oasis-api 3.0.2

Python API for the Open Acquisition System for IEPE Sensors (OASIS)

OASIS Board Python Package

Used in the following packages:

• oasis-gui
• oasis-tui

                    +-------------------+
                    |     oasis-api     |
                    |  (Python library) |
                    +-------------------+
                             ^
         +-------------------+---------------------+
         |                   |                     |
  +----------------+   +----------------+   +----------------+
  |   oasis-cli    |   |   oasis-tui    |   |   oasis-gui    |
  | (flags & args) |   | (guided menus) |   | (desktop/web)  |
  +----------------+   +----------------+   +----------------+

HDF5 File Format for OASIS Measurements

Overview

Measurement data is stored in HDF5 files in a tidy data format, making it easy to analyze, visualize, and share.

Structure

• The main dataset is stored at the root as /data.
• The file contains attributes describing metadata and the measurement setup.

Data Table: /data

• Shape: (N, ) where N = number of channels × number of time points

• Each row represents a single observation:

  • channel: Integer (1–8), channel number
  • time: Float (seconds), timestamp of the sample
  • voltage: Float (volts), measured voltage value

Example (first few rows):

channel	time	voltage
1	0.00000	0.0324
1	0.00100	0.0451
...	...	...
8	9.99900	0.0078

• Units:

  • The voltage column has the attribute unit = "V"

File Attributes (Metadata)

• duration_s: Duration of acquisition (in seconds)
• sampling_frequency_hz: Sampling frequency (in Hz)
• voltage_ranges: Array of voltage ranges for each channel (in volts)
• voltage_ranges_unit: "V"
• channels: Number of channels (typically 8)
• tidy_format: Description of the tidy layout

Why Tidy Data?

• Each variable forms a column: channel, time, voltage
• Each observation forms a row: one reading from one channel at one time
• Each type of observational unit forms a table: all data is in /data
• This format makes the data easy to filter, aggregate, and visualize in Python (Pandas), R, MATLAB, etc.

---

How to Read the File (Python Example)

import h5py
import numpy as np

with h5py.File("measurement.h5", "r") as f:
    data = f["data"][:]
    print("Fields:", data.dtype.names)  # ('channel', 'time', 'voltage')
    print("First row:", data[0])
    print("Sampling frequency:", f.attrs["sampling_frequency_hz"])
    print("Voltage ranges:", f.attrs["voltage_ranges"])

---

Viewing

• Use HDFView or Vitables to inspect your data and metadata visually.