This software converts the sparse event stream (in HDF5) generated by tpx3HitParser from Timepix3 data to frames.
The green blocks are performed by tpx3HitParser while the blue blocks are done by tpx3EventViewer.
Download
git clone https://github.com/M4I-nanoscopy/tpx3EventViewer.git
cd tpx3EventViewer
Recommended way is to use a Python virtualenv. But this is optional.
virtualenv tpx3
source tpx3/bin/activate
Install Python dependencies
pip install -r requirements.txt
$./tpx3HitParser.py --help
usage: tpx3EventViewer.py [-h] [-t] [--uint32] [--uint8] [-m] [-f FILE] [-o] [-n] [-r ROTATION] [-g GAIN] [--animation] [--power_spectrum] [--flip_x] [--flip_y] [--hits] [--hits_tot] [--hits_toa] [--gauss GAUSS] [--events_sumtot] [--events_nhits] [--timing_stats]
[--tot_threshold TOT_THRESHOLD] [--tot_limit TOT_LIMIT] [--chip CHIP] [--normalize] [--exposure EXPOSURE] [--start START] [--end END] [--super_res N] [--cluster_stats] [--cluster_stats_tot CLUSTER_STATS_TOT] [--cluster_stats_size CLUSTER_STATS_SIZE]
FILE
positional arguments:
FILE Input .h5 file
options:
-h, --help show this help message and exit
-t Store uint16 .tif file
--uint32 Store uint32 tif (not supported by all readers!)
--uint8 Store uint8 tif (supported by almost all readers)
-m Store as mrc file
-f FILE File name for .tif file (default is .h5 file with .tif extension)
-o Overwrite existing file
-n Don't show interactive viewer
-r ROTATION, --rotation ROTATION
Rotate 90 degrees (1: clockwise, -1 anti-clockwise, 0: none). Default: 0
-g GAIN, --gain GAIN MRC file with gain correction.
--animation Store as animated mp4 file
--power_spectrum Show power spectrum
--flip_x Flip image in X
--flip_y Flip image in Y
--hits Use hits (default in counting mode)
--hits_tot Use hits in ToT mode
--hits_toa Use hits in ToA mode
--gauss GAUSS Use events, but place back as gaussian with a certain lambda. Default: None
--events_sumtot Use events in sumToT mode
--events_nhits Use events in nHits mode
--timing_stats Show timing stats
--tot_threshold TOT_THRESHOLD
In hits show only hits above ToT threshold
--tot_limit TOT_LIMIT
In hits show only hits below ToT limit
--chip CHIP Limit display to certain chip
--normalize Normalize to the average (useful for showing ToT)
--exposure EXPOSURE Max exposure time in seconds (0: infinite)
--start START Start time in seconds
--end END End time in seconds
--super_res N Up scale the amount of pixels by N factor
--cluster_stats Show cluster stats
--cluster_stats_tot CLUSTER_STATS_TOT
Override cluster_stats ToT limit
--cluster_stats_size CLUSTER_STATS_SIZE
Override cluster_stats size limit
Please consider citing either or both the Zenodo deposit of this code and our two papers:
- van Schayck, J. Paul. (2020). M4I-nanoscopy/tpx3EventViewer. Zenodo. https://doi.org/10.5281/zenodo.3693990
- Schayck, J. P. van, Genderen, E. van, Maddox, E., Roussel, L., Boulanger, H., Fröjdh, E., Abrahams, J.-P., Peters, P. J. & Ravelli, R. B. G. (2020). Sub-pixel electron detection using a convolutional neural network. Ultramicroscopy, 218, 113091. https://doi.org/10.1016/j.ultramic.2020.113091
- J Paul van Schayck, Yue Zhang, Kèvin Knoops, Peter J Peters, Raimond B G Ravelli, Integration of an Event-driven Timepix3 Hybrid Pixel Detector into a Cryo-EM Workflow, Microscopy and Microanalysis, Volume 29, Issue 1, February 2023, Pages 352–363, https://doi.org/10.1093/micmic/ozac009
(c) Maastricht University
MIT license
- Paul van Schayck (p.vanschayck@maastrichtuniversity.nl)
- Raimond Ravelli (rbg.ravelli@maastrichtuniversity.nl) (corresponding)