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* jfjoch_broker: Optional per-dataset authentication - statistics, images and plots can require a bearer token, which jfjoch_viewer supports. * jfjoch_viewer: Dark mode and a theme-matched colour scheme, a magnifier panel, and simpler contrast and background controls. * Rugnux: Multiple performance improvements on GPU and CPU (CPU-only processing up to 40% faster, faster image decoding on ARM), with unchanged results. * Rugnux: `--model` rigid-body refinement runs on the GPU, and the model-validation check is faster and more reliable. * Rugnux: Improved scaling and merging - error model, outlier rejection, absorption correction and French-Wilson amplitudes now agree more closely with XDS and ctruncate. * Rugnux: Improved integration - radial background on powder and ice rings, crowded rotation data keep their reflections, and CPU-only builds integrate large unit cells as GPU builds do. * Rugnux: More robust detector geometry - measured beam centre, X-ray bandwidth and goniometer rate, and geometry refinement accepted only on significant evidence. * Rugnux: Merged files are written in the standard setting, or in the setting of a reference MTZ, structure-factor mmCIF or model, with its free-R flags. * Rugnux: Richer report - ice and powder rings, further lattices, superstructure candidates and mosaicity, with warnings worded as prompts to check. * Rugnux: Clear error messages when a data set needs more GPU or host memory than is available. Reviewed-on: #83 Co-authored-by: Filip Leonarski <filip.leonarski@psi.ch>
56 lines
2.3 KiB
Markdown
56 lines
2.3 KiB
Markdown
# Pixel mask
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## Mask format
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Jungfraujoch generally follows the [NXmx format](https://manual.nexusformat.org/classes/applications/NXmx.html) for the pixel mask.
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The pixel mask is a 32-bit unsigned integer array of the same size as the image.
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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.
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Bit values are set as follows:
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Bit 0 - gap (pixel with no sensor)
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Bit 1 - error pixel (for PSI JUNGFRAU: pixel doesn't set proper gain during pedestal, for DECTRIS: pixel is part of detector pixel mask)
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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)
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Bit 8 - user defined mask
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Bit 9 - beam stop shadow (found by `rugnux --detect-beam-stop`, on by default; see [Rugnux](RUGNUX.md)).
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Unlike the other bits this one belongs to the run that found it, not to the dataset: Rugnux clears it
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at the start of every run, so a mask read back from a file that carries one starts clear. The user
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mask (bit 8) is left alone.
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Bit 10 - defective pixel found on the run's own frames (rotation data from a counting sensor; see
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[CPU data analysis §1.6](CPU_DATA_ANALYSIS_IMAGE.md)): lit above its resolution ring on more frames
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than one reflection or chance explains, or holding the detector's error value on most frames.
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Bit 30 - module edge (only for PSI systems)
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Bit 31 - chip edge interpolated pixel (multipixel)
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## Custom user mask
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Jungfraujoch allows a custom user mask to be uploaded. This happens in two steps. First create the mask in TIFF format:
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```python
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import numpy as np
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import tifffile as tiff
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# Create an array matching a 2068 x 2164 (width x height) image: 2164 rows, 2068 columns
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array = np.zeros((2164, 2068), dtype=np.uint32)
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# Mark the pixel at column 400, row 300 with the value 1
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array[300, 400] = 1
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# Save the array as a TIFF file
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tiff.imwrite('mask.tiff', array)
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```
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Pixels with non-zero value in the TIFF file will be marked as belonging to the user mask (bit 8).
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Then upload the mask to Jungfraujoch server:
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```shell
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curl -v http://<jfjoch_broker http address>/config/user_mask.tiff -XPUT --data-binary @mask.tiff
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```
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