add windows build to release action

.github/workflows/release.yml

@@ -0,0 +1,97 @@
+name: Release
+
+# Controls when the action will run.
+on:
+  # Triggers the workflow on push or pull request events but only for the master branch
+  push:
+    tags:
+      - "*"
+
+  # Allows you to run this workflow manually from the Actions tab
+  workflow_dispatch:
+    inputs:
+      build-items:
+        description: 'Items to be build'
+        required: true
+        default: 'all'
+        type: choice
+        options:
+          - all
+          - windows
+          - linux
+          - mac
+
+jobs:
+  build-ubuntu-latest:
+    runs-on: ubuntu-latest
+    if: ${{ (github.event_name != 'workflow_dispatch') || (contains(fromJson('["all", "linux"]'), github.event.inputs.build-items)) }}
+    steps:
+    - uses: actions/checkout@v4
+    - uses: actions/setup-python@v5
+      with:
+        python-version: '3.11'
+    - name: Install dependencies
+      run: |
+        python -m pip install --upgrade pip
+        pip install build
+        pip install -r requirements.txt
+    - name: Build PyPI package
+      run: |
+        python3 -m build
+    - name: Upload to PyPI
+      if: github.event_name != 'workflow_dispatch'
+      uses: pypa/gh-action-pypi-publish@release/v1
+      with:
+        user: __token__
+        password: ${{ secrets.PYPI_TOKEN }}
+        skip-existing: true
+    - name: Archive distribution
+      uses: actions/upload-artifact@v4
+      with:
+        name: linux-dist
+        path: |
+          dist/*.tar.gz
+
+  build-windows:
+    runs-on: windows-latest
+    if: ${{ (github.event_name != 'workflow_dispatch') || (contains(fromJson('["all", "windows"]'), github.event.inputs.build-items)) }}
+
+    steps:
+    - uses: actions/checkout@v4
+    - name: Set up Python
+      uses: actions/setup-python@v5
+      with:
+        python-version: 3.12
+    - name: Install dependencies
+      run: |
+        C:\Miniconda\condabin\conda.bat env update --file conda_windows.yml --name base
+        C:\Miniconda\condabin\conda.bat init powershell
+    - name: Build with pyinstaller
+      run: |
+        pyinstaller windows_folder.spec
+        cd dist\eos
+        Compress-Archive -Path .\* -Destination ..\..\eos.zip
+    - name: Archive distribution
+      uses: actions/upload-artifact@v4
+      with:
+        name: windows-dist
+        path: |
+          eos.zip
+
+  release:
+    if: github.event_name != 'workflow_dispatch'
+    runs-on: ubuntu-latest
+    needs: [build-ubuntu-latest]
+    steps:
+    - uses: actions/checkout@v4
+    - uses: actions/download-artifact@v4
+      with:
+        name: linux-dist
+    - uses: actions/download-artifact@v4
+      with:
+        name: windows-dist
+    - uses: ncipollo/release-action@v1
+      with:
+        artifacts: "amor*.tar.gz,*.zip"
+        token: ${{ secrets.GITHUB_TOKEN }}
+        allowUpdates: true

.github/workflows/unit_tests.yml

@@ -0,0 +1,37 @@
+name: Unit Testing
+
+on:
+  push:
+      branches:
+        - main
+  pull_request:
+
+  # Allows you to run this workflow manually from the Actions tab
+  workflow_dispatch:
+
+jobs:
+  build:
+
+    runs-on: ubuntu-22.04
+    strategy:
+      matrix:
+        python-version: [3.8, 3.9, '3.10', '3.11', '3.12']
+      fail-fast: false
+
+    steps:
+      - uses: actions/checkout@v4
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v5
+        with:
+          python-version: ${{ matrix.python-version }}
+
+      - name: Install dependencies
+        run: |
+          python -m pip install --upgrade pip
+          pip install pytest
+          pip install -r requirements.txt
+
+      - name: Test with pytest
+        run: |
+          cd tests
+          python -m pytest --pyargs .

.gitignore

@@ -5,6 +5,6 @@
 __pycache__
 raw
 .idea
-test_data
+test_results
 build
 dist

README.md

@@ -1,12 +0,0 @@
-Software repository for the neutron reflectometer Amor at the Paul Scherrer Institut, Switzerland
-
-reduction of the raw files (.hdf) to reflectivity files in one of the representations of the **ORSO reflectivity file format**:
-
-> `eos.py`  
-> `neos.py` : version for playing and testing
-
-visualisation of the content of a raw file (.hdf):
-
-> `events2histogram.py`
-
-#TODO: real readme for final system needed.

README.rst

@@ -0,0 +1,27 @@
+EOS - The AMOR focusing reflectometry data reduction software
+-------------------------------------------------------------
+
+.. image:: https://img.shields.io/pypi/v/amor-eos.svg
+        :target: https://pypi.python.org/pypi/amor-eos/
+
+
+Software repository for the neutron reflectometer Amor at the Paul Scherrer Institut, Switzerland
+
+Reduction of the raw files (.hdf) to reflectivity files in one of the representations of the **ORSO reflectivity file format**:
+
+  eos.py --help
+
+visualisation of the content of a raw file (.hdf):
+
+  events2histogram.py
+
+:TODO: real readme for final system needed.
+
+Installation
+------------
+Create a virtual python environment (>3.8) and install the PyPI package:
+
+  pip install amor-eos
+
+On Windows you can also use the binary eos.exe that you find in the 
+[GitHub Releases]([https://github.com/jochenstahn/amor/releases/latest) section

