Add tests for proximity.

rapids
junos 2021-08-17 10:51:51 +02:00
parent 3821314dd9
commit 4d73b9d5ff
3 changed files with 99 additions and 1 deletions

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@ -0,0 +1,63 @@
id,timestamp,device_id,_id,double_proximity,accuracy,label,dateTime
39017,1565802024310,f67354f7-d675-4b76-80c8-123cc4744a5b,2962,0,3,,2019-08-14T17:00:24Z
39018,1565802051075,f67354f7-d675-4b76-80c8-123cc4744a5b,2963,0,3,,2019-08-14T17:00:51Z
39019,1565802051354,f67354f7-d675-4b76-80c8-123cc4744a5b,2964,8,3,,2019-08-14T17:00:51Z
39089,1565010418305,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,51,5,3,,2019-08-05T13:06:58Z
39090,1565010772188,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,52,5,3,,2019-08-05T13:12:52Z
39091,1565012334450,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,53,5,3,,2019-08-05T13:38:54Z
39092,1565013000660,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,54,5,3,,2019-08-05T13:50:00Z
39093,1565022742894,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,55,0,3,,2019-08-05T16:32:22Z
39094,1565089295906,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,56,5,3,,2019-08-06T11:01:35Z
39095,1565096030817,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,57,0,3,,2019-08-06T12:53:50Z
39096,1565096367694,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,58,5,3,,2019-08-06T12:59:27Z
39097,1565096408570,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,59,5,3,,2019-08-06T13:00:08Z
39098,1565116821528,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,60,5,3,,2019-08-06T18:40:21Z
39099,1565131345333,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,61,0,3,,2019-08-06T22:42:25Z
39100,1565131375072,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,62,5,3,,2019-08-06T22:42:55Z
39101,1565131386353,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,63,0,3,,2019-08-06T22:43:06Z
39102,1565131389213,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,64,5,3,,2019-08-06T22:43:09Z
39103,1565131448891,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,65,0,3,,2019-08-06T22:44:08Z
39104,1565131454131,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,66,5,3,,2019-08-06T22:44:14Z
39105,1565176143083,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,67,0,3,,2019-08-07T11:09:03Z
39106,1565179569310,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,68,5,3,,2019-08-07T12:06:09Z
39107,1565180699173,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,69,5,3,,2019-08-07T12:24:59Z
39108,1565182538578,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,70,5,3,,2019-08-07T12:55:38Z
39109,1565192592776,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,71,0,3,,2019-08-07T15:43:12Z
39110,1565216023797,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,72,5,3,,2019-08-07T22:13:43Z
39111,1565248358647,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,73,0,3,,2019-08-08T07:12:38Z
39112,1565275859157,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,74,5,3,,2019-08-08T14:50:59Z
39113,1565304201431,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,75,0,3,,2019-08-08T22:43:21Z
39114,1565304229591,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,76,5,3,,2019-08-08T22:43:49Z
39115,1565304262050,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,77,0,3,,2019-08-08T22:44:22Z
39116,1565613142970,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,78,5,3,,2019-08-12T12:32:22Z
39117,1565618266531,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,79,5,3,,2019-08-12T13:57:46Z
39118,1565618410488,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,80,5,3,,2019-08-12T14:00:10Z
39119,1565618704942,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,81,5,3,,2019-08-12T14:05:04Z
39120,1565619005315,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,82,5,3,,2019-08-12T14:10:05Z
39121,1565619405904,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,83,5,3,,2019-08-12T14:16:45Z
39122,1565619678037,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,84,5,3,,2019-08-12T14:21:18Z
39123,1565621206713,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,85,5,3,,2019-08-12T14:46:46Z
39124,1565626622125,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,86,5,3,,2019-08-12T16:17:02Z
39125,1565684876738,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,87,5,3,,2019-08-13T08:27:56Z
39126,1565684956618,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,88,5,3,,2019-08-13T08:29:16Z
39127,1565684965647,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,89,5,3,,2019-08-13T08:29:25Z
39128,1565685092246,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,90,5,3,,2019-08-13T08:31:32Z
39129,1565685136337,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,91,5,3,,2019-08-13T08:32:16Z
39130,1565685147453,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,92,5,3,,2019-08-13T08:32:27Z
39131,1565685212523,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,93,5,3,,2019-08-13T08:33:32Z
39132,1565703397796,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,94,0,3,,2019-08-13T13:36:37Z
