You can create and MTC Device Class by specifying a Delimited MTConnect Data (DMTCD) file and a devices.XML
create_mtc_device_from_dmtcdThe usage is straightforward. The user can provide ther path to the Delimited MTConnect Data(DMTCD) file and the devices XML and the package reads the files and packages the data into an easily usable MTCDevice S4 Data Structure.
require(mtconnectR)## Loading required package: mtconnectRfile_path_dmtcd = "testdata/dataExtraction/test_dmtcd.log"
file_path_xml = "testdata/dataExtraction/test_devices.xml"
device_name = "test_device"
mtc_device = create_mtc_device_from_dmtcd(
system.file(file_path_dmtcd, package = "mtconnectR"),
system.file(file_path_xml, package = "mtconnectR"),
device_name)## Reading Delimted MTC data...##
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|=================================================================| 100%## 20.48% data contextualized successfuly!A few convenience functions are provided to help the user with the MTC Classes. They are:
This function is used to get a single MTC data item from the MTC device class. If no parameters are provided, the first data item is returned. The user can optionally enter either a character string - in which case the data items whose paths match the character string are returned or one or more indexes. Please note that if the pattern matches more than one data item, a list of MTC Data Items is returned.
# Get the first data item in the list
mtc_data_item = getDataItem(mtc_device)
print(mtc_data_item)## An object of class "MTCDataItem"
## Slot "data":
## timestamp value
## 1 2014-07-15 07:04:25.608 100
##
## Slot "metadata":
## $category
## [1] "SAMPLE"
##
## $xpath
## [1] "test_device<Device>:Frapidovr<PATH_FEEDRATE-OVERRIDE>"# Get all the data items with "Xabs" in the name
mtc_data_item = getDataItem(mtc_device, "Xabs")
print(mtc_data_item)## An object of class "MTCDataItem"
## Slot "data":
## timestamp value
## 1 2014-07-15 07:04:25.608 8.26262
## 2 2014-07-15 07:04:25.788 4.61391
## 3 2014-07-15 07:04:29.983 8.14832
## 4 2014-07-15 07:04:34.210 56.67629
## 5 2014-07-15 07:04:38.526 41.27500
## 6 2014-07-15 07:04:42.862 38.94074
## 7 2014-07-15 07:04:47.049 -19.75612
## 8 2014-07-15 07:04:51.286 -20.20316
## 9 2014-07-15 07:04:55.492 -21.00961
## 10 2014-07-15 07:04:59.729 -1.99644
## 11 2014-07-15 07:05:03.914 1.98247
## 12 2014-07-15 07:05:08.141 29.57195
## 13 2014-07-15 07:05:12.328 -23.00986
## 14 2014-07-15 07:05:16.513 276.65426
## 15 2014-07-15 07:05:20.710 56.94934
## 16 2014-07-15 07:05:24.875 32.88030
## 17 2014-07-15 07:05:29.092 -51.92649
##
## Slot "metadata":
## $category
## [1] "SAMPLE"
##
## $xpath
## [1] "test_device<Device>:Xabs<POSITION-ACTUAL>"# Get the data item with the 5th index
mtc_data_item = getDataItem(mtc_device, 5)
print(mtc_data_item)## An object of class "MTCDataItem"
