IDE File Basics¶

What’s an IDE file?¶

An IDE file is a read-only hierarchical data format that stores recording information generated by an enDAQ sensor device. It contains both time-indexed data from several different kinds of sensors (like acceleration, pressure, temperature, etc.), as well as metadata about the recording device (like device serial number, model number, device name, etc.) and recording settings.

Accessing an IDE file¶

The top-level interface for an IDE file is the Dataset object, through which one can access all of the above-listed information. When you open a file for reading, for example, this is the type of object that is returned.

Opening an IDE File¶

You can open an IDE file like so:

filename = "/path/to/your/file.IDE"
with idelib.importFile(filename) as ds:
    print(type(ds))

Note: a Dataset object perfoms lazy-loading, meaning that it only loads information as is needed. As a result, it internally retains a handle to the source file which needs to be closed after use. This can be accomplished by either:

using Dataset as a context manager (as seen above; this is the recommended method), or

by using Dataset as a normal object and calling the close() method manually:

filename = "/path/to/your/file.IDE"
ds = idelib.importFile(filename)
# use `ds` here
ds.close()  # remember to close the file after use!

Getting recording data¶

Channels & subchannels¶

IDE files organize recording data into channels and subchannels. A channel encapsulates data recorded by a particular individual sensor on the device (e.g., XYZ acceleration from the ADXL375 DC Accelerometer); a subchannel, if present, specifies a particular data stream within a channel (e.g., the X-coordinate acceleration from the ADXL375 DC Accelerometer).

At the top-level, a Dataset object has a channels member, which is a dict of all channels recorded in the file. The dict is keyed by channel ID numbers, with Channel objects in the values.

Each Channel object has a subchannels member, which is a list of Subchannel objects. If the channel has no subchannels, this member will be None.

The channels, channel ID numbers and subchannels that may appear in a given recording file depend on the physical sensors available on the recording device, which are indicated by the device’s product number. Below are some product number abbreviations used herein:

(Abbreviated) Product No.	Description	Example Product Nos.
S/W-D	enDAQ S-series & W-series devices with a single digital accelerometer	S3-D16, W5-D40
S/W-DD	enDAQ S-series & W-series devices with dual digital accelerometers	S1-D100D40, S2-D25D16
S/W-ED	enDAQ S-series & W-series devices with an analog electrocapacitive and a digital accelerometer	W8-E25D40, S4-E100D40
S/W-RD	enDAQ S-series & W-series devices with an analog piezoresistive and a digital accelerometer	S4-R500D40, W8-R2000D40
SSX	Mide Slam Stick X data recorders	SSX
SSC	Mide Slam Stick C data recorders	SSC
SSS	Mide Slam Stick S data recorders	SSS

The below table lists channel ID numbers used in a recording file based on the recording device’s product number (device series numbers and accelerometer sensitivity ranges are omitted when applicable to all such devices):

Sensor	Channel ID	Valid Devices	Subchannels
Main Accelerometer	8	S/W-RD, S/W-ED, SSS, SSX	X-, Y-, Z-axis Acceleration
16/200g Accelerometer	32	S/W-DD, SSX, SSS, SSC, S/W-D16, S/W-D200	X-, Y-, Z-axis Acceleration
8/40g Accelerometer	80	S/W-RD, S/W-DD, S/W-ED, S/W-D40, S/W-D8	X-, Y-, Z-axis Acceleration
IMU Gyroscope	47	All 1	X-, Y-, Z-axis Rotation
Absolute Orientation	65	All 1	X-, Y-, Z-, W-axis Quaternion; Acc
Relative Orientation	70	All 1	X-, Y-, Z-, W-axis Quaternion
MPL3115	36	All 1	Pressure, Temperature 2
MS8607	59	All 1	Pressure, Temperature, Humidity 3
SI1133	76	All 1	Lux, UV

1(1,2,3,4,5,6): excluding early SSC/SSS/SSX models
2: 1 Hz Internal Measurements
3: 10 Hz Control Pad Measurements

To simply use all recording data, we can iterate through each subchannel in a dataset like so:

for ch in ds.channels.values():
    for sch in ch.subchannels:
        print(sch)

EventArrays & raw data¶

Each Channel and SubChannel object has a getSession() method, which returns an EventArray object. EventArray is a wrapper around a channel’s underlying recording data that loads data on demand from the source file. You can index an EventArray (e.g., eventarray[i] for some index i) to get a numpy ndarray of data. Data is organized in an n-dimensional array.

For subchannels, this will always be a 2-by-n array, where n is the number of samples recorded; eventarray[1] indexes the samples, eventarray[0] indexes the respective timestamps.

For channels, this will be a (c+1)-by-n array, where n is the number of samples recorded and c is the number of subchannels; eventarray[1:] indexes the samples, eventarray[0] indexes the respective timestamps.

Getting metadata¶

Dataset makes available some basic metadata. Some useful pieces of information are stored directly as members:

>>> ds.filename
'/home/enDAQ/recordings/test.IDE'

Other data is stored in the dict member recorderInfo:

>>> ds.recorderInfo['RecorderSerial']
10118
>>> ds.recorderInfo['PartNumber']
'W8-E100D40'

EventArray also stores some sample-specific metadata, like the data’s units:

>>> eventarray.units
('Acceleration', 'g')

idelib: a Python Library for accessing enDAQ sensor recordings

idelib API Reference