Bm29

build-deb.sh

@@ -68,12 +68,12 @@ then
             bookworm)
                 debian_version=12
                 ;;
-	    trixie)
-		debian_version=13
-		;;
-	    sid)
-		debian_version=13
-		;;
+	        trixie)
+		    debian_version=13
+		    ;;
+	        sid)
+		    debian_version=13
+		    ;;
         esac
     fi
 
@@ -109,6 +109,7 @@ optional arguments:
     --debian10      Simulate a debian 10 Buster system
     --debian11      Simulate a debian 11 Bullseye system
     --debian12      Simulate a debian 12 Bookworm system
+    --debian13      Simulate a debian 13 Trixie system
 "
 
 install=0

doc/source/dahu.rst

@@ -11,15 +11,15 @@ The *dahu* server executes **jobs**:
 * The job (de-) serializes JSON strings coming from/returning to Tango
 * Jobs are executed asynchronously, the request for calculation is answered instantaneously with a *jobid* (an integer, unique for the process).
 * The *jobid* can be used to poll the server for the status of the job or for manual synchronization (mind that Tango can time-out!).
-* When jobs are finished, the client is notified via Tango events about the status
+* When jobs are finished, the client is notified via **Tango events** about the status change
 * Results can be retrieved after the job has finished.
 
 Jobs execute **plugin**:
 ------------------------
 
-* Plugins are written in Python (extension in Cython or OpenCL are common)
+* Plugins are written in Python (extensions in Cython or OpenCL are common)
 * Plugins can be classes or simple functions
-* The input and output MUST be JSON-seriablisable as simple dictionnaries
+* The input and output MUST be JSON-serializable as simple dictionaries
 * Plugins are dynamically loaded from Python modules
 * Plugins can be profiled for performance analysis
 

plugins/bm29/__init__.py

@@ -11,14 +11,16 @@
 __contact__ = "Jerome.Kieffer@ESRF.eu"
 __license__ = "MIT"
 __copyright__ = "European Synchrotron Radiation Facility, Grenoble, France"
-__date__ = "03/12/2024"
+__date__ = "05/05/2025"
 __status__ = "development"
 __version__ = "0.2.0"
 
 from dahu.factory import register
 from .integrate import IntegrateMultiframe
 from .subtracte import SubtractBuffer
 from .hplc import HPLC
+from .mesh import Mesh
 register(IntegrateMultiframe, fqn="bm29.integratemultiframe")
 register(SubtractBuffer, fqn="bm29.subtractbuffer")
 register(HPLC, fqn="bm29.hplc")
+register(Mesh, fqn="bm29.mesh")

plugins/bm29/common.py

@@ -4,45 +4,44 @@
 """Data Analysis plugin for BM29: BioSaxs
 
 Common data structures: Sample, Ispyb
- 
+
 """
 
 __authors__ = ["Jérôme Kieffer"]
 __contact__ = "Jerome.Kieffer@ESRF.eu"
 __license__ = "MIT"
 __copyright__ = "European Synchrotron Radiation Facility, Grenoble, France"
-__date__ = "20/02/2025"
+__date__ = "09/03/2026"
 __status__ = "development"
-version = "0.0.2"
+__version__ = "0.0.2"
 
 import os
 from pathlib import Path
 from collections import namedtuple
 from typing import NamedTuple
 import json
 import logging
-logger = logging.getLogger("bm29.common")
 import numpy
 from dahu.cache import DataCache
 from hdf5plugin import Bitshuffle, Zfp
-import pyFAI, pyFAI.units
+import pyFAI
+import pyFAI.integrator.load_engines  #noqa
+import pyFAI.units
 from pyFAI.method_registry import IntegrationMethod
 import fabio
-from .nexus import Nexus, get_isotime
-# else:
-#     from pyFAI.io import Nexus, get_isotime
-
-#cmp contains the compression options, shared by all plugins. Used mainly for images 
-cmp = cmp_int = Bitshuffle()
-cmp_float = Zfp(reversible=True) 
+logger = logging.getLogger("bm29.common")
 
+#cmp contains the compression options, shared by all plugins. Used mainly for images
+cmp = cmp_int = Bitshuffle()
+cmp_float = Zfp(reversible=True)
+version = __version__
 
 #This is used for NXdata plot style
 SAXS_STYLE = json.dumps({"signal_scale_type": "log"},
-                        indent=2, 
+                        indent=2,
                         separators=(",\r\n", ":\t"))
 NORMAL_STYLE = json.dumps({"signal_scale_type": "linear"},
-                          indent=2, 
+                          indent=2,
                           separators=(",\r\n", ":\t"))
 
 
@@ -89,15 +88,15 @@ def _fromdict(cls, dico):
 
 
 class Sample(NamedTuple):
-    """ This object represents the sample with the following representation 
+    """ This object represents the sample with the following representation
       "sample": {
         "name": "bsa",
         "description": "protein description like Bovine Serum Albumin",
         "buffer": "description of buffer, pH, ...",
         "concentration": 0,
         "hplc": "column name and chromatography conditions",
         "temperature": 20,
-        "temperature_env": 20},  
+        "temperature_env": 20},
     """
     name: str="Unknown sample"
     description: str=None
@@ -150,7 +149,7 @@ def get_equivalent_frames(proba, absolute=0.1, relative=0.2):
     ext_diag = numpy.zeros(size + 1, dtype=numpy.int16)
     delta = numpy.zeros(size + 1, dtype=numpy.int16)
     ext_diag[1:-1] = numpy.diagonal(proba, 1) >= relative
-    ext_diag[0] = ext_diag[1] 
+    ext_diag[0] = ext_diag[1]
     delta[0] = ext_diag[1]
     delta[1:] = ext_diag[1:] - ext_diag[:-1]
     start = numpy.where(delta > 0)[0]