## Slot "data":
## timestamp value
## 1 2014-07-15 07:04:25.608 238.02594
## 2 2014-07-15 07:04:25.788 240.46434
## 3 2014-07-15 07:04:29.983 234.98429
## 4 2014-07-15 07:04:34.210 280.67762
## 5 2014-07-15 07:04:38.526 267.71600
## 6 2014-07-15 07:04:42.862 269.86738
## 7 2014-07-15 07:04:47.049 278.72436
## 8 2014-07-15 07:04:51.286 211.29117
## 9 2014-07-15 07:04:55.492 208.65973
## 10 2014-07-15 07:04:59.729 213.84387
## 11 2014-07-15 07:05:03.914 272.26514
## 12 2014-07-15 07:05:08.141 244.55374
## 13 2014-07-15 07:05:12.328 212.84184
## 14 2014-07-15 07:05:16.513 465.69630
## 15 2014-07-15 07:05:20.710 243.04752
## 16 2014-07-15 07:05:24.875 272.85950
## 17 2014-07-15 07:05:29.092 263.14527
##
## Slot "metadata":
## $category
## [1] "SAMPLE"
##
## $xpath
## [1] "test_device<Device>:Yabs<POSITION-ACTUAL>"# Get all data items with path matching the string 'POSITION'
mtc_data_item_list = getDataItem(mtc_device, "POSITION")
print(mtc_data_item)## An object of class "MTCDataItem"
## Slot "data":
## timestamp value
## 1 2014-07-15 07:04:25.608 238.02594
## 2 2014-07-15 07:04:25.788 240.46434
## 3 2014-07-15 07:04:29.983 234.98429
## 4 2014-07-15 07:04:34.210 280.67762
## 5 2014-07-15 07:04:38.526 267.71600
## 6 2014-07-15 07:04:42.862 269.86738
## 7 2014-07-15 07:04:47.049 278.72436
## 8 2014-07-15 07:04:51.286 211.29117
## 9 2014-07-15 07:04:55.492 208.65973
## 10 2014-07-15 07:04:59.729 213.84387
## 11 2014-07-15 07:05:03.914 272.26514
## 12 2014-07-15 07:05:08.141 244.55374
## 13 2014-07-15 07:05:12.328 212.84184
## 14 2014-07-15 07:05:16.513 465.69630
## 15 2014-07-15 07:05:20.710 243.04752
## 16 2014-07-15 07:05:24.875 272.85950
## 17 2014-07-15 07:05:29.092 263.14527
##
## Slot "metadata":
## $category
## [1] "SAMPLE"
##
## $xpath
## [1] "test_device<Device>:Yabs<POSITION-ACTUAL>"Displays a quick summary of the MTC Object with the following
print(summary(mtc_device))## Length Class Mode
## 1 MTCDevice S4print(summary(mtc_data_item))## Length Class Mode
## 1 MTCDataItem S4If the user wants to get all the data from an MTC Object into a data.frame for further analysis, they can use the getData method. It converts all the time series data into a data.frame object.
# Get Data from a MTC Device Class
mtc_device_data = getData(mtc_device)
print(mtc_device_data)## data_item_name
## 1 test_device<Device>:Frapidovr<PATH_FEEDRATE-OVERRIDE>
## 2 test_device<Device>:Sovr<SPINDLE_SPEED-OVERRIDE>
## 3 test_device<Device>:Xabs<POSITION-ACTUAL>
## 4 test_device<Device>:Xabs<POSITION-ACTUAL>
## 5 test_device<Device>:Xabs<POSITION-ACTUAL>
## 6 test_device<Device>:Xabs<POSITION-ACTUAL>
## 7 test_device<Device>:Xabs<POSITION-ACTUAL>
## 8 test_device<Device>:Xabs<POSITION-ACTUAL>
## 9 test_device<Device>:Xabs<POSITION-ACTUAL>
## 10 test_device<Device>:Xabs<POSITION-ACTUAL>
## 11 test_device<Device>:Xabs<POSITION-ACTUAL>
## 12 test_device<Device>:Xabs<POSITION-ACTUAL>
## 13 test_device<Device>:Xabs<POSITION-ACTUAL>
## 14 test_device<Device>:Xabs<POSITION-ACTUAL>
## 15 test_device<Device>:Xabs<POSITION-ACTUAL>
## 16 test_device<Device>:Xabs<POSITION-ACTUAL>
## 17 test_device<Device>:Xabs<POSITION-ACTUAL>
