Description:
Currently, the software assumes that each set of XY coordinates corresponds to a single spectral measurement. However, many experiments involve taking repeated measurements over time at the exact same spatial location, leading to "time-resolved" or "kinetic" datasets (e.g., monitoring a reaction, photobleaching, or time-series mapping).
We need to add support for these types of datasets across both the Spectra and Maps workspaces.
Proposed Feature & Implementation Scope:
- Data Structure Updates:
- Update the core data models (e.g.,
m_spectrum.py, and the map data structures) to support a 3rd / 4th dimension—often the time axis (t) or a scan index number.
- Ensure the file loading logic (
m_io.py) can correctly parse and handle files containing multiple spectra sharing identical XY coordinates but differing timestamps or scan indices.
- Spectra Workspace Integration:
- Allow users to load a time-series file and view it as a collection of spectra.
- Provide UI controls (like a slider or playback buttons) to step through the repeated measurements sequentially.
- Maps Workspace Integration:
- Modify the 2D map visualization to handle overlapping points.
- Add a timeline or frame slider to the UI so users can view how the 2D spatial map (or specific peaks within it) changes over time.
- Data Analysis & Fitting:
- Ensure that fitting routines can process temporal data (e.g., extracting the intensity of a peak over time to plot a kinetic curve).
Description:
Currently, the software assumes that each set of XY coordinates corresponds to a single spectral measurement. However, many experiments involve taking repeated measurements over time at the exact same spatial location, leading to "time-resolved" or "kinetic" datasets (e.g., monitoring a reaction, photobleaching, or time-series mapping).
We need to add support for these types of datasets across both the Spectra and Maps workspaces.
Proposed Feature & Implementation Scope:
m_spectrum.py, and the map data structures) to support a 3rd / 4th dimension—often the time axis (t) or a scan index number.m_io.py) can correctly parse and handle files containing multiple spectra sharing identical XY coordinates but differing timestamps or scan indices.