endaq.ide

endaq.ide.extract_time(doc, out, start=0, end=None, channels=None, **kwargs)

Efficiently extract data within a certain interval from an IDE file. Note that due to the way data is stored in an IDE, the exported interval will be slightly wider than the specified start and end times; this ensures the data is copied verbatim and without loss.

The start and end times, if used, may be specified in several ways:

  • int/float (Microseconds from the recording start)

  • str (formatted as a time from the recording start, e.g., MM:SS, HH:MM:SS, DDd HH:MM:SS). More examples:

    • ":01" or ":1" or "1s" (1 second)

    • "22:11" (22 minutes, 11 seconds)

    • "3:22:11" (3 hours, 22 minutes, 11 seconds)

    • "1d 3:22:11" (1 day, 3 hours, 22 minutes, 11 seconds)

  • datetime.timedelta or pandas.Timedelta (time from the recording start)

  • datetime.datetime (an explicit UTC time)

Parameters
  • doc – A Dataset or the name of a local IDE file. Dataset objects do not have to be fully imported.

  • out – A filename or stream to which to save the extracted data.

  • start – The starting time. Defaults to the start of the recording.

  • end – The ending time. Defaults to the end of the recording.

  • channels – A list of channel IDs to specifically export. If None, all channels will be exported. Note excluded channels will still appear in the new IDE’s channels dictionary, but the file will contain no data for them.

Returns

The total number of bytes written, and total number of ChannelDataBlock elements copied.

endaq.ide.filter_channels(channels, measurement_type=<MeasurementType: Any/all>)

Filter a list of Channel and/or SubChannel instances by their measurement type(s).

Parameters
  • channels – A list or dictionary of channels/subchannels to filter.

  • measurement_type – A MeasurementType, a measurement type ‘key’ string, or a string of multiple keys generated by adding and/or subtracting MeasurementType objects. Any ‘subtracted’ types will be excluded.

endaq.ide.get_channel_table(dataset, measurement_type=<MeasurementType: Any/all>, start=0, end=None, formatting=None, index=True, precision=4, timestamps=False, **kwargs)

Get summary data for all SubChannel objects in a Dataset that contain one or more type of sensor data. By using the optional start and end parameters, information can be retrieved for a specific interval of time.

The start and end times, if used, may be specified in several ways:

  • int/float (Microseconds from the recording start)

  • str (formatted as a time from the recording start, e.g., MM:SS, HH:MM:SS, DDd HH:MM:SS). More examples:

    • ":01" or ":1" or "1s" (1 second)

    • "22:11" (22 minutes, 11 seconds)

    • "3:22:11" (3 hours, 22 minutes, 11 seconds)

    • "1d 3:22:11" (1 day, 3 hours, 22 minutes, 11 seconds)

  • datetime.timedelta or pandas.Timedelta (time from the recording start)

  • datetime.datetime (an explicit UTC time)

Parameters
  • dataset – A idelib.dataset.Dataset or a list of channels/subchannels from which to build the table.

  • measurement_type – A MeasurementType, a measurement type ‘key’ string, or a string of multiple keys generated by adding and/or subtracting MeasurementType objects to filter the results. Any ‘subtracted’ types will be excluded.

  • start – The starting time. Defaults to the start of the recording.

  • end – The ending time. Defaults to the end of the recording.

  • formatting – A dictionary of additional style/formatting items (see pandas.DataFrame.style.format()). If False, no additional formatting is applied.

  • index – If True, show the index column on the left.

  • precision – The default decimal precision to display. Can be changed later.

  • timestamps – If True, show the start and end as raw microsecond timestamps.

Returns

A table (pandas.io.formats.style.Styler) of summary data.

Return type

pandas.DataFrame

endaq.ide.get_channels(dataset, measurement_type=<MeasurementType: Any/all>, subchannels=True)

Get a list of Channel or SubChannel instances from a Dataset by their measurement type(s).

