iba.py: Create IBA Analyzer .dat Files Without the IBA Library

A lightweight, open-source tool to generate and parse ibaAnalyzer-compatible .dat files—no proprietary IBA software or libraries required.

Key Features

• No IBA Dependencies: Works independently of the official IBA library.
• Bidirectional Conversion: JSON ↔ .dat (create .dat from JSON, or extract data from existing .dat files).
• Simple API: Use via CLI or directly in Python code.
• ibaAnalyzer Compatibility: Generates .dat files that open seamlessly in ibaAnalyzer.

Installation

pip install iba-py

Usage

1. Command-Line Interface (CLI)

Convert between JSON and .dat files with a single command.

Example 1: JSON → .dat (Create IBA .dat File)

Define your data in a JSON file (see JSON Format below), then run:

python -m iba_py your_data.json

This generates your_data.dat in the same directory.

Example 2: .dat → JSON (Extract Data from Existing .dat)

To reverse-engineer a .dat file into human-readable JSON:

python -m iba_py your_existing.dat

This generates your_existing.json with the raw data, timestamps, and interval.

2. Programmatic Usage (Python Code)

Import enc (encode to .dat) and dec (decode from .dat) directly in your scripts.

Example: Create a .dat File Programmatically

from iba_py import enc, dec

# Step 1: Define your data (match the JSON format)
begin_datetime = "2024-05-20T14:30:00"  # ISO 8601 datetime (ibaAnalyzer-compatible)
interval = 0.1  # Time between data points (0.1 seconds = 100ms)
data = {
    "Channel_A": [10.2, 10.3, 10.5, 10.4],  # List of values for Channel A
    "Channel_B": [20.1, 20.0, 19.8, 19.9]   # List of values for Channel B
}

# Step 2: Encode to .dat file
enc("output.dat", begin_datetime, interval, data)

# Step 3 (Optional): Decode the .dat file back to verify
decoded_dt, decoded_interval, decoded_data = dec("output.dat")
print("Decoded Begin Time:", decoded_dt)
print("Decoded Interval:", decoded_interval)
print("Decoded Data:", decoded_data)

JSON Format

The JSON file is a 3-element list that defines the .dat file structure:

[
  "BEGIN_DATETIME",  # ISO 8601 datetime string (e.g., "2024-05-20T10:00:00")
  INTERVAL_SECONDS,  # Float: time between data points (e.g., 0.5 for 500ms)
  {                  # Data dictionary: channel names → value lists
    "CHANNEL_NAME_1": [VALUE_1, VALUE_2, ...],
    "CHANNEL_NAME_2": [VALUE_1, VALUE_2, ...]
  }
]

Requirements for Valid JSON:

• Begin Datetime: Must be an ISO 8601 string (ibaAnalyzer uses this as the start timestamp).
• Interval: Must be a positive float (seconds between consecutive data points).
• Data Dictionary:
  • Keys: Valid channel names (strings, no special characters preferred).
  • Values: Lists of numerical values (floats/integers). All lists must have the same length (one value per timestamp).

Example JSON File

Save this as sample_data.json:

[
  "2024-05-20T09:00:00",
  0.2,
  {
    "Temperature_C": [22.5, 22.6, 22.7, 22.6, 22.5],
    "Pressure_kPa": [101.3, 101.4, 101.3, 101.2, 101.3],
    "Flow_LPM": [5.0, 5.1, 5.0, 4.9, 5.0]
  }
]

Generate the .dat file with:

python -m iba_py sample_data.json

Why This Project?

The official IBA library is often:

• Proprietary or restricted.
• Tied to specific hardware/OS.
• Overly complex for simple .dat creation.

iba.py provides a free, open alternative for generating valid .dat files using standard JSON and Python.

Troubleshooting

If your .dat file doesn’t open in ibaAnalyzer:

1. Check JSON Validity: Use a JSON linter (e.g., jsonlint.com) to ensure no syntax errors.
2. Verify Data Lengths: All value lists in the JSON must have the same length.
3. Datetime Format: Ensure the begin datetime is ISO 8601 (e.g., YYYY-MM-DDTHH:MM:SS).
4. Interval Type: The interval must be a float (e.g., 0.1, not "0.1").

Contributing

Contributions are welcome! To contribute:

1. Fork the repo.
2. Create a feature branch (git checkout -b feature/your-feature).
3. Commit your changes (git commit -m 'Add your feature').
4. Push to the branch (git push origin feature/your-feature).
5. Open a Pull Request.