miz-dac 0.6.0

Minimal measurement data analysis frame with nodes and container.

Data Action Context

DAC provides a minimal frame for (measurement) data analysis if you want to:

• Visualize data, process and interact
• Customize your analysis
• Save the analysis and load back
• Enable multiple analysis of same processing (like batch analysis)
• Link different analysis

Example of DAC user interface as shown below:

Concepts

Data & Action

The processing is essentially "function call to data (objects or parameters)".

The actions to data can be processing (non-interactive and time consuming, with outputs) or visualing (interactive, no output).

Interaction

Predefined click-able Jupyter notebook

Context

For multiple measurements / analyses under different conditions, the processing can be very similar, with a few parameters changed.

To enable same processing and share "variable names" among different conditions, context is used.

Auxiliaries

Quick tasks (on action node)

For parameter input, sometimes we need to interact with output of previous action and set, or we're inputting something long (e.g. a file path).

"Quick tasks" helps to fill the parameters with interactions.

Quick actions (on data node)

To explore data, actions can be created and accept the data as input. However, it costs several steps, and sometimes we want just exploring freely.

"Quick actions" creates actions virtually (not adding to project) who function to selected data nodes with default parameters. If delicate parameter tuning is required, then create a normal action.

Get started

Modules

Besides the minimal frame, this repo also provides usable modules for common measurement data analyis.

Extending

data.py and actions.py

For each module (contains a bunch of analysis methods of same topic), data types and the processing/visualization methods need defined.

(scripting: use the classes directly)

plugins.yaml

A YAML file is used to control which actions are available at what context, it helps:

1. Separate different analysis, keep related actions
2. Use the order to guide analyzing sequence
3. Easily adapt or reuse actions

Appendix

OOP or function calls