conda_windows.yml

@@ -0,0 +1,43 @@
+name: eos_build
+channels:
+  - defaults
+dependencies:
+  - altgraph=0.17.3=py312haa95532_0
+  - blas=1.0=mkl
+  - bzip2=1.0.8=h2bbff1b_6
+  - ca-certificates=2024.11.26=haa95532_0
+  - expat=2.6.3=h5da7b33_0
+  - h5py=3.12.1=py312h3b2c811_0
+  - hdf5=1.12.1=h51c971a_3
+  - icc_rt=2022.1.0=h6049295_2
+  - intel-openmp=2023.1.0=h59b6b97_46320
+  - libffi=3.4.4=hd77b12b_1
+  - llvmlite=0.43.0=py312hf2fb9eb_0
+  - mkl=2023.1.0=h6b88ed4_46358
+  - mkl-service=2.4.0=py312h2bbff1b_1
+  - mkl_fft=1.3.11=py312h827c3e9_0
+  - mkl_random=1.2.8=py312h0158946_0
+  - numba=0.60.0=py312h0158946_0
+  - numpy=1.26.4=py312hfd52020_0
+  - numpy-base=1.26.4=py312h4dde369_0
+  - openssl=3.0.15=h827c3e9_0
+  - packaging=24.1=py312haa95532_0
+  - pefile=2023.2.7=py312haa95532_0
+  - pip=24.2=py312haa95532_0
+  - pyinstaller=6.9.0=py312h0416ee5_0
+  - pyinstaller-hooks-contrib=2024.7=py312haa95532_0
+  - python=3.12.7=h14ffc60_0
+  - pywin32-ctypes=0.2.2=py312haa95532_0
+  - setuptools=75.1.0=py312haa95532_0
+  - sqlite=3.45.3=h2bbff1b_0
+  - tbb=2021.8.0=h59b6b97_0
+  - tk=8.6.14=h0416ee5_0
+  - tzdata=2024b=h04d1e81_0
+  - vc=14.40=h2eaa2aa_1
+  - vs2015_runtime=14.40.33807=h98bb1dd_1
+  - wheel=0.44.0=py312haa95532_0
+  - xz=5.4.6=h8cc25b3_1
+  - zlib=1.2.13=h8cc25b3_1
+  - pip:
+      - orsopy==1.2.1
+      - pyyaml==6.0.2

libeos/__init__.py

@@ -2,5 +2,5 @@
 Package to handle data redction at AMOR instrument to be used by eos.py script.
 """
 
-__version__ = '2.1.0'
-__date__    = '2024-08-25'
+__version__ = '2.1.2'
+__date__    = '2024-12-03'

libeos/command_line.py

@@ -23,28 +23,32 @@ def commandLineArgs():
                             default = Defaults.normalisationFileIdentifier,
                             nargs = '+',
                             help = "file number(s) of normalisation measurement")
-    input_data.add_argument("-nm", "--normalisationMethod",
-                            default = Defaults.normalisationMethod,
-                            help = "normalisation method: [o]verillumination, [u]nderillumination, [d]irect_beam")
-    input_data.add_argument("--raw", 
+    input_data.add_argument("-rp", "--rawPath", 
                             type = str,
-                            default = Defaults.raw,
-                            help = "relative path to directory with .hdf files")
-    input_data.add_argument("-d", "--dataPath",
-                            type = str,
-                            default = Defaults.dataPath,
-                            help = "relative path for output")
+                            default = Defaults.rawPath,
+                            help = "ath to directory with .hdf files")
     input_data.add_argument("-Y", "--year",
                             default = Defaults.year,
                             type = int,
                             help = "year the measurement was performed")
     input_data.add_argument("-sub", "--subtract",
                             help = "R(q_z) curve to be subtracted (in .Rqz.ort format)")
+    input_data.add_argument("-nm", "--normalisationMethod",
+                            default = Defaults.normalisationMethod,
+                            help = "normalisation method: [o]verillumination, [u]nderillumination, [d]irect_beam")
+    input_data.add_argument("-mt", "--monitorType",
+                            type = str,
+                            default = Defaults.monitorType,
+                            help = "one of [p]rotonCurrent, [t]ime or [n]eutronMonitor")
 
     output = clas.add_argument_group('output')
     output.add_argument("-o", "--outputName",
                             default = Defaults.outputName,
                             help = "output file name (withot suffix)")
+    output.add_argument("-op", "--outputPath",
+                            type = str,
+                            default = Defaults.outputPath,
+                            help = "path for output")
     output.add_argument("-of", "--outputFormat",
                             nargs = '+',
                             default = Defaults.outputFormat,
@@ -98,6 +102,11 @@ def commandLineArgs():
                             nargs = 2,
                             type = float,
                             help = "q_z range")
+    masks.add_argument("-ct", "--lowCurrentThreshold",
+                            default = Defaults.lowCurrentThreshold,
+                            type = float,
+                            help = "proton current threshold for discarding neutron pulses")
+
 
     overwrite = clas.add_argument_group('overwrite')
     overwrite.add_argument("-cs", "--chopperSpeed",
@@ -172,8 +181,7 @@ def command_line_options():
 
     reader_config = ReaderConfig(
         year                         = clas.year,
-        raw                          = clas.raw,
-        dataPath                     = clas.dataPath
+        rawPath                      = clas.rawPath,
         )
     experiment_config = ExperimentConfig(
         sampleModel                  = clas.sampleModel,
@@ -182,10 +190,12 @@ def command_line_options():
         yRange                       = clas.yRange,
         lambdaRange                  = clas.lambdaRange,
         qzRange                      = clas.qzRange,
+        lowCurrentThreshold          = clas.lowCurrentThreshold,
         incidentAngle                = clas.incidentAngle,
         mu                           = clas.mu,
         nu                           = clas.nu,
-        muOffset                     = clas.muOffset
+        muOffset                     = clas.muOffset,
+        monitorType                  = clas.monitorType,
         )
     reduction_config = ReductionConfig(
         qResolution                  = clas.qResolution,
@@ -202,7 +212,8 @@ def command_line_options():
         )
     output_config = OutputConfig(
         outputFormats                = output_format_list(clas.outputFormat),
-        outputName                   = clas.outputName
+        outputName                   = clas.outputName,
+        outputPath                   = clas.outputPath,
         )
 
     return EOSConfig(reader_config, experiment_config, reduction_config, output_config)

libeos/file_reader.py

@@ -2,12 +2,11 @@ import logging
 import os
 import subprocess
 import sys
-from datetime import datetime
+from datetime import datetime, timezone
 from typing import List
 
 import h5py
 import numpy as np
-import scipy as sp
 from orsopy import fileio
 from orsopy.fileio.model_language import SampleModel
 