## 18 test_device<Device>:Xabs<POSITION-ACTUAL>
## 19 test_device<Device>:Xabs<POSITION-ACTUAL>
## 20 test_device<Device>:Xload<LOAD>
## 21 test_device<Device>:Xload<LOAD>
## 22 test_device<Device>:Xload<LOAD>
## 23 test_device<Device>:Xload<LOAD>
## 24 test_device<Device>:Xload<LOAD>
## 25 test_device<Device>:Xload<LOAD>
## 26 test_device<Device>:Xload<LOAD>
## 27 test_device<Device>:Xload<LOAD>
## 28 test_device<Device>:Yabs<POSITION-ACTUAL>
## 29 test_device<Device>:Yabs<POSITION-ACTUAL>
## 30 test_device<Device>:Yabs<POSITION-ACTUAL>
## 31 test_device<Device>:Yabs<POSITION-ACTUAL>
## 32 test_device<Device>:Yabs<POSITION-ACTUAL>
## 33 test_device<Device>:Yabs<POSITION-ACTUAL>
## 34 test_device<Device>:Yabs<POSITION-ACTUAL>
## 35 test_device<Device>:Yabs<POSITION-ACTUAL>
## 36 test_device<Device>:Yabs<POSITION-ACTUAL>
## 37 test_device<Device>:Yabs<POSITION-ACTUAL>
## 38 test_device<Device>:Yabs<POSITION-ACTUAL>
## 39 test_device<Device>:Yabs<POSITION-ACTUAL>
## 40 test_device<Device>:Yabs<POSITION-ACTUAL>
## 41 test_device<Device>:Yabs<POSITION-ACTUAL>
## 42 test_device<Device>:Yabs<POSITION-ACTUAL>
## 43 test_device<Device>:Yabs<POSITION-ACTUAL>
## 44 test_device<Device>:Yabs<POSITION-ACTUAL>
## 45 test_device<Device>:Yload<LOAD>
## 46 test_device<Device>:Yload<LOAD>
## 47 test_device<Device>:Yload<LOAD>
## 48 test_device<Device>:Yload<LOAD>
## 49 test_device<Device>:Yload<LOAD>
## 50 test_device<Device>:Yload<LOAD>
## 51 test_device<Device>:Yload<LOAD>
## timestamp value
## 1 2014-07-15 07:04:25.608 100.00000
## 2 2014-07-15 07:04:25.608 100.00000
## 3 2014-07-15 07:04:25.608 8.26262
## 4 2014-07-15 07:04:25.788 4.61391
## 5 2014-07-15 07:04:29.983 8.14832
## 6 2014-07-15 07:04:34.210 56.67629
## 7 2014-07-15 07:04:38.526 41.27500
## 8 2014-07-15 07:04:42.862 38.94074
## 9 2014-07-15 07:04:47.049 -19.75612
## 10 2014-07-15 07:04:51.286 -20.20316
## 11 2014-07-15 07:04:55.492 -21.00961
## 12 2014-07-15 07:04:59.729 -1.99644
## 13 2014-07-15 07:05:03.914 1.98247
## 14 2014-07-15 07:05:08.141 29.57195
## 15 2014-07-15 07:05:12.328 -23.00986
## 16 2014-07-15 07:05:16.513 276.65426
## 17 2014-07-15 07:05:20.710 56.94934
## 18 2014-07-15 07:05:24.875 32.88030
## 19 2014-07-15 07:05:29.092 -51.92649
## 20 2014-07-15 07:04:25.608 -8.00000
## 21 2014-07-15 07:04:29.983 -2.00000
## 22 2014-07-15 07:04:47.049 10.00000
## 23 2014-07-15 07:04:51.286 -1.00000
## 24 2014-07-15 07:05:03.914 -9.00000
## 25 2014-07-15 07:05:08.141 -17.00000
## 26 2014-07-15 07:05:12.328 6.00000
## 27 2014-07-15 07:05:20.710 -1.00000
## 28 2014-07-15 07:04:25.608 238.02594
## 29 2014-07-15 07:04:25.788 240.46434
## 30 2014-07-15 07:04:29.983 234.98429
## 31 2014-07-15 07:04:34.210 280.67762
## 32 2014-07-15 07:04:38.526 267.71600
## 33 2014-07-15 07:04:42.862 269.86738
## 34 2014-07-15 07:04:47.049 278.72436
## 35 2014-07-15 07:04:51.286 211.29117
## 36 2014-07-15 07:04:55.492 208.65973
## 37 2014-07-15 07:04:59.729 213.84387
## 38 2014-07-15 07:05:03.914 272.26514
## 