout = EventIntervals(intervals_list=intervals_shootout, label='shootouts', color='blue')
event_intervals_kills = EventIntervals(intervals_list=intervals_kills, label='kills', color='limegreen')
event_intervals_death = EventIntervals(intervals_list=intervals_death, label='deaths', color='red')
# events_intervals_list = [event_intervals_shootout, event_intervals_kills, event_intervals_death]
events_intervals_list = [event_intervals_kills, event_intervals_death]
for sensor_name in sensors_columns_dict:
df = session_data_dict[sensor_name].copy()
# if sensor_name == 'schairlog':
# chair_features = get_chair_features(df, session_id) # TMP
# chair_features_list.append(chair_features)
# ss = StandardScaler()
# # df.values = ss.fit_transform(df.values)
# df.loc[:, sensors_columns_dict[sensor_name]] = ss.fit_transform(df.loc[:, sensors_columns_dict[sensor_name]])
# ### WARNING: it is CUSTOM PART
# if sensor_name == 'schairlog':
# chair_analyser = GeneralAnalyser(
# df,
# pic_prefix=pic_prefix,
# sensor_name='Chair', # Manual assignment
# session_id=session_id,
# events_intervals_list=events_intervals_list,
# interval=interval,
# reaction_multiplier=reaction_multiplier,
# )
# # chair_analyser.get_floating_features() # Need to be refactored
# chair_analyser._append_floating_features(interval=interval)
#
# for column in sensors_columns_dict[sensor_name]:
# analyser_column_pairs_list.append([chair_analyser, column])
### VISUALIZATION
analyser_column_pairs_list = []
for sensor_name in sensors_columns_dict:
df = session_data_dict[sensor_name]
analyser = GeneralAnalyser(df, pic_prefix=pic_prefix, sensor_name=sensor_name, session_id=session_id)
for column in sensors_columns_dict[sensor_name]:
analyser_column_pairs_list.append([analyser, column])
plot_measurements(
analyser_column_pairs_list=analyser_column_pairs_list,
pic_prefix=pic_prefix,
session_id=session_id,
event_intervals_list=events_intervals_list,
n_rows=4, # TODO: automatically adjust number of rows and cols
n_cols=4,
figsize=(21, 8),
plot_suptitle=False,
alpha=0.8,
alpha_background=0.5,
)
# general_analyser.plot_measurements_timeline(column_name=sensor_name, intervals_dicts_list=intervals_dicts_list, alpha=0.9)