@@ -21,7 +20,6 @@ try:
 except Exception:
     nb_helpers = None
 
-
 class AmorData:
     """read meta-data and event streams from .hdf file(s), apply filters and conversions"""
     chopperDetectorDistance: float
@@ -38,19 +36,20 @@ class AmorData:
     kap: float
     lambdaMax: float
     lambda_e: np.ndarray
-    monitor: float
+    #monitor: float
     mu: float
     nu: float
     tau: float
     tofCut: float
     start_date: str
+    monitorType: str
 
     seriesStartTime = None
 
     #-------------------------------------------------------------------------------------------------
     def __init__(self, header: Header, reader_config: ReaderConfig, config: ExperimentConfig,
                  short_notation:str, norm=False):
-        self.startTime = reader_config.startTime
+        #self.startTime = reader_config.startTime
         self.header = header
         self.config = config
         self.reader_config = reader_config
@@ -68,22 +67,26 @@ class AmorData:
         else:
             self.readHeaderInfo = True
 
-        _detZ_e            = []
-        _lamda_e           = []
-        _wallTime_e        = []
-        _monitor           = 0
-        #_current          = []
+        _detZ_e = []
+        _lamda_e = []
+        _wallTime_e = []
+        #_monitor = 0
+        _monitorPerPulse = []
+        _pulseTimeS = []
         for file in self.file_list:
             self.read_individual_data(file, norm)
-            _detZ_e        = np.append(_detZ_e,        self.detZ_e)
-            _lamda_e       = np.append(_lamda_e,       self.lamda_e)
-            _wallTime_e    = np.append(_wallTime_e,    self.wallTime_e)
-            _monitor       += self.monitor
-        self.detZ_e        = _detZ_e
-        self.lamda_e       = _lamda_e
-        self.wallTime_e    = _wallTime_e
-        self.monitor       = _monitor
-        logging.warning(f'    {self.monitorType} monitor = {self.monitor:9.3f}')
+            _detZ_e = np.append(_detZ_e, self.detZ_e)
+            _lamda_e = np.append(_lamda_e, self.lamda_e)
+            _wallTime_e = np.append(_wallTime_e, self.wallTime_e)
+            _monitorPerPulse = np.append(_monitorPerPulse, self.monitorPerPulse)
+            _pulseTimeS = np.append(_pulseTimeS, self.pulseTimeS)
+            #_monitor += self.monitor
+        self.detZ_e = _detZ_e
+        self.lamda_e = _lamda_e
+        self.wallTime_e = _wallTime_e
+        #self.monitor = _monitor
+        self.monitorPerPulse = _monitorPerPulse   
+        self.pulseTimeS    = _pulseTimeS
 
     #-------------------------------------------------------------------------------------------------
     #def path_generator(self, number):
@@ -105,7 +108,7 @@ class AmorData:
     def path_generator(self, number):
         fileName = f'amor{self.reader_config.year}n{number:06d}.hdf'
         path = ''
-        for rawd in self.reader_config.raw:
+        for rawd in self.reader_config.rawPath:
             if os.path.exists(os.path.join(rawd,fileName)):
                 path = rawd
                 break
@@ -113,7 +116,7 @@ class AmorData:
             if os.path.exists(f'/afs/psi.ch/project/sinqdata/{self.reader_config.year}/amor/{int(number/1000)}/{fileName}'):
                 path = f'/afs/psi.ch/project/sinqdata/{self.reader_config.year}/amor/{int(number/1000)}'
             else:
-                sys.exit(f'# ERROR: the file {fileName} can not be found in {self.reader_config.raw}!')
+                sys.exit(f'# ERROR: the file {fileName} can not be found in {self.reader_config.rawPath}')
         return os.path.join(path, fileName)
     #-------------------------------------------------------------------------------------------------
     def expand_file_list(self, short_notation):
@@ -153,7 +156,7 @@ class AmorData:
         if self.readHeaderInfo:
             self.read_header_info()
 
-        logging.warning(f'    data from file: {fileName}')
+        logging.warning(f'    from file: {fileName}')
         self.read_individual_header()
 
         # add header content
@@ -180,15 +183,26 @@ class AmorData:
 
         self.read_event_stream()
         totalNumber = np.shape(self.tof_e)[0]
+        # check for empty event stream
+        if totalNumber == 0:
+             logging.error('empty event stream: can not determine end time')
+             sys.exit()
 
         self.sort_pulses()
 
-        self.define_monitor()
-
-        # sort the events into the related pulses
+        self.associate_pulse_with_monitor()
 
         self.extract_walltime(norm)
 
+        # following lines: debugging output to trace the time-offset of proton current and neutron pulses
+        if self.config.monitorType == 'x':
+            cpp, t_bins = np.histogram(self.wallTime_e, self.pulseTimeS)
+            np.savetxt('tme.hst', np.vstack((self.pulseTimeS[:-1], cpp, self.monitorPerPulse[:-1])).T)
+
+        #self.average_events_per_pulse() # for debugging only. VERY time consuming!!!
+
+        self.monitor_threshold()
+
         self.filter_strange_times()
 
         self.merge_frames()
@@ -204,51 +218,56 @@ class AmorData:
         logging.info(f'      number of events: total = {totalNumber:7d}, filtered = {np.shape(self.lamda_e)[0]:7d}')
 
     def sort_pulses(self):
-        chopperPeriod = int(2*self.tau*1e9)
+        chopperPeriod = np.int64(2*self.tau*1e9)
         pulseTime = np.sort(self.dataPacketTime_p)
         pulseTime = pulseTime[np.abs(pulseTime[:]-np.roll(pulseTime, 1)[:])>5]
 
-        if self.seriesStartTime is None:
-            self.seriesStartTime = float(pulseTime[0])
-        pulseTime -= self.seriesStartTime
-        self.stopTime = float(pulseTime[-1])
+        pulseTime -= np.int64(self.seriesStartTime)
+        self.stopTime = pulseTime[-1]
+        pulseTime = pulseTime[pulseTime>=0]
 