39 2014-07-15 07:05:08.141 244.55374
## 40 2014-07-15 07:05:12.328 212.84184
## 41 2014-07-15 07:05:16.513 465.69630
## 42 2014-07-15 07:05:20.710 243.04752
## 43 2014-07-15 07:05:24.875 272.85950
## 44 2014-07-15 07:05:29.092 263.14527
## 45 2014-07-15 07:04:25.608 -29.00000
## 46 2014-07-15 07:04:38.526 -24.00000
## 47 2014-07-15 07:04:47.049 -34.00000
## 48 2014-07-15 07:04:51.286 -25.00000
## 49 2014-07-15 07:05:12.328 -20.00000
## 50 2014-07-15 07:05:16.513 -29.00000
## 51 2014-07-15 07:05:29.092 -24.00000# Get Data from a MTC Data item Class
mtc_data_item_data = getData(mtc_data_item)
print(mtc_data_item_data)## timestamp value
## 1 2014-07-15 07:04:25.608 238.02594
## 2 2014-07-15 07:04:25.788 240.46434
## 3 2014-07-15 07:04:29.983 234.98429
## 4 2014-07-15 07:04:34.210 280.67762
## 5 2014-07-15 07:04:38.526 267.71600
## 6 2014-07-15 07:04:42.862 269.86738
## 7 2014-07-15 07:04:47.049 278.72436
## 8 2014-07-15 07:04:51.286 211.29117
## 9 2014-07-15 07:04:55.492 208.65973
## 10 2014-07-15 07:04:59.729 213.84387
## 11 2014-07-15 07:05:03.914 272.26514
## 12 2014-07-15 07:05:08.141 244.55374
## 13 2014-07-15 07:05:12.328 212.84184
## 14 2014-07-15 07:05:16.513 465.69630
## 15 2014-07-15 07:05:20.710 243.04752
## 16 2014-07-15 07:05:24.875 272.85950
## 17 2014-07-15 07:05:29.092 263.14527One common use case for a user doing exploratory analysis is to see how the different data items interact with each other. The long format using getData method is not ideal for this. For this case, we can use the merge function to put all the data into a single time series by merging the data items.
Also, the user can conveniently specify the pattern over which to merge or the indices to merge like case of the getData method. For Example `merge(x, “abc”)’ will merge all the objects that have the the string “abc” in their name to one data frame. If no pattern is provided then all the data items are merged into one.
# merge all the objects that have the string 'POSIT' into one data frame
print(merge(mtc_device, "POSIT"))## timestamp test_device<Device>:Xabs<POSITION-ACTUAL>
## 1 2014-07-15 07:04:25.608 8.26262
## 2 2014-07-15 07:04:25.788 4.61391
## 3 2014-07-15 07:04:29.983 8.14832
## 4 2014-07-15 07:04:34.210 56.67629
## 5 2014-07-15 07:04:38.526 41.27500
## 6 2014-07-15 07:04:42.862 38.94074
## 7 2014-07-15 07:04:47.049 -19.75612
## 8 2014-07-15 07:04:51.286 -20.20316
## 9 2014-07-15 07:04:55.492 -21.00961
## 10 2014-07-15 07:04:59.729 -1.99644
## 11 2014-07-15 07:05:03.914 1.98247
## 12 2014-07-15 07:05:08.141 29.57195
## 13 2014-07-15 07:05:12.328 -23.00986
## 14 2014-07-15 07:05:16.513 276.65426
## 15 2014-07-15 07:05:20.710 56.94934
## 16 2014-07-15 07:05:24.875 32.88030
## 17 2014-07-15 07:05:29.092 -51.92649
## test_device<Device>:Yabs<POSITION-ACTUAL>
## 1 238.02594
## 2 240.46434
## 3 234.98429
## 4 280.67762
## 5 267.71600
## 6 269.86738
## 7 278.72436
## 8 211.29117
## 9 208.65973
## 10 213.84387
## 11 272.26514
## 12 244.55374
## 13 212.84184
## 14 465.69630
## 15 243.04752
## 16 272.85950
## 17 263.14527# merge data items with indices 3:5 into a data.frame
print(merge(mtc_device, 3:5))## timestamp test_device<Device>:Xabs<POSITION-ACTUAL>
