Merge branch 'master' into development

.gitlab-ci.yml

@@ -63,7 +63,6 @@ conda:build:windows:
     - win
   script:
     - conda activate base
-    - cd tools && git pull --force && cd..
     - .\tools\build.bat
 
 conda:test:linux:

conda-recipe/meta.yaml

@@ -33,6 +33,7 @@ requirements:
     - hdf5
     - python
     - setuptools
+    - typing             # [py27]
     - numpy
   run:
     - python

doc/conf.py

@@ -180,8 +180,7 @@
 # index.html
 release_highlights_dir = Path("..") / "examples" / "release_highlights"
 # Finds the highlight with the latest version number
-latest_highlights = sorted(release_highlights_dir.glob(
-    "plot_release_highlights_*.py"))[-1]
+latest_highlights = sorted(release_highlights_dir.glob("plot_release_highlights_*.py"))[-1]
 latest_highlights = latest_highlights.with_suffix('').name
 html_context["release_highlights"] = \
     f"auto_examples/release_highlights/{latest_highlights}"

doc/templates/index.html

@@ -102,15 +102,15 @@ <h4 class="sk-landing-subheader text-white font-italic mb-3">time-tagged time-re
     <div class="col-md-4 mb-3 px-md-2 sk-px-xl-4">
       <div class="card h-100">
         <div class="card-body">
-          <a href="model_selection.html#model-selection"><h4 class="sk-card-title card-title">Photon distribution analysis</h4></a>
-          <p class="card-text">Recover fluorescence lifetimes and distance distributions.</p>
+          <a href="modules/pda.html"><h4 class="sk-card-title card-title">Photon distribution analysis</h4></a>
+          <p class="card-text">Analyze intensities and recover distances.</p>
           <p class="card-text"><strong>Applications:</strong> Interaction studies, recover distances</br>
           <strong>Methods:</strong>
           <a href="modules/lifetime_analysis.html#maximum-likelihood-estimation">MLE</a>,
           and <a href="modules/lifetime_analysis.html">more...</a></p>
         </div>
         <div class="overflow-hidden mx-2 text-center flex-fill">
-          <a href="auto_examples/single_molecule/plot_single_molecule_pda_2.html"  aria-label="Photon distribution analysis">
+          <a href="auto_examples/single_molecule/plot_single_molecule_pda_2.html"  aria-label="modPhoton distribution analysis">
             <img src="_images/sphx_glr_plot_single_molecule_pda_2_001.png" class="sk-index-img" alt="Demonstration of a PDA">
           </a>
         </div>
@@ -148,7 +148,7 @@ <h4 class="sk-landing-call-header">News</h4>
 
           <li><strong>On-going development:</strong>
             <a href="whats_new.html"><strong>What's new</strong> (Changelog)</a>
-          <li><strong>April 2021.</strong> tttrlib 0.21.2 is available for download (<a href="whats_new/v0.21.0.html#version-0-0-21">Changelog</a>).
+          <li><strong>January 2024.</strong> tttrlib 0.25.0 is available for download (<a href="whats_new/v0.21.0.html#version-0-0-21">Changelog</a>).
           <li><strong>tttrlib from 0.21 requires Python 3.8 or greater.</strong>
           </li>
         </ul>

doc/themes/scikit-learn-modern/nav.html

@@ -53,7 +53,7 @@
           <a class="sk-nav-link nav-link" href="{{ pathto('api/index') }}">API</a>
         </li>
         <li class="nav-item">
-          <a class="sk-nav-link nav-link" href="{{ pathto('examples/index') }}">Applications</a>
+          <a class="sk-nav-link nav-link" href="{{ pathto('auto_examples/index') }}">Applications</a>
         </li>
         {%- for title, link in drop_down_navigation %}
         <li class="nav-item">

examples/tttr/plot_tttr_header.py

@@ -24,7 +24,8 @@
 """
 
 import tttrlib
-data = tttrlib.TTTR('./test/data/bh/bh_spc132.spc', 'SPC-130')
+
+data = tttrlib.TTTR('../../tttr-data/bh/pq/bh_spc132.spc', 'SPC-130')
 # the header can be accesses by the method get_header or as an property
 header = data.header
 
@@ -40,10 +41,10 @@
 # attribute modifies the header / meta data of a TTTR object.
 
 import json
-data = tttrlib.TTTR('./test/data/PQ/PTU/PQ_PTU_HH_T3.PTU', 'PTU')
+data = tttrlib.TTTR('./test/data/PQ/PTU/pq_ptu_hh_t3.ptu', 'PTU')
 
 #%%
-# the header can be accesses by the method get_header or as an property
+# the header can be accesses by the method get_header or as a property
 
 header = data.header
 header_json = header.json
@@ -89,7 +90,7 @@
 # Creating and writing TTTRHeader
 # ===============================
 # Each TTTR object has an attribute that is an instance of the TTTRHeader class.
-#     This instances makes the meta data contained in the TTTR file accessible. TTTRHeader
+#     This instances makes the meta-data contained in the TTTR file accessible. TTTRHeader
 # objects can also be created independently of TTTR object.
 
 header = tttrlib.TTTRHeader()
@@ -105,7 +106,7 @@
 
 #%%
 # The JSON string must contain a `tags` list. The `tags` list is a list of dictionarys
-# in which each dictionary corresponds to a meta data field in the header. For instance,
+# in which each dictionary corresponds to a meta-data field in the header. For instance,
 
 print(header.json) # '{\n "tags": []\n}'
 

ext/python/Correlator.py

@@ -14,7 +14,6 @@ def __getattr__(self, item):
     else:
         raise AttributeError
 
-
 @property
 def correlation(self):
     return self.get_corr_normalized()

pyproject.toml

@@ -82,7 +82,6 @@ select = "cp3{8,9,10}-*"
 
     before-all = [
         "yum update -y --nogpgcheck",
-        "yum update -y",
         "yum install -y epel-release",
         "yum -y install boost-devel swig cmake"
     ]

src/TTTR.cpp

@@ -268,6 +268,9 @@ int TTTR::read_file(const char *fn, int container_type) {
             header = new TTTRHeader(fp, container_type);
             fp_records_begin = header->end();
             tttr_record_type = header->get_tttr_record_type();
+#ifdef VERBOSE_TTTRLIB
+            std::clog << "-- TTTR record type: " << tttr_record_type << std::endl;
+#endif
             processRecord = processRecord_map[tttr_record_type];
             n_records_in_file =
                 get_number_of_records_by_file_size(
@@ -373,6 +376,9 @@ void TTTR::read_records(
         size_t chunk
 ) {
     n_rec = n_rec < n_records_in_file ? n_rec : n_records_in_file;
+#ifdef VERBOSE_TTTRLIB
+    std::cout << "-- Records that will be read : " << n_rec << std::endl;
+#endif
     if(rewind) fseek(fp, (long) fp_records_begin, SEEK_SET);
 
     // The data is read in two steps. In the first step bigger data chunks