Merge pull request #27 from MStarmans91/development

Release 3.2.0

.travis.yml

@@ -20,47 +20,29 @@ matrix:
         - PATH=/c/Python37:/c/Python37/Scripts:$PATH
         - WORCDEBUG=true
       install:
-      - python setup.py -q install
-      - git clone --single-branch --branch develop https://github.com/MStarmans91/WORCTutorial
+        - python setup.py -q install
+        - git clone --single-branch --branch develop https://github.com/MStarmans91/WORCTutorial
       # 'python' points to Python 2.7 on macOS but points to Python 3.8 on Linux and Windows
       # 'python3' is a 'command not found' error on Windows but 'py' works on Windows only.
-      script: python WORCTutorial/WORCTutorialSimple.py
+      script: 
+        - python WORCTutorial/WORCTutorialSimple.py
     - name: "Linux"
       before_install:
-      - sudo apt-get -qq update
-      - sudo apt-get -qq -y install git
-      - pip install numpy # Not doing so may give issues with PyRadiomics, as it depends on numpy upon installation
-      - pip install -r requirements.txt
+       - sudo apt-get -qq update
+       - sudo apt-get -qq -y install git
+       - pip install numpy # Not doing so may give issues with PyRadiomics, as it depends on numpy upon installation
+       - pip install -r requirements.txt
       env:
         - WORCDEBUG=true
       install:
-      - python setup.py -q install
-      - git clone --single-branch --branch develop https://github.com/MStarmans91/WORCTutorial
-      # 'python' points to Python 2.7 on macOS but points to Python 3.8 on Linux and Windows
-      # 'python3' is a 'command not found' error on Windows but 'py' works on Windows only.
+        - python setup.py -q install
+        - git clone --single-branch --branch develop https://github.com/MStarmans91/WORCTutorial
+        # 'python' points to Python 2.7 on macOS but points to Python 3.8 on Linux and Windows
+        # 'python3' is a 'command not found' error on Windows but 'py' works on Windows only.
       script:
-      - python WORCTutorial/WORCTutorialSimple.py
-      - fastr trace /tmp/WORC_Example_STWStrategyHN/__sink_data__.json --sinks features_train_CT_0_predict --samples HN1331
-      - fastr trace /tmp/WORC_Example_STWStrategyHN/__sink_data__.json --sinks features_train_CT_0_pyradiomics --samples HN1331
-      - fastr trace /tmp/WORC_Example_STWStrategyHN/__sink_data__.json --sinks classification --samples all
-    # - name: "MacOS"
-    #   os: osx
-    #   osx_image: xcode11.2  # Python 3.7.4 running on macOS 10.14.4
-    #   language: shell
-    #   before_install:
-    #     - python3 --version
-    #     - pip3 install -U pip
-    #     - pip3 install numpy # Not doing so may give issues with PyRadiomics, as it depends on numpy upon installation
-    #   env:
-    #     - WORCDEBUG=true
-    #   install:
-    #   - python3 setup.py -q install
-    #   - git clone --single-branch --branch develop https://github.com/MStarmans91/WORCTutorial
-    #   # 'python' points to Python 2.7 on macOS but points to Python 3.8 on Linux and Windows
-    #   # 'python3' is a 'command not found' error on Windows but 'py' works on Windows only.
-    #   script:
-    #     - python3 WORCTutorial/WORCTutorialSimple.py
-    #     - fastr trace /var/folders/17/5mc7816d3mndxjqgplq6057w0000gn/T/WORC_Example_STWStrategyHN4/__sink_data__.json --sinks features_train_CT_0 --samples HN1331
+        - python WORCTutorial/WORCTutorialSimple.py
+        - fastr trace /tmp/WORC_Example_STWStrategyHN/__sink_data__.json --sinks features_train_CT_0_predict --samples HN1331
+        - fastr trace /tmp/WORC_Example_STWStrategyHN/__sink_data__.json --sinks classification --samples all
 
 notifications:
   slack:

CHANGELOG

@@ -6,13 +6,40 @@ All notable changes to this project will be documented in this file.
 The format is based on `Keep a Changelog <http://keepachangelog.com/>`_
 and this project adheres to `Semantic Versioning <http://semver.org/>`_
 
-3.1.4 - 2020-05-22
+3.2.0 - 2020-06-26
+------------------
+
+Added
+~~~~~~~
+- Labelprocessing can now also handle having patient ID in the feature files.
+  Was required for ComBat.
+
+Changed
+~~~~~~~
+- Output of plot_SVM function is better ordered.
+- Several defaults, as we now have PyRadiomics fully embedded, resulting in
+  a large increase in features.
+- No more overrides for the full config, as the default now is the full config.
+
+Fixed
+~~~~~
+- Cardinality of decomposition tool was incorrect.
+- ComBat integration in WORC network now works properly.
+- Documentation didn't build due to C-extension dependencies of PyRadiomics,
+  and thus therefore also PREDICT. Fixed in setup.py and readthedocs files.
+- Documentation building.
+- Bugfix in segmentix test output url.
+- Bugfix in SimpleWORC facade when using features.
+- Warning when using Evaluation pipeline without images.
+
+
+3.1.4 - 2020-05-26
 ------------------
 