         # fill in missing pulse times 
         # TODO: check for real end time
-        self.pulseTimeS = np.array([pulseTime[0]])
-        for tt in pulseTime[1:]:
-            nxt = self.pulseTimeS[-1] + chopperPeriod
-            while abs(tt - nxt) > self.tau*1e9:
-                self.pulseTimeS = np.append(self.pulseTimeS, nxt)
-                nxt += chopperPeriod
+        try:
+            # TODO: use the first pulse of the respective measurement
+            #nextPulseTime = startTime % np.int64(self.tau*2e9)
+            nextPulseTime = self.pulseTimeS[-1] + chopperPeriod
+        except AttributeError:
+            nextPulseTime = pulseTime[0] % np.int64(self.tau*2e9)
+            self.pulseTimeS = np.array([], dtype=np.int64)
+        for tt in pulseTime:
+            while tt - nextPulseTime > self.tau*1e9:
+                self.pulseTimeS = np.append(self.pulseTimeS, nextPulseTime)
+                nextPulseTime += chopperPeriod
             self.pulseTimeS = np.append(self.pulseTimeS, tt)
-        # remove 'partially filled' pulses
-        self.pulseTimeS = self.pulseTimeS[1:-1]
+            nextPulseTime = self.pulseTimeS[-1] + chopperPeriod
 
-    def associate_pulse_with_current(self):
-        if self.monitorType == 'protonCharge':
-            lowCurrentThreshold = 0.05 # mA
-            self.currentTime -= self.seriesStartTime
-            currentInterpolator = sp.interpolate.interp1d(self.currentTime, self.current, kind='previous', bounds_error=False, fill_value=0)
-            self.charge = np.array(currentInterpolator(self.pulseTimeS) * 2*self.tau *1e-3, dtype=float)
+    def get_current_per_pulse(self, pulseTimeS, currentTimeS, currents):
+        # add currents for early pulses and current time value after last pulse (j+1)
+        currentTimeS = np.hstack([[0], currentTimeS, [pulseTimeS[-1]+1]])
+        currents = np.hstack([[0], currents])
+        pulseCurrentS = np.zeros(pulseTimeS.shape[0], dtype=float)
+        j = 0
+        for i, ti in enumerate(pulseTimeS):
+            if ti >= currentTimeS[j+1]: 
+                j += 1
+            pulseCurrentS[i] = currents[j]
+            #print(f' {i}  {pulseTimeS[i]}  {pulseCurrentS[i]}') 
+        return pulseCurrentS
+
+    def associate_pulse_with_monitor(self):
+        if self.config.monitorType == 'p': # protonCharge
+            self.currentTime -= np.int64(self.seriesStartTime)
+            self.currentTime -= np.int64(16e9) # time offset of proton current signal
+            self.monitorPerPulse = self.get_current_per_pulse(self.pulseTimeS, self.currentTime, self.current) * 2*self.tau * 1e-3
             # filter low-current pulses
-            self.charge = np.where(self.charge > 2*self.tau *lowCurrentThreshold, self.charge, 0)
-            # remove 'partially filled' pulses
-            self.charge[0] = 0
-            self.charge[-1] = 0
-
-    def define_monitor(self):
-        if self.monitorType == 'protonCharge':
-            chargeSum = np.sum(self.charge)
-            logging.warning(f'      proton charge = {chargeSum:9.3f} mC')
-            self.monitor = chargeSum
-        elif self.monitorType == 'countingTime':
-            self.monitor = self.stopTime - self.seriesStartTime
-        else:
-            self.monitor = 1.
+            self.monitorPerPulse = np.where(self.monitorPerPulse > 2*self.tau * self.config.lowCurrentThreshold * 1e-3, self.monitorPerPulse, 0)
+        elif self.config.monitorType == 't': # countingTime
+            self.monitorPerPulse = np.ones(np.shape(self.pulseTimeS)[0])*self.tau
+        else: 
+            self.monitorPerPulse = 1./np.shape(pulseTimeS)[1]
 
     def extract_walltime(self, norm):
-        #self.dataPacketTime_p = np.array(self.dataPacketTime_p, dtype=float) / 1e9
         if nb_helpers:
             self.wallTime_e = nb_helpers.extract_walltime(self.tof_e, self.dataPacket_p, self.dataPacketTime_p)
         else:
@@ -256,19 +275,25 @@ class AmorData:
             for i in range(len(self.dataPacket_p)-1):
                 self.wallTime_e[self.dataPacket_p[i]:self.dataPacket_p[i+1]] = self.dataPacketTime_p[i]
             self.wallTime_e[self.dataPacket_p[-1]:] = self.dataPacketTime_p[-1]
-        #if not self.startTime and not norm:
-        #    self.startTime = self.wallTime_e[0]
         self.wallTime_e -= np.int64(self.seriesStartTime)
-        logging.debug(f'      wall time from {self.wallTime_e[0]/1e9} to {self.wallTime_e[-1]/1e9}')
+        logging.debug(f'      wall time from {self.wallTime_e[0]/1e9:6.1f} s to {self.wallTime_e[-1]/1e9:6.1f} s')
+
+    def average_events_per_pulse(self):
+        if self.config.monitorType == 'p':
+            for i, time in enumerate(self.pulseTimeS):
+                events = np.shape(self.wallTime_e[self.wallTime_e == time])[0]
+                logging.info(f'pulse: {i:6.0f}, events: {events:6.0f}, monitor: {self.monitorPerPulse[i]:6.2f}')
 
     def monitor_threshold(self):
-        goodTimeS = self.pulseTimeS[self.charge!=0]
-        filter_e = np.where(np.isin(self.wallTime_e, goodTimeS), True, False)
-        self.tof_e = self.tof_e[filter_e]
-        self.pixelID_e = self.pixelID_e[filter_e]
-        self.wallTime_e = self.wallTime_e[filter_e]
-        logging.warning(f'      rejected {np.shape(self.charge)[0]-np.shape(goodTimeS)[0]} pulses due to low beam current')
-        logging.warning(f'      rejected {np.shape(filter_e)[0]-np.shape(self.tof_e)[0]} events due to low beam current')
+        if self.config.monitorType == 'p': # fix to check for file compatibility
+            goodTimeS = self.pulseTimeS[self.monitorPerPulse!=0]
+            filter_e = np.where(np.isin(self.wallTime_e, goodTimeS), True, False)
+            self.tof_e = self.tof_e[filter_e]
+            self.pixelID_e = self.pixelID_e[filter_e]
+            self.wallTime_e = self.wallTime_e[filter_e]
+            logging.info(f'      rejected {np.shape(self.monitorPerPulse)[0]-np.shape(goodTimeS)[0]} out of {np.shape(self.monitorPerPulse)[0]} pulses')
+            logging.info(f'          with {np.shape(filter_e)[0]-np.shape(self.tof_e)[0]} events due to low beam current')
+            logging.info(f'      average counts per pulse =  {np.shape(self.tof_e)[0] / np.shape(goodTimeS[goodTimeS!=0])[0]:7.1f}')
 