## 1 2014-07-15 07:04:25.608 8.26262
## 2 2014-07-15 07:04:25.788 4.61391
## 3 2014-07-15 07:04:29.983 8.14832
## 4 2014-07-15 07:04:34.210 56.67629
## 5 2014-07-15 07:04:38.526 41.27500
## 6 2014-07-15 07:04:42.862 38.94074
## 7 2014-07-15 07:04:47.049 -19.75612
## 8 2014-07-15 07:04:51.286 -20.20316
## 9 2014-07-15 07:04:55.492 -21.00961
## 10 2014-07-15 07:04:59.729 -1.99644
## 11 2014-07-15 07:05:03.914 1.98247
## 12 2014-07-15 07:05:08.141 29.57195
## 13 2014-07-15 07:05:12.328 -23.00986
## 14 2014-07-15 07:05:16.513 276.65426
## 15 2014-07-15 07:05:20.710 56.94934
## 16 2014-07-15 07:05:24.875 32.88030
## 17 2014-07-15 07:05:29.092 -51.92649
## test_device<Device>:Xload<LOAD>
## 1 -8
## 2 -8
## 3 -2
## 4 -2
## 5 -2
## 6 -2
## 7 10
## 8 -1
## 9 -1
## 10 -1
## 11 -9
## 12 -17
## 13 6
## 14 6
## 15 -1
## 16 -1
## 17 -1
## test_device<Device>:Yabs<POSITION-ACTUAL>
## 1 238.02594
## 2 240.46434
## 3 234.98429
## 4 280.67762
## 5 267.71600
## 6 269.86738
## 7 278.72436
## 8 211.29117
## 9 208.65973
## 10 213.84387
## 11 272.26514
## 12 244.55374
## 13 212.84184
## 14 465.69630
## 15 243.04752
## 16 272.85950
## 17 263.14527# merge all the data items
merged_mtc_device = (merge(mtc_device))
# renaming column names to make it more readable
names(merged_mtc_device) = stringr::str_replace(names(merged_mtc_device), "test_device<Device>:", "")
print(merged_mtc_device)## timestamp Frapidovr<PATH_FEEDRATE-OVERRIDE>
## 1 2014-07-15 07:04:25.608 100
## 2 2014-07-15 07:04:25.788 100
## 3 2014-07-15 07:04:29.983 100
## 4 2014-07-15 07:04:34.210 100
## 5 2014-07-15 07:04:38.526 100
## 6 2014-07-15 07:04:42.862 100
## 7 2014-07-15 07:04:47.049 100
## 8 2014-07-15 07:04:51.286 100
## 9 2014-07-15 07:04:55.492 100
## 10 2014-07-15 07:04:59.729 100
## 11 2014-07-15 07:05:03.914 100
## 12 2014-07-15 07:05:08.141 100
## 13 2014-07-15 07:05:12.328 100
## 14 2014-07-15 07:05:16.513 100
## 15 2014-07-15 07:05:20.710 100
## 16 2014-07-15 07:05:24.875 100
## 17 2014-07-15 07:05:29.092 100
## Sovr<SPINDLE_SPEED-OVERRIDE> Xabs<POSITION-ACTUAL> Xload<LOAD>
## 1 100 8.26262 -8
## 2 100 4.61391 -8
## 3 100 8.14832 -2
## 4 100 56.67629 -2
## 5 100 41.27500 -2
## 6 100 38.94074 -2
## 7 100 -19.75612 10
## 8 100 -20.20316 -1
## 9 100 -21.00961 -1
## 10 100 -1.99644 -1
## 11 100 1.98247 -9
## 12 100 29.57195 -17
## 13 100 -23.00986 6
## 14 100 276.65426 6
## 15 100 56.94934 -1
## 16 100 32.88030 -1
## 17 100 -51.92649 -1
## Yabs<POSITION-ACTUAL> Yload<LOAD>
## 1 238.02594 -29
## 2 240.46434 -29
## 3 234.98429 -29
## 4 280.67762 -29
## 5 267.71600 -24
## 6 269.86738 -24
## 7 278.72436 -34
## 8 211.29117 -25
## 9 208.65973 -25
## 10 213.84387 -25
## 11 272.26514 -25
## 12 244.55374 -25
## 13 212.84184 -20
## 14 465.69630 -29
## 15 243.04752 -29
## 16 272.85950 -29
## 17 263.14527 -24