Files
leonarski_f 7f2ebd8209
Build Packages / Build documentation (push) Successful in 46s
Build Packages / Create release (push) Successful in 8s
Build Packages / build:portable:macos-arm64:nocuda (push) Successful in 5m25s
Build Packages / build:rugnux:linux-aarch64:cuda (push) Successful in 9m46s
Build Packages / build:portable:linux-x86_64:nocuda (push) Successful in 13m25s
Build Packages / build:portable:linux-x86_64:cuda (push) Successful in 16m41s
Build Packages / build:portable:windows-x86_64:nocuda (push) Successful in 23m46s
Build Packages / HDF5 consumer tests (DIALS, XDS) (push) Successful in 25m37s
Build Packages / build:jfjoch:rocky8:nocuda (push) Successful in 24m31s
Build Packages / build:portable:windows-x86_64:cuda (push) Successful in 28m9s
Build Packages / build:jfjoch:ubuntu2204:nocuda (push) Successful in 20m47s
Build Packages / build:jfjoch:rocky9:nocuda (push) Successful in 26m21s
Build Packages / build:jfjoch:ubuntu2404:nocuda (push) Successful in 27m36s
Build Packages / Generate python client (push) Successful in 31s
Build Packages / build:jfjoch:rocky8:cuda-sls9 (push) Successful in 29m27s
Build Packages / build:jfjoch:rocky9:cuda-sls9 (push) Successful in 31m46s
Build Packages / build:jfjoch:ubuntu2204:cuda (push) Successful in 25m22s
Build Packages / build:jfjoch:rocky8:cuda (push) Successful in 30m36s
Build Packages / build:jfjoch:rocky9:cuda (push) Successful in 31m49s
Build Packages / build:jfjoch:ubuntu2404:cuda (push) Successful in 23m57s
Build Packages / Unit tests (push) Successful in 1h47m52s
Build Packages / Validation Battery (push) Successful in 44m55s
v1.0.0-rc.184 (#95)
* Rugnux: Rotation processing recovers most of the speed lost since 1.0.0-rc.180; live processing in jfjoch_broker finishes sooner.
* Rugnux: More reliable rotation processing and indexing, including small molecules and supercells.
* Rugnux: More robust serial data and model refinement; molecular replacement handles multi-chain models.
* jfjoch_broker (experimental): Live serial processing keeps the detector geometry fixed for the whole run.
* jfjoch_broker: Pixel sum without an FPGA, a mask bit for inactive pixels, and several stability fixes.
* jfjoch_broker: Rotation indexing and quick integration moved to rugnux live mode; their API settings are deprecated and ignored.
* jfjoch_broker, Rugnux: Azimuthal integration can use logarithmic (log10) Q bins or a given number of bins, set from the API, the web interface and the Rugnux command line.
* jfjoch_viewer: Build and display fixes; the README is rewritten.

Reviewed-on: #95
Co-authored-by: Filip Leonarski <filip.leonarski@psi.ch>
2026-11-10 22:06:51 +01:00

2.4 KiB

Pixel mask

Mask format

Jungfraujoch generally follows the NXmx format for the pixel mask. The pixel mask is a 32-bit unsigned integer array of the same size as the image. The conditions for masking a pixel are encoded by setting a particular bit to one. This makes it possible to record the reason why a pixel is included in the mask, and several reasons can be recorded for one pixel at the same time.

Bit values are set as follows:

Bit 0 - gap (pixel with no sensor)

Bit 1 - error pixel (for PSI JUNGFRAU: pixel doesn't set proper gain during pedestal, for DECTRIS: pixel is part of detector pixel mask)

Bit 4 - noisy pixel (for PSI JUNGFRAU: pixel pedestal G0 RMS is over threshold, for DECTRIS: pixel was flagged with signal during dark data collection at initialization)

Bit 8 - user defined mask

Bit 9 - beam stop shadow (found by rugnux --detect-beam-stop, on by default; see Rugnux). Unlike the other bits this one belongs to the run that found it, not to the dataset: Rugnux clears it at the start of every run, so a mask read back from a file that carries one starts clear. The user mask (bit 8) is left alone.

Bit 10 - defective pixel found on the run's own frames (rotation data from a counting sensor; see CPU data analysis §1.6): lit above its resolution ring on more frames than one reflection or chance explains, or holding the detector's error value on most frames.

Bit 11 - outside a CCD's active area, measured on the run's own frames (see CPU data analysis §1.6).

Bit 30 - module edge (only for PSI systems)

Bit 31 - chip edge interpolated pixel (multipixel)

Custom user mask

Jungfraujoch allows a custom user mask to be uploaded. This happens in two steps. First create the mask in TIFF format:

import numpy as np
import tifffile as tiff

# Create an array matching a 2068 x 2164 (width x height) image: 2164 rows, 2068 columns
array = np.zeros((2164, 2068), dtype=np.uint32)

# Mark the pixel at column 400, row 300 with the value 1
array[300, 400] = 1

# Save the array as a TIFF file
tiff.imwrite('mask.tiff', array)

Pixels with non-zero value in the TIFF file will be marked as belonging to the user mask (bit 8).

Then upload the mask to Jungfraujoch server:

curl -v http://<jfjoch_broker http address>/config/user_mask.tiff -XPUT --data-binary @mask.tiff