     def filter_qz_range(self, norm):
         if self.config.qzRange[1]<0.3 and not norm:
@@ -350,17 +375,20 @@ class AmorData:
         self.tof_e = np.array(self.hdf['/entry1/Amor/detector/data/event_time_offset'][:])/1.e9
         self.pixelID_e = np.array(self.hdf['/entry1/Amor/detector/data/event_id'][:], dtype=np.int64)
         self.dataPacket_p = np.array(self.hdf['/entry1/Amor/detector/data/event_index'][:], dtype=np.uint64)
-        #self.dataPacketTime_p = np.array(self.hdf['/entry1/Amor/detector/data/event_time_zero'][:], dtype=np.uint64)/1e9
-        self.dataPacketTime_p = np.array(self.hdf['/entry1/Amor/detector/data/event_time_zero'][:], dtype=float)
-        try:
-            self.currentTime = np.array(self.hdf['entry1/Amor/detector/proton_current/time'][:], dtype=np.int64)
-            self.current = np.array(self.hdf['entry1/Amor/detector/proton_current/value'][:,0], dtype=float)
-            if len(self.current)>0:
-                self.monitorType = 'protonCharge'
-            else:
-                self.monitorType = 'countingTime'
-        except(KeyError, IndexError):
-            self.monitorType = 'countingTime'
+        self.dataPacketTime_p = np.array(self.hdf['/entry1/Amor/detector/data/event_time_zero'][:], dtype=np.int64)
+        if self.config.monitorType in ['auto', 'p']:
+            try:
+                self.currentTime = np.array(self.hdf['entry1/Amor/detector/proton_current/time'][:], dtype=np.int64)
+                self.current = np.array(self.hdf['entry1/Amor/detector/proton_current/value'][:,0], dtype=float)
+                if len(self.current)>4:
+                    self.config.monitorType = 'p'
+                else:
+                    self.config.monitorType = 't'
+            except(KeyError, IndexError):
+                self.config.monitorType = 't'
+        else:
+            self.config.monitorType = 't'
+        #TODO: protonMonitor
 
     def read_individual_header(self):
         self.chopperDistance = float(np.take(self.hdf['entry1/Amor/chopper/pair_separation'], 0))
@@ -404,7 +432,11 @@ class AmorData:
         if self.config.nu:
             self.nu = self.config.nu
 
-        self.fileDate = datetime.fromisoformat( self.hdf['/entry1/start_time'][0].decode('utf-8') )
+        # extract start time as unix time, adding UTC offset of 1h to time string
+        self.fileDate = datetime.fromisoformat( self.hdf['/entry1/start_time'][0].decode('utf-8')+"+01:00" )
+        self.startTime = np.int64( (self.fileDate.timestamp() ) * 1e9 )
+        if self.seriesStartTime is None:
+            self.seriesStartTime = self.startTime 
 
     def read_header_info(self):
         # read general information and first data set

libeos/nb_helpers.py

@@ -11,12 +11,11 @@ def merge_frames(tof_e, tofCut, tau, total_offset):
         tof_e_out[ti] = ((tof_e[ti]-dt)%tau)+total_offset  # tof shifted to 1 frame
     return tof_e_out
 
-@nb.jit(nb.float64[:](nb.float64[:], nb.uint64[:], nb.float64[:]),
+@nb.jit(nb.float64[:](nb.float64[:], nb.uint64[:], nb.int64[:]),
         nopython=True, parallel=True, cache=True)
 def extract_walltime(tof_e, dataPacket_p, dataPacketTime_p):
     # assigning every event the wall time of the event packet (absolute time of pulse ?start?)
     totalNumber = np.shape(tof_e)[0]
-    #wallTime_e = np.empty(totalNumber, dtype=np.float64)
     wallTime_e = np.empty(totalNumber, dtype=np.int64)
     for i in nb.prange(len(dataPacket_p)-1):
         for j in range(dataPacket_p[i], dataPacket_p[i+1]):

libeos/options.py

@@ -5,16 +5,18 @@ from dataclasses import dataclass, field
 from typing import Optional, Tuple
 from datetime import datetime
 from os import path
+import numpy as np
 
 import logging
 
 class Defaults:
     # fileIdentifier
-    dataPath                    = '.'
-    raw                         = ['.', path.join('.','raw'), path.join('..','raw'), path.join('..','..','raw')]
+    outputPath                  = '.'
+    rawPath                     = ['.', path.join('.','raw'), path.join('..','raw'), path.join('..','..','raw')]
     year                        = datetime.now().year
     normalisationFileIdentifier = []
     normalisationMethod         = 'o'
+    monitorType                 = 'auto'
     # subtract
     outputName                  = "fromEOS"
     outputFormat                = ['Rqz.ort']
@@ -35,6 +37,7 @@ class Defaults:
     mu                          = 0
     nu                          = 0
     sampleModel                 = None
+    lowCurrentThreshold         = 50
     #
     
     
@@ -42,8 +45,7 @@ class Defaults:
 @dataclass
 class ReaderConfig:
     year: int
-    dataPath: str
-    raw: Tuple[str]
+    rawPath: Tuple[str]
     startTime: Optional[float] = 0
 
 @dataclass
@@ -53,6 +55,8 @@ class ExperimentConfig:
     yRange: Tuple[float, float]
     lambdaRange: Tuple[float, float]
     qzRange: Tuple[float, float]
+    monitorType: str
+    lowCurrentThreshold: float
 
     sampleModel: Optional[str] = None
     chopperPhaseOffset: float = 0
@@ -80,6 +84,7 @@ class ReductionConfig:
 class OutputConfig:
     outputFormats: list
     outputName: str
+    outputPath: str
 
