-
Notifications
You must be signed in to change notification settings - Fork 1
/
behavior_2016-10.py
153 lines (141 loc) · 7.12 KB
/
behavior_2016-10.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
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
import numpy as np
import nept
import measurements as m
from core import Experiment, Rat, TrialEpoch
cached_data = True
for plot_extended in [False]:
extended_sessions = ['!2016-12-06', '!2016-12-07a', '!2016-12-07b', '!2016-12-08', '!2016-12-09']
extended_rats = [Rat('5', group="1"),
Rat("8", group="2")]
all_rats = [
Rat('1', group="1"),
Rat('2', group="2"),
Rat('3', group="1"),
Rat('4', group="2"),
Rat('5', group="1"),
Rat('6', group="2"),
Rat('7', group="1"),
Rat('8', group="2")
]
magazine = ['!2016-10-18']
ignore = magazine + ['!2016-10-19a1']
expt = Experiment(
name="201610",
cache_key="epoch",
plot_key="",
trial_epochs=[
TrialEpoch("mags", start_idx=1, stop_idx=2),
TrialEpoch("baseline", start_idx=4, duration=-10),
TrialEpoch("baseline", start_idx=6, duration=-10),
TrialEpoch("light1", start_idx=4, stop_idx=5),
TrialEpoch("light2", start_idx=6, stop_idx=7),
TrialEpoch("sound1", start_idx=8, stop_idx=9),
TrialEpoch("sound2", start_idx=10, stop_idx=11),
],
measurements=[m.Duration(), m.Count(), m.Latency(), m.AtLeastOne()],
rats=[extended_rats if plot_extended else all_rats][0],
ignore_sessions=[ignore if plot_extended else ignore + extended_sessions][0],
)
colours = {'baseline, ': '#252525',
'light, rewarded': '#1f77b4',
'light, unrewarded': '#aec7e8',
'light1, rewarded': '#1f77b4',
'light1, unrewarded': '#aec7e8',
'light2, rewarded': '#1f77b4',
'light2, unrewarded': '#aec7e8',
'sound, rewarded': '#2ca02c',
'sound, unrewarded': '#98df8a',
'sound1, rewarded': '#2ca02c',
'sound1, unrewarded': '#98df8a',
'sound2, rewarded': '#e377c2',
'sound2, unrewarded': '#f7b6d2',
}
def add_datapoints(session, data, rat):
def add_data(cue, trial=None, n_missing=0):
if trial is not None:
meta = {
"cue_type": cue[:-1],
"trial_type": trial[-1],
"rewarded": "rewarded" if trial[-1] in ("2", "4") else "unrewarded",
"cue": cue,
}
trial = data[trial]
cue = data[cue]
session.add_epoch_data(rat.rat_id, trial.intersect(cue), meta, n_missing)
else:
meta = {
"cue_type": cue,
"trial_type": "",
"rewarded": "",
"cue": cue,
}
session.add_epoch_data(rat.rat_id, data[cue], meta, n_missing)
def add_data_notrials(feature, target, trial_num, delay=5.02, n_missing=0):
feature_starts = []
feature_stops = []
target_starts = []
target_stops = []
for feature_start, feature_stop in zip(data[feature].starts, data[feature].stops):
for target_start, target_stop in zip(data[target].starts, data[target].stops):
if np.allclose(target_start - feature_stop, delay):
meta_feature = {"cue_type": feature[:-1],
"trial_type": trial_num,
"rewarded": "rewarded" if trial_num in ("2", "4") else "unrewarded",
"cue": feature,
}
meta_target = {"cue_type": target[:-1],
"trial_type": trial_num,
"rewarded": "rewarded" if trial_num in ("2", "4") else "unrewarded",
"cue": target,
}
feature_starts = feature_starts + [feature_start]
feature_stops = feature_stops + [feature_stop]
target_starts = target_starts + [target_start]
target_stops = target_stops + [target_stop]
session.add_epoch_data(rat.rat_id, nept.Epoch([feature_starts, feature_stops]), meta_feature, n_missing)
session.add_epoch_data(rat.rat_id, nept.Epoch([target_starts, target_stops]), meta_target, n_missing)
if session.number == 1:
if rat.group == "1":
add_data_notrials("light1", "sound2", trial_num="1", n_missing=1)
add_data_notrials("light1", "sound1", trial_num="2", n_missing=2)
add_data_notrials("light2", "sound1", trial_num="3", n_missing=2)
add_data_notrials("light2", "sound2", trial_num="4", n_missing=1)
add_data("baseline", n_missing=6)
elif rat.group == "2":
add_data_notrials("light1", "sound2", trial_num="4", n_missing=1)
add_data_notrials("light1", "sound1", trial_num="3", n_missing=2)
add_data_notrials("light2", "sound1", trial_num="2", n_missing=2)
add_data_notrials("light2", "sound2", trial_num="1", n_missing=1)
add_data("baseline", n_missing=6)
else:
if rat.group == "1":
add_data_notrials("light1", "sound2", trial_num="1")
add_data_notrials("light1", "sound1", trial_num="2")
add_data_notrials("light2", "sound1", trial_num="3")
add_data_notrials("light2", "sound2", trial_num="4")
add_data("baseline")
elif rat.group == "2":
add_data_notrials("light1", "sound2", trial_num="4")
add_data_notrials("light1", "sound1", trial_num="3")
add_data_notrials("light2", "sound1", trial_num="2")
add_data_notrials("light2", "sound2", trial_num="1")
add_data("baseline")
expt.add_datapoints = add_datapoints
# if plot_extended:
# change = [35.5, 46.5, 51.5]
# expt.analyze(cached_data=cached_data)
# for rat in expt.rats:
# expt.plot_rat(rat, change=change, colours=colours, by_outcome=True)
# expt.plot_rat(rat, change=change, colours=colours, by_outcome=False)
# expt.plot_rat(rat, measure="Duration", change=change, colours=colours)
# expt.plot_rat(rat, measure="Count", change=change, colours=colours)
# else:
# change = [35.5, 46.5]
# expt.plot_all(cached_data=cached_data, change=change, colours=colours)
# expt.plot_all(measure="Duration", cached_data=cached_data, change=change, colours=colours)
# expt.plot_all(measure="Count", cached_data=cached_data, change=change, colours=colours)
expt.analyze(cached_data=cached_data)
for rat in expt.rats:
expt.plot_rat(rat, measure="Duration", colours=colours, by_outcome=True)
expt.plot_rat(rat, measure="Duration", colours=colours, by_outcome=False)
expt.plot_group(expt.rats, label="all-rats", measure="Duration", colours=colours, by_outcome=True)