39133,1565776203019,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,95,5,3,,2019-08-14T09:50:03Z
39134,1565776434168,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,96,5,3,,2019-08-14T09:53:54Z
39135,1565776435231,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,97,0,3,,2019-08-14T09:53:55Z
39136,1565776443368,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,98,5,3,,2019-08-14T09:54:03Z
39137,1565779277109,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,99,0,3,,2019-08-14T10:41:17Z
39138,1565780016327,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,100,5,3,,2019-08-14T10:53:36Z
39139,1565780027437,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,101,5,3,,2019-08-14T10:53:47Z
39140,1565783470934,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,102,5,3,,2019-08-14T11:51:10Z
39141,1565783801540,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,103,0,3,,2019-08-14T11:56:41Z
39142,1565783802120,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,104,5,3,,2019-08-14T11:56:42Z
39143,1565783861495,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,105,5,3,,2019-08-14T11:57:41Z
39144,1565785318762,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,106,0,3,,2019-08-14T12:21:58Z
39145,1565785319346,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,107,5,3,,2019-08-14T12:21:59Z
39146,1565960121019,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,108,5,3,,2019-08-16T12:55:21Z
39147,1565960226792,fdb06d4a-ee6e-4336-9a96-fc8d2715f243,109,5,3,,2019-08-16T12:57:06Z
1 id timestamp device_id _id double_proximity accuracy label dateTime
2 39017 1565802024310 f67354f7-d675-4b76-80c8-123cc4744a5b 2962 0 3 2019-08-14T17:00:24Z
3 39018 1565802051075 f67354f7-d675-4b76-80c8-123cc4744a5b 2963 0 3 2019-08-14T17:00:51Z
4 39019 1565802051354 f67354f7-d675-4b76-80c8-123cc4744a5b 2964 8 3 2019-08-14T17:00:51Z
5 39089 1565010418305 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 51 5 3 2019-08-05T13:06:58Z
6 39090 1565010772188 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 52 5 3 2019-08-05T13:12:52Z
7 39091 1565012334450 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 53 5 3 2019-08-05T13:38:54Z
8 39092 1565013000660 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 54 5 3 2019-08-05T13:50:00Z
9 39093 1565022742894 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 55 0 3 2019-08-05T16:32:22Z
10 39094 1565089295906 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 56 5 3 2019-08-06T11:01:35Z
11 39095 1565096030817 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 57 0 3 2019-08-06T12:53:50Z
12 39096 1565096367694 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 58 5 3 2019-08-06T12:59:27Z
13 39097 1565096408570 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 59 5 3 2019-08-06T13:00:08Z
14 39098 1565116821528 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 60 5 3 2019-08-06T18:40:21Z
15 39099 1565131345333 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 61 0 3 2019-08-06T22:42:25Z
16 39100 1565131375072 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 62 5 3 2019-08-06T22:42:55Z
17 39101 1565131386353 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 63 0 3 2019-08-06T22:43:06Z
18 39102 1565131389213 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 64 5 3 2019-08-06T22:43:09Z
19 39103 1565131448891 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 65 0 3 2019-08-06T22:44:08Z
20 39104 1565131454131 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 66 5 3 2019-08-06T22:44:14Z
21 39105 1565176143083 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 67 0 3 2019-08-07T11:09:03Z
22 39106 1565179569310 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 68 5 3 2019-08-07T12:06:09Z
23 39107 1565180699173 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 69 5 3 2019-08-07T12:24:59Z
24 39108 1565182538578 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 70 5 3 2019-08-07T12:55:38Z
25 39109 1565192592776 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 71 0 3 2019-08-07T15:43:12Z
26 39110 1565216023797 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 72 5 3 2019-08-07T22:13:43Z
27 39111 1565248358647 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 73 0 3 2019-08-08T07:12:38Z
28 39112 1565275859157 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 74 5 3 2019-08-08T14:50:59Z
29 39113 1565304201431 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 75 0 3 2019-08-08T22:43:21Z
30 39114 1565304229591 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 76 5 3 2019-08-08T22:43:49Z
31 39115 1565304262050 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 77 0 3 2019-08-08T22:44:22Z
32 39116 1565613142970 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 78 5 3 2019-08-12T12:32:22Z
33 39117 1565618266531 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 79 5 3 2019-08-12T13:57:46Z
34 39118 1565618410488 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 80 5 3 2019-08-12T14:00:10Z