 @dataclass
 class EOSConfig:
@@ -105,10 +110,8 @@ class EOSConfig:
             inpt += f' -Y {self.reader.year}'
         else:
             inpt += f' -Y {datetime.now().year}'
-        if self.reader.dataPath != '.':
-            inpt += f' --dataPath {self.reader.dataPath}'
-        #if self.reader.raw != '.':
-        #    inpt  = f' --rawd {self.reader.raw}'
+        if np.shape(self.reader.rawPath)[0] == 1:
+            inpt += f' --rawPath {self.reader.rawPath}'
         if self.reduction.subtract:
             inpt += f' -subtract {self.reduction.subtract}'
         if self.reduction.normalisationFileIdentifier:
@@ -119,6 +122,8 @@ class EOSConfig:
         otpt = ''
         if self.reduction.qResolution:
             otpt += f' -r {self.reduction.qResolution}'
+        if self.output.outputPath != '.':
+            inpt += f' --outputdPath {self.output.outputPath}'
         if self.output.outputName:
             otpt += f' -o {self.output.outputName}'
         if self.output.outputFormats != ['Rqz.ort']:
@@ -130,9 +135,9 @@ class EOSConfig:
         if self.experiment.lambdaRange!= Defaults.lambdaRange:
             mask += f' -l {" ".join(str(ff) for ff in self.experiment.lambdaRange)}'
         if self.reduction.thetaRange != Defaults.thetaRange:
-            mask += f' -T {" ".join(str(ff) for ff in self.reduction.thetaRange)}'
+            mask += f' -t {" ".join(str(ff) for ff in self.reduction.thetaRange)}'
         elif self.reduction.thetaRangeR != Defaults.thetaRangeR:
-            mask += f' -t {" ".join(str(ff) for ff in self.reduction.thetaRangeR)}'
+            mask += f' -T {" ".join(str(ff) for ff in self.reduction.thetaRangeR)}'
         if self.experiment.qzRange!= Defaults.qzRange:
             mask += f' -q {" ".join(str(ff) for ff in self.experiment.qzRange)}'
 

libeos/reduction.py

@@ -22,10 +22,12 @@ class AmorReduction:
         self.header = Header()
         self.header.reduction.call = config.call_string()
 
+        self.monitorUnit = {'n': 'cnts', 'p': 'mC', 't': 's'}
+
     def reduce(self):
-        if not os.path.exists(f'{self.reader_config.dataPath}'):
-            logging.debug(f'Creating destination path {self.reader_config.dataPath}')
-            os.system(f'mkdir {self.reader_config.dataPath}')
+        if not os.path.exists(f'{self.output_config.outputPath}'):
+            logging.debug(f'Creating destination path {self.output_config.outputPath}')
+            os.system(f'mkdir {self.output_config.outputPath}')
 
         # load or create normalisation matrix
         if self.reduction_config.normalisationFileIdentifier:
@@ -76,12 +78,13 @@ class AmorReduction:
     def read_unsliced(self, i):
         lamda_e = self.file_reader.lamda_e
         detZ_e  = self.file_reader.detZ_e
+        self.monitor = np.sum(self.file_reader.monitorPerPulse)
+        logging.warning(f'    monitor = {self.monitor:8.2f} {self.monitorUnit[self.experiment_config.monitorType]}')
         qz_lz, qx_lz, ref_lz, err_lz, res_lz, lamda_lz, theta_lz, int_lz, self.mask_lz = self.project_on_lz(
                 self.file_reader, self.norm_lz, self.normAngle, lamda_e, detZ_e)
-        monitor = self.file_reader.monitor
-        if monitor>1 :
-            ref_lz /= monitor
-            err_lz /= monitor
+        #if self.monitor>1 :
+        #    ref_lz /= self.monitor
+        #    err_lz /= self.monitor
         try:
             ref_lz *= self.reduction_config.scale[i]
             err_lz *= self.reduction_config.scale[i]
@@ -170,7 +173,8 @@ class AmorReduction:
                 j += 1
 
     def read_timeslices(self, i):
-        wallTime_e = self.file_reader.wallTime_e
+        wallTime_e = np.float64(self.file_reader.wallTime_e)/1e9
+        pulseTimeS = np.float64(self.file_reader.pulseTimeS)/1e9
         interval = self.reduction_config.timeSlize[0]
         try:
             start = self.reduction_config.timeSlize[1]
@@ -181,13 +185,17 @@ class AmorReduction:
         except:
             stop = wallTime_e[-1]
         # make overwriting log lines possible by removing newline at the end
-        logging.StreamHandler.terminator = "\r"
+        #logging.StreamHandler.terminator = "\r"
+        logging.warning(f'    time slizing')
+        logging.info('      slize  time  monitor')
         for ti, time in enumerate(np.arange(start, stop, interval)):
-            logging.warning(f' time slize {ti:4d}')
 
             filter_e = np.where((time<wallTime_e) & (wallTime_e<time+interval), True, False)
             lamda_e = self.file_reader.lamda_e[filter_e]
             detZ_e = self.file_reader.detZ_e[filter_e]
+            filter_m = np.where((time<pulseTimeS) & (pulseTimeS<time+interval), True, False)
+            self.monitor = np.sum(self.file_reader.monitorPerPulse[filter_m])
+            logging.info(f'      {ti:<4d}  {time:5.0f}  {self.monitor:7.2f} {self.monitorUnit[self.experiment_config.monitorType]}')
 
             qz_lz, qx_lz, ref_lz, err_lz, res_lz, lamda_lz, theta_lz, int_lz, mask_lz = self.project_on_lz(
                     self.file_reader, self.norm_lz, self.normAngle, lamda_e, detZ_e)
@@ -220,17 +228,17 @@ class AmorReduction:
             orso_data = fileio.OrsoDataset(headerRqz, data)
             self.datasetsRqz.append(orso_data)
         # reset normal logging behavior
-        logging.StreamHandler.terminator = "\n"
-        logging.warning(f' time slizing, done')
+        #logging.StreamHandler.terminator = "\n"
+        logging.info(f'      done  {time+interval:5.0f}')
 
