Reading Features

arora.reader.get_edf

arora.reader.get_edf(file)

Reads in edf file.

Parameters:

filestr: Path to the edf file to be read

Returnslist of float , pandas DataFrame

An array of all the signals and a DataFrame with information about the signals

For example:

>>> edf_file = "path/to/edf.file"
>>> arora.reader.get_edf(edf_file)
>>>([array([2.33333333e-06, 2.33333333e-06, 2.33333333e-06, ...,
         2.11111111e-06, 2.22222222e-06, 2.11111111e-06]),
  array([2.11111111e-06, 2.22222222e-06, 2.11111111e-06, ...,
         2.11111111e-06, 2.33333333e-06, 2.22222222e-06]),
  array([2.11111111e-06, 2.22222222e-06, 2.11111111e-06, ...,
         2.22222222e-06, 2.11111111e-06, 2.33333333e-06]),
  array([0., 0., 0., ..., 0., 0., 0.]),
  array([-0.00015, -0.00015, -0.00015, ..., -0.00015, -0.00015, -0.00015]),
  array([3.e-06, 3.e-06, 3.e-06, ..., 3.e-06, 3.e-06, 3.e-06])])
                label dimension  sample_rate  sample_frequency  physical_max  \
 0            Abdomen         V        250.0             250.0      0.001201
 1        Abdomen CaL                  250.0             250.0      0.000799
 2       Abdomen Fast         V       2000.0            2000.0      0.001213
 3        Abdomen Raw    counts       2000.0            2000.0      0.000208
 4           Activity       g/s        200.0             200.0     10.000000
 ...
 78  Voltage (battery         V       1000.0            5000.0     35.767000
 79    Voltage (core)         V       1000.0            4000.0     35.767000
 80            X Axis         g        100.0             200.0      2.000000
 81            Y Axis         g        100.0             100.0      2.000000
 82            Z Axis         g        100.0             100.0      2.000000
     physical_min  digital_max  digital_min prefilter transducer
 0       -0.00005        33333       -33333
 1       -0.00005        33333       -33333
 2       -0.00015        33333       -33333
 3        0.00000        33333       -33333
 4      -50.00030        33333       -33333
 ...
 78     -35.76800        33333       -33333
 79     -59.76800        33333       -33333
 80      -5.00006        33333       -33333
 81      -1.00006        33333       -33333
 82      -5.00006        33333       -33333

arora.reader.get_e4_info

arora.reader.get_e4_info(csv_file)

Parameters:

csv_filestr: filename of a csv file

Returnsint,

start time and frequency of the file

For example:

>>> csv_file = "path/to/csv/file/file_name.csv"
>>> start_time, freq = arora.reader.get_e4_info(csv_file)
>>> start_time
some_datetime_object
>>> freq
200

arora.reader.e4_to_dataframe

arora.reader.e4_to_dataframe(signal_name, path)

Parameters:

signal_namestr: Name of the signal.
pathstr: Path to file.

Returns:

pandas.DataFrame of the signal.

For example:

>>> arora.reader.e4_to_dataframe()

arora.reader.withings_csv_to_dataframe

arora.reader.withings_csv_to_dataframe(signal, path)

Parameters:

signal?: signals
pathstr: Path to file.

Returns:

pandas.DataFrame of the signals.

For example:

>>> arora.reader.withings_csv_to_dataframe()