35 39119 1565618704942 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 81 5 3 2019-08-12T14:05:04Z
36 39120 1565619005315 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 82 5 3 2019-08-12T14:10:05Z
37 39121 1565619405904 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 83 5 3 2019-08-12T14:16:45Z
38 39122 1565619678037 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 84 5 3 2019-08-12T14:21:18Z
39 39123 1565621206713 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 85 5 3 2019-08-12T14:46:46Z
40 39124 1565626622125 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 86 5 3 2019-08-12T16:17:02Z
41 39125 1565684876738 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 87 5 3 2019-08-13T08:27:56Z
42 39126 1565684956618 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 88 5 3 2019-08-13T08:29:16Z
43 39127 1565684965647 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 89 5 3 2019-08-13T08:29:25Z
44 39128 1565685092246 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 90 5 3 2019-08-13T08:31:32Z
45 39129 1565685136337 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 91 5 3 2019-08-13T08:32:16Z
46 39130 1565685147453 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 92 5 3 2019-08-13T08:32:27Z
47 39131 1565685212523 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 93 5 3 2019-08-13T08:33:32Z
48 39132 1565703397796 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 94 0 3 2019-08-13T13:36:37Z
49 39133 1565776203019 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 95 5 3 2019-08-14T09:50:03Z
50 39134 1565776434168 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 96 5 3 2019-08-14T09:53:54Z
51 39135 1565776435231 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 97 0 3 2019-08-14T09:53:55Z
52 39136 1565776443368 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 98 5 3 2019-08-14T09:54:03Z
53 39137 1565779277109 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 99 0 3 2019-08-14T10:41:17Z
54 39138 1565780016327 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 100 5 3 2019-08-14T10:53:36Z
55 39139 1565780027437 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 101 5 3 2019-08-14T10:53:47Z
56 39140 1565783470934 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 102 5 3 2019-08-14T11:51:10Z
57 39141 1565783801540 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 103 0 3 2019-08-14T11:56:41Z
58 39142 1565783802120 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 104 5 3 2019-08-14T11:56:42Z
59 39143 1565783861495 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 105 5 3 2019-08-14T11:57:41Z
60 39144 1565785318762 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 106 0 3 2019-08-14T12:21:58Z
61 39145 1565785319346 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 107 5 3 2019-08-14T12:21:59Z
62 39146 1565960121019 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 108 5 3 2019-08-16T12:55:21Z
63 39147 1565960226792 fdb06d4a-ee6e-4336-9a96-fc8d2715f243 109 5 3 2019-08-16T12:57:06Z

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@ -5,6 +5,8 @@ import pandas as pd
from config.models import Participant, Proximity
from setup import db_engine, session
FEATURES_PROXIMITY = ["freq_prox_near", "prop_prox_near"]
def get_proximity_data(usernames: Collection) -> pd.DataFrame:
"""
@ -56,7 +58,7 @@ def recode_proximity(df_proximity: pd.DataFrame) -> pd.DataFrame:
def count_proximity(
df_proximity: pd.DataFrame, group_by: Collection = ["participant_id"]
df_proximity: pd.DataFrame, group_by: Collection = None
) -> pd.DataFrame:
"""
The function counts how many times a "near" value occurs in proximity
@ -75,6 +77,8 @@ def count_proximity(
df_proximity_features: pd.DataFrame
A dataframe with the count of "near" proximity values and their relative count.
"""
if group_by is None:
group_by = ["participant_id"]
if "bool_prox_near" not in df_proximity:
df_proximity = recode_proximity(df_proximity)
df_proximity["bool_prox_far"] = ~df_proximity["bool_prox_near"]

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@ -0,0 +1,31 @@
import unittest
from features.proximity import *
class ProximityFeatures(unittest.TestCase):
df_proximity = pd.DataFrame()
df_proximity_recoded = pd.DataFrame()
df_proximity_features = pd.DataFrame()
@classmethod
def setUpClass(cls) -> None:
cls.df_proximity = pd.read_csv("../data/example_proximity.csv")
cls.df_proximity["participant_id"] = 99
def test_recode_proximity(self):
self.df_proximity_recoded = recode_proximity(self.df_proximity)
self.assertIn("bool_prox_near", self.df_proximity_recoded)
# Is the recoded column present?
self.assertIn(True, self.df_proximity_recoded.bool_prox_near)
# Are there "near" values in the data?
self.assertIn(False, self.df_proximity_recoded.bool_prox_near)
# Are there "far" values in the data?
def test_count_proximity(self):
self.df_proximity_recoded = recode_proximity(self.df_proximity)
self.df_proximity_features = count_proximity(self.df_proximity_recoded)
print(self.df_proximity_features.columns)
self.assertCountEqual(
self.df_proximity_features.columns.to_list(), FEATURES_PROXIMITY
)