 Added
 ~~~~~~~
 - Catch error if number of segmentations supplied does not match number of
-  images. 
+  images.
 - Add support in SimpleWORC and BasicWORC for multiple segmentations per
   patient.
 - Chi2 test in statistical testing.

README.md

@@ -1,11 +1,11 @@
-# WORC v3.1.4
+# WORC v3.2.0
 ## Workflow for Optimal Radiomics Classification
 
 ## Information
 
-| Linux                          | Windows                       | Documentation                 | PyPi                          |
-|--------------------------------|-------------------------------|-------------------------------|-------------------------------|
-| [![][tci-linx]][tci-linx-lnk]  | [![][tci-wind]][tci-wind-lnk] | [![][doc]][doc-lnk]           | [![][pypi]][pypi-lnk]         |
+| Linux                          | Windows                       | Documentation                 | PyPi                          |Citing WORC          |
+|--------------------------------|-------------------------------|-------------------------------|-------------------------------|---------------------|
+| [![][tci-linx]][tci-linx-lnk]  | [![][tci-wind]][tci-wind-lnk] | [![][doc]][doc-lnk]           | [![][pypi]][pypi-lnk]         | [![][DOI]][DOI-lnk] | 
 
 [tci-linx]: https://travis-ci.com/MStarmans91/WORC.svg?token=qyvaeq7Cpwu7hJGB98Gp&branch=master&job=1
 [tci-linx-lnk]: https://travis-ci.com/MStarmans91/WORC
@@ -19,6 +19,9 @@
 [pypi]: https://badge.fury.io/py/WORC.svg
 [pypi-lnk]: https://badge.fury.io/py/WORC
 
+[DOI]: https://zenodo.org/badge/DOI/10.5281/zenodo.3840534.svg
+[DOI-lnk]: https://zenodo.org/badge/latestdoi/92295542
+
 # Introduction
 
 WORC is an open-source python package for the easy execution of full radiomics pipelines.
@@ -84,7 +87,7 @@ Besides a Jupyter notebook with instructions, we provide there also an example s
 ## License
 This package is covered by the open source [APACHE 2.0 License](APACHE-LICENSE-2.0).
 
-When using WORC, please cite this repository using the following DOI: [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3840534.svg)](https://zenodo.org/badge/latestdoi/92295542)
+When using WORC, please cite this repository using the following DOI: [![][DOI]][DOI-lnk].
 
 ## Contact
 We are happy to help you with any questions. Please sent us a mail or place an issue on the Github.

README.rst

@@ -1,4 +1,4 @@
-WORC v3.1.4
+WORC v3.2.0
 ===========
 
 Workflow for Optimal Radiomics Classification
@@ -7,11 +7,12 @@ Workflow for Optimal Radiomics Classification
 Information
 -----------
 
-+--------------------+-------------------+-------------------+-------------------+
-| Linux              | Windows           | Documentation     | PyPi              |
-+====================+===================+===================+===================+
-| |image0|           | |image1|          | |image2|          | |image3|          |
-+--------------------+-------------------+-------------------+-------------------+
++-----------------+-----------------+-----------------+-----------------+------------+
+| Linux           | Windows         | Documentation   | PyPi            | Citing     |
+|                 |                 |                 |                 | WORC       |
++=================+=================+=================+=================+============+
+| |image0|        | |image1|        | |image2|        | |image3|        | |image4|   |
++-----------------+-----------------+-----------------+-----------------+------------+
 
 Introduction
 ============
@@ -114,7 +115,8 @@ License
 This package is covered by the open source `APACHE 2.0
 License <APACHE-LICENSE-2.0>`__.
 
-When using WORC, please cite this repository.
+When using WORC, please cite this repository using the following DOI:
+|image5|.
 
 Contact
 -------
@@ -183,3 +185,7 @@ to input them on every request.
    :target: https://worc.readthedocs.io/en/latest/?badge=latest
 .. |image3| image:: https://badge.fury.io/py/WORC.svg
    :target: https://badge.fury.io/py/WORC
+.. |image4| image:: https://zenodo.org/badge/DOI/10.5281/zenodo.3840534.svg
+   :target: https://zenodo.org/badge/latestdoi/92295542
+.. |image5| image:: https://zenodo.org/badge/DOI/10.5281/zenodo.3840534.svg
+   :target: https://zenodo.org/badge/latestdoi/92295542

WORC/IOparser/file_io.py

@@ -49,6 +49,7 @@ def load_data(featurefiles, patientinfo=None, label_names=None, modnames=[]):
     # Read out all feature values and labels
     image_features_temp = list()
     feature_labels_all = list()
+    pids = list()
     for i_patient in range(0, len(featurefiles[0])):
         feature_values_temp = list()
         feature_labels_temp = list()
@@ -67,6 +68,19 @@ def load_data(featurefiles, patientinfo=None, label_names=None, modnames=[]):
         # Also make a list of all unique label names
         feature_labels_all = feature_labels_all + list(set(feature_labels_temp) - set(feature_labels_all))
 
+        # If PID in feature file, use those
+        if 'patient' in list(feat_temