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EMinsight

Background

These scripts will parse the xml and mrc files in an EPU session directory and produce a report on the sessions set up parameters as well as performance analysis of the data collection sessions. It can be run anytime during a data collection, but should ideally be run at the end of a session to accuractely report on the whole session.

Installation

Clone the repository to your local machine

In a terminal, change directory into the cloned repository directory

Run the following command to set up a vritual environment for EMinsight

$ python -m venv python

$ source python/bin/activate

$ pip install .

Each time you want to use EMinsight, remember to activate that virtual environment

$ source python/bin/activate

Usage instructions

Navigate to the directory you want to send outputs to (optional)

$ cd /path/to/working/output/area

Run a report on a single visit diretory

$ epu.xml_summary.py --help

$ epu.xml_summary.py --i /dls/m07/data/2023/bi23047-106 --o bi23047-106

Run a global report across all visits from all visits on m07 in 2023

$ epu.reporting.py --o global --input /dls/m07/data/2023

Use a GUI to achieve the same as above

$ eminsight.py

Data structure

EMinsight currently expects data structured in the following way

dls
├── m02 # eBIC/DLS instrument identifier
│ ├── data
│ │ ├── 2023 # year of collection
| | | └── bi23047-106 # unique eBIC/DLS data collection identifer
| | | | ├── Atlas
| | | | | └── Supervisor_[date][time]-[session-identifier]Atlas # Atlas directory used by EPU session
| | | | ├── processed
| | | | | └── raw | | | | | | └── Relion
| | | | ├── processing
| | | | ├── raw
| | | | | ├── GridSquare
[Square-ID] # Raw movie data from EPU session
| | | | | | └── Data # Raw data from this GridSquare
| | | | | ├── metadata
| | | | | | └── Supervisor
[date][time][unique-session-identifier]_EPU # EPU session files, xml metadata, compressed images
| | | | | | | └── Images-Disc1
| | | | | | | | ├── Data
| | | | | | | | ├── FoilHoles

Further development is required to make this robust to scenarios where other facilities use:
- Different data collection identifiers (i.e. bi23047-106 versus YYYYMMDD)
- Different instrument identifiers (i.e. m02 versus Krios2)
- Different directory structures altogether

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