     def save_Rqz(self):
-        fname = os.path.join(self.reader_config.dataPath, f'{self.output_config.outputName}.Rqz.ort')
+        fname = os.path.join(self.output_config.outputPath, f'{self.output_config.outputName}.Rqz.ort')
         logging.warning(f'    {fname}')
         theSecondLine = f' {self.header.experiment.title} | {self.header.experiment.start_date} | sample {self.header.sample.name} | R(q_z)'
         fileio.save_orso(self.datasetsRqz, fname, data_separator='\n', comment=theSecondLine)
 
     def save_Rtl(self):
-        fname = os.path.join(self.reader_config.dataPath, f'{self.output_config.outputName}.Rlt.ort')
+        fname = os.path.join(self.output_config.outputPath, f'{self.output_config.outputName}.Rlt.ort')
         logging.warning(f'    {fname}')
         theSecondLine = f' {self.header.experiment.title} | {self.header.experiment.start_date} | sample {self.header.sample.name} | R(lambda, theta)'
         fileio.save_orso(self.datasetsRlt, fname, data_separator='\n', comment=theSecondLine)
@@ -298,7 +306,7 @@ class AmorReduction:
         return q_q[1:], R_q, dR_q, dq_q
 
     def loadRqz(self, name):
-        fname = os.path.join(self.reader_config.dataPath, name)
+        fname = os.path.join(self.output_config.outputPath, name)
         if os.path.exists(fname):
             fileName = fname
         elif os.path.exists(f'{fname}.Rqz.ort'):
@@ -311,12 +319,12 @@ class AmorReduction:
         return q_q, Sq_q, dS_q, fileName
 
     def create_normalisation_map(self, short_notation):
-        dataPath = self.reader_config.dataPath
+        outputPath = self.output_config.outputPath
         normalisation_list = expand_file_list(short_notation)
         name = str(normalisation_list[0])
         for i in range(1, len(normalisation_list), 1):
             name = f'{name}_{normalisation_list[i]}'
-        n_path = os.path.join(dataPath, f'{name}.norm')
+        n_path = os.path.join(outputPath, f'{name}.norm')
         if os.path.exists(n_path):
             logging.warning(f'normalisation matrix: found and using {n_path}')
             with open(n_path, 'rb') as fh:
@@ -336,7 +344,7 @@ class AmorReduction:
             self.normAngle     = fromHDF.nu - fromHDF.mu
             lamda_e          = fromHDF.lamda_e
             detZ_e           = fromHDF.detZ_e
-            self.normMonitor = fromHDF.monitor 
+            self.normMonitor = np.sum(fromHDF.monitorPerPulse)
             self.norm_lz, bins_l, bins_z = np.histogram2d(lamda_e, detZ_e, bins = (self.grid.lamda(), self.grid.z()))
             self.norm_lz = np.where(self.norm_lz>2, self.norm_lz, np.nan)
             # correct for the SM reflectivity
@@ -380,7 +388,11 @@ class AmorReduction:
         mask_lz   = np.where(np.isnan(norm_lz), False, True)
         mask_lz   = np.logical_and(mask_lz, np.where(np.absolute(thetaN_lz)>5e-3, True, False))
         mask_lz   = np.logical_and(mask_lz, np.where(np.absolute(alphaF_lz)>5e-3, True, False))
-        if self.reduction_config.thetaRange[1]<12:
+        if self.reduction_config.thetaRangeR[1]<12:
+          t0 = fromHDF.nu - fromHDF.mu
+          mask_lz   = np.logical_and(mask_lz, np.where(alphaF_lz-t0 >= self.reduction_config.thetaRangeR[0], True, False))
+          mask_lz   = np.logical_and(mask_lz, np.where(alphaF_lz-t0 <= self.reduction_config.thetaRangeR[1], True, False))
+        elif self.reduction_config.thetaRange[1]<12:
           mask_lz   = np.logical_and(mask_lz, np.where(alphaF_lz >= self.reduction_config.thetaRange[0], True, False))
           mask_lz   = np.logical_and(mask_lz, np.where(alphaF_lz <= self.reduction_config.thetaRange[1], True, False))
         else:
@@ -388,10 +400,6 @@ class AmorReduction:
                                               fromHDF.nu - fromHDF.mu + fromHDF.div/2]
           mask_lz   = np.logical_and(mask_lz, np.where(alphaF_lz >= self.reduction_config.thetaRange[0], True, False))
           mask_lz   = np.logical_and(mask_lz, np.where(alphaF_lz <= self.reduction_config.thetaRange[1], True, False))
-        if self.reduction_config.thetaRangeR[1]<12:
-          t0 = fromHDF.nu - fromHDF.mu
-          mask_lz   = np.logical_and(mask_lz, np.where(alphaF_lz-t0 >= self.reduction_config.thetaRangeR[0], True, False))
-          mask_lz   = np.logical_and(mask_lz, np.where(alphaF_lz-t0 <= self.reduction_config.thetaRangeR[1], True, False))
         if self.experiment_config.lambdaRange[1]<15:
           mask_lz   = np.logical_and(mask_lz, np.where(lamda_lz >= self.experiment_config.lambdaRange[0], True, False))
           mask_lz   = np.logical_and(mask_lz, np.where(lamda_lz <= self.experiment_config.lambdaRange[1], True, False))
@@ -416,19 +424,24 @@ class AmorReduction:
 
         if self.reduction_config.normalisationMethod == 'o':
             logging.debug('      assuming an overilluminated sample and correcting for the angle of incidence')
-            ref_lz    = (int_lz * np.absolute(thetaN_lz)) / (norm_lz * np.absolute(thetaF_lz)) * self.normMonitor
+            ref_lz    = (int_lz * np.absolute(thetaN_lz)) / (norm_lz * np.absolute(thetaF_lz))
         elif self.reduction_config.normalisationMethod == 'u':
             logging.debug('      assuming an underilluminated sample and ignoring the angle of incidence')
-            ref_lz    = (int_lz / norm_lz) * self.normMonitor
+            ref_lz    = (int_lz / norm_lz)
         elif self.reduction_config.normalisationMethod == 'd':
             logging.debug('      assuming direct beam for normalisation and ignoring the angle of incidence')
             norm_lz = np.flip(norm_lz,1)
-            ref_lz    = (int_lz / norm_lz) * self.normMonitor
+            ref_lz    = (int_lz / norm_lz)
         else:
             logging.error('unknown normalisation method! Use [u], [o] or [d]')
-            ref_lz    = (int_lz * np.absolute(thetaN_lz)) / (norm_lz * np.absolute(thetaF_lz)) * self.normMonitor
+            ref_lz    = (int_lz * np.absolute(thetaN_lz)) / (norm_lz * np.absolute(thetaF_lz))
+        if self.monitor > 1e-6 :
+            ref_lz   *= self.normMonitor / self.monitor
+        else:
+            logging.warning('   too small monitor value for normalisation -> ignoring monitors')
         err_lz    = ref_lz * np.sqrt( 1/(int_lz+.1) + 1/norm_lz ) 
 