Parameters
  • dataset – The Dataset from which to retrieve the list.

  • measurement_type – A MeasurementType, a measurement type ‘key’ string, or a string of multiple keys generated by adding and/or subtracting MeasurementType objects. Any ‘subtracted’ types will be excluded.

  • subchannels – If False, get only Channel objects. If True, get only SubChannel objects.

Returns

A list of matching SubChannel instances from the Dataset.

endaq.ide.get_doc(name=None, filename=None, url=None, parsed=True, start=0, end=None, localfile=None, params=None, cookies=None, **kwargs)

Retrieve an IDE file from either a file or URL.

Note: name, filename, and url are mutually exclusive arguments. One and only one must be specified. Attempting to supply more than one will generate an error.

Example usage:

get_doc("my_recording.ide")
get_doc("https://example.com/remote_recording.ide")
get_doc(filename="my_recording.ide")
get_doc(url="https://example.com/remote_recording.ide")
get_doc(filename="my_recording.ide", start="1:23")

The start and end times, if used, may be specified in several ways:

  • int/float (Microseconds from the recording start)

  • str (formatted as a time from the recording start, e.g., MM:SS, HH:MM:SS, DDd HH:MM:SS). More examples:

    • ":01" or ":1" or "1s" (1 second)

    • "22:11" (22 minutes, 11 seconds)

    • "3:22:11" (3 hours, 22 minutes, 11 seconds)

    • "1d 3:22:11" (1 day, 3 hours, 22 minutes, 11 seconds)

  • datetime.timedelta or pandas.Timedelta (time from the recording start)

  • datetime.datetime (an explicit UTC time)

Parameters
  • name – The name or URL of the IDE. The method of fetching it will be automatically chosen based on how it is formatted.

  • filename – The name of an IDE file. Supplying a name this way will force it to be read from a file, avoiding the possibility of accidentally trying to retrieve it via URL.

  • url – The URL of an IDE file. Supplying a name this way will force it to be read from a URL, avoiding the possibility of accidentally trying to retrieve it from a local file.

  • parsed – If True (default), the IDE will be fully parsed after it is fetched. If False, only the file metadata will be initially loaded, and a call to idelib.importer.readData(). This can save time.

  • start – The starting time. Defaults to the start of the recording. Only applicable if parsed is True.

  • end – The ending time. Defaults to the end of the recording. Only applicable if parsed is True.

  • localfile – The name of the file to which to write data recieved from a URL. If none is supplied, a temporary file will be used. Only applicable when opening a URL.

  • params – Additional URL request parameters. Only applicable when opening a URL.

  • cookies – Additional browser cookies for use in the URL request. Only applicable when opening a URL.

Returns

The fetched IDE data.

Additionally, get_doc() will accept the keyword arguments for idelib.importer.importFile() or idelib.importer.openFile()

endaq.ide.get_measurement_type(channel)

Get the appropriate MeasurementType object for a given SubChannel. Calling with a Channel returns a list of MeasurementType objects, with one for each child SubChannel.

Parameters

channel – A Channel or SubChannel instance (e.g., from a Dataset).

Returns

A MeasurementType object (for a SubChannel), or a list of MeasurentType objects (one for each child) if a Channel was supplied.

endaq.ide.to_pandas(channel, time_mode='datetime')

Read IDE data into a pandas DataFrame.

Parameters
  • channel (Union[idelib.dataset.Channel, idelib.dataset.SubChannel]) – a Channel object, as produced from Dataset.channels or endaq.ide.get_channels

  • time_mode – how to temporally index samples; each mode uses either relative times (with respect to the start of the recording) or absolute times (i.e., date-times): - “seconds” - a pandas.Float64Index of relative timestamps, in seconds - “timedelta” - a pandas.TimeDeltaIndex of relative timestamps - “datetime” - a pandas.DateTimeIndex of absolute timestamps

Returns

a pandas.DataFrame containing the channel’s data

Return type

pandas.core.frame.DataFrame