Getting Started with Strym¶

[1]:

import strym
from strym import strymread
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import urllib.request

/home/ivory/anaconda3/envs/dbn/lib/python3.7/site-packages/statsmodels/tools/_testing.py:19: FutureWarning: pandas.util.testing is deprecated. Use the functions in the public API at pandas.testing instead.
  import pandas.util.testing as tm

Loading BokehJS ...

[2]:

dbcfile = '/home/ivory/VersionControl/Jmscslgroup/strym/examples/newToyotacode.dbc'

[3]:

%%time
folder = "/home/ivory/CyverseData/JmscslgroupData/PandaData/2020_08_13/"
file= "2020-08-13-13-26-45_2T3Y1RFV8KC014025_CAN_Messages.csv"
r =strymread(csvfile=folder + file, dbcfile = dbcfile, createdb = True, verbose=False)

UNIQUE constraint failed: RAW_CAN.Clock, RAW_CAN.Bus, RAW_CAN.MessageID
CPU times: user 21.6 s, sys: 1.02 s, total: 22.6 s
Wall time: 16.7 s

[4]:

r.dataframe

[4]:

	Time	Bus	MessageID	Message	MessageLength
Clock
2020-08-13 20:26:46.108451843	1.597350e+09	2	835	0000430000000091	8.0
2020-08-13 20:26:46.108451843	1.597350e+09	0	835	0000430000000091	8.0
2020-08-13 20:26:46.108451843	1.597350e+09	2	705	08ff86ff8cbc009f	8.0
2020-08-13 20:26:46.108451843	1.597350e+09	0	705	08ff86ff8cbc009f	8.0
2020-08-13 20:26:46.108793974	1.597350e+09	2	452	0383260838007f38	8.0
...	...	...	...	...	...
2020-08-13 20:37:17.848950863	1.597351e+09	1	441	de7ffc00000ffc26	8.0
2020-08-13 20:37:17.849765062	1.597351e+09	1	442	de7ffc00000ffc27	8.0
2020-08-13 20:37:17.849765062	1.597351e+09	2	401	e2ff8830646400fb	8.0
2020-08-13 20:37:17.849765062	1.597351e+09	0	401	e2ff8830646400fb	8.0
2020-08-13 20:37:17.850608110	1.597351e+09	1	443	de7ffc00000ffc28	8.0

2509598 rows × 5 columns

[5]:

r.dataframe.head()

[5]:

	Time	Bus	MessageID	Message	MessageLength
Clock
2020-08-13 20:26:46.108451843	1.597350e+09	2	835	0000430000000091	8.0
2020-08-13 20:26:46.108451843	1.597350e+09	0	835	0000430000000091	8.0
2020-08-13 20:26:46.108451843	1.597350e+09	2	705	08ff86ff8cbc009f	8.0
2020-08-13 20:26:46.108451843	1.597350e+09	0	705	08ff86ff8cbc009f	8.0
2020-08-13 20:26:46.108793974	1.597350e+09	2	452	0383260838007f38	8.0

Get the count of all messages¶

[6]:

count = r.count(plot = True)
count

[6]:

	MessageID	Counts_Bus_0	Counts_Bus_1	Counts_Bus_2	TotalCount
36	36	31626	0	31626	63252
37	37	63252	0	63252	126504
170	170	63252	0	63252	126504
180	180	31626	0	31626	63252
186	186	21084	0	21084	42168
...	...	...	...	...	...
2008	2008	48	0	48	96
2015	2015	24	0	24	48
2016	2016	3	0	3	6
2024	2024	26	0	26	52
2025	2025	17	0	17	34

200 rows × 5 columns

Reading a signal from a particular message ID¶

[7]:

msg180 = r.get_ts(msg=180, signal=1)

[8]:

msg180

[8]:

	Time	Message	Bus
Clock
2020-08-13 20:26:46.109022141	1.597350e+09	0.0	2
2020-08-13 20:26:46.109022141	1.597350e+09	0.0	0
2020-08-13 20:26:46.111299038	1.597350e+09	0.0	2
2020-08-13 20:26:46.111299038	1.597350e+09	0.0	0
2020-08-13 20:26:46.113986015	1.597350e+09	0.0	2
...	...	...	...
2020-08-13 20:37:17.794481993	1.597351e+09	0.0	0
2020-08-13 20:37:17.814836025	1.597351e+09	0.0	2
2020-08-13 20:37:17.815034866	1.597351e+09	0.0	0
2020-08-13 20:37:17.834714174	1.597351e+09	0.0	2
2020-08-13 20:37:17.834714174	1.597351e+09	0.0	0

63252 rows × 3 columns

Plotting the signal¶

[9]:

strymread.plt_ts(msg180, title="Message msg180, Signal ID 1")

Quality Check of Data Rate of Particular Message¶

[15]:

ts_speed = r.speed()
strymread.ranalyze(msg180)

Analyzing Timestamp and Data Rate of Timeseries
Interquartile Range of Rate for Timeseries is 1.3397845087453533

From above plots, we can see that most message were received within sampling time of 0.02s or 50 Hz.

[12]:

resampled180 = strymread.resample(msg180, rate = 50)
strymread.ranalyze(resampled180)

Analyzing Timestamp and Data Rate of Timeseries
Interquartile Range of Rate for Timeseries is 0.0005959978496221652

[13]:

strymread.plt_ts(resampled180)