+        # TODO: allow for non-ideal Delta lambda / lambda (rather than 2.2%)
         res_lz    = np.ones((np.shape(lamda_l[:-1])[0], np.shape(alphaF_z)[0])) * 0.022**2
         res_lz    = res_lz + (0.008/alphaF_lz)**2
         res_lz    = qz_lz * np.sqrt(res_lz)

pyproject.toml

@@ -0,0 +1,6 @@
+[build-system]
+requires = [
+    "setuptools>=42",
+    "wheel"
+]
+build-backend = "setuptools.build_meta"

setup.cfg

@@ -0,0 +1,32 @@
+[bdist_wheel]
+universal = 1
+
+[metadata]
+name = amor_eos
+version = attr: libeos.__version__
+author = Jochen Stahn - Paul Scherrer Institut
+author_email = jochen.stahn@psi.ch
+description = EOS reflectometry reduction for AMOR instrument
+long_description = Reduces data obtained by focusing time of flight neutron reflectivity to full reflectivity curve.
+license = MIT
+classifiers =
+    Programming Language :: Python :: 3
+    License :: OSI Approved :: MIT License
+    Operating System :: OS Independent
+    Topic :: Scientific/Engineering
+    Development Status :: 5 - Production/Stable
+
+[options]
+python_requires = >=3.8
+packages =
+    libeos
+scripts =
+    eos.py
+install_requires =
+    numpy
+    h5py
+    orsopy
+    numba
+
+[project.urls]
+Homepage = "https://github.com/jochenstahn/amor"

tests/test_full_analysis.py

@@ -21,15 +21,14 @@ class FullAmorTest(TestCase):
         self.pr.enable()
         self.reader_config = options.ReaderConfig(
                 year=2023,
-                dataPath=os.path.join('..', "test_data"),
-                raw=(os.path.join('..', "test_data"),)
+                rawPath=(os.path.join('..', "test_data"),),
                 )
 
     def tearDown(self):
         self.pr.disable()
         for fi in ['test.Rqz.ort', '614.norm']:
             try:
-                os.unlink(os.path.join(self.reader_config.dataPath, fi))
+                os.unlink(os.path.join(self.reader_config.rawPath[0], fi))
             except FileNotFoundError:
                 pass
 
@@ -38,6 +37,8 @@ class FullAmorTest(TestCase):
         experiment_config = options.ExperimentConfig(
                 chopperPhase=-13.5,
                 chopperPhaseOffset=-5,
+                monitorType=options.Defaults.monitorType,
+                lowCurrentThreshold=options.Defaults.lowCurrentThreshold,
                 yRange=(11., 41.),
                 lambdaRange=(2., 15.),
                 qzRange=(0.005, 0.30),
@@ -60,7 +61,8 @@ class FullAmorTest(TestCase):
                 )
         output_config = options.OutputConfig(
                 outputFormats=["Rqz.ort"],
-                outputName='test'
+                outputName='test',
+                outputPath=os.path.join('..', 'test_results'),
                 )
         config=options.EOSConfig(self.reader_config, experiment_config, reduction_config, output_config)
         # run three times to get similar timing to noslicing runs
@@ -75,6 +77,8 @@ class FullAmorTest(TestCase):
         experiment_config = options.ExperimentConfig(
                 chopperPhase=-13.5,
                 chopperPhaseOffset=-5,
+                monitorType=options.Defaults.monitorType,
+                lowCurrentThreshold=options.Defaults.lowCurrentThreshold,
                 yRange=(11., 41.),
                 lambdaRange=(2., 15.),
                 qzRange=(0.005, 0.30),
@@ -91,12 +95,13 @@ class FullAmorTest(TestCase):
                 thetaRangeR=(-12., 12.),
                 fileIdentifier=["610", "611", "608,612-613", "609"],
                 scale=[1],
-                normalisationFileIdentifier=["614"],
+                normalisationFileIdentifier=["608"],
                 autoscale=(True, True)
                 )
         output_config = options.OutputConfig(
                 outputFormats=["Rqz.ort"],
-                outputName='test'
+                outputName='test',
+                outputPath=os.path.join('..', 'test_results'),
                 )
         config=options.EOSConfig(self.reader_config, experiment_config, reduction_config, output_config)
         reducer = reduction.AmorReduction(config)

windows_build.spec

@@ -12,7 +12,7 @@ a = Analysis(
     runtime_hooks=[],
     excludes=[],
     noarchive=False,
-    optimize=0,
+    optimize=1,
 )
 pyz = PYZ(a.pure)
 

windows_folder.spec

@@ -0,0 +1,44 @@
+# -*- mode: python ; coding: utf-8 -*-
+
+
+a = Analysis(
+    ['eos.py'],
+    pathex=[],
+    binaries=[],
+    datas=[],
+    hiddenimports=[],
+    hookspath=[],
+    hooksconfig={},
+    runtime_hooks=[],
+    excludes=[],
+    noarchive=False,
+    optimize=1,
+)
+pyz = PYZ(a.pure)
+
+exe = EXE(
+    pyz,
+    a.scripts,
+    [],
+    exclude_binaries=True,
+    name='eos',
+    debug=False,
+    bootloader_ignore_signals=False,
+    strip=False,
+    upx=True,
+    console=True,
+    disable_windowed_traceback=False,
+    argv_emulation=False,
+    target_arch=None,
+    codesign_identity=None,
+    entitlements_file=None,
+)
+coll = COLLECT(
+    exe,
+    a.binaries,
+    a.datas,
+    strip=False,
+    upx=True,
+    upx_exclude=[],
+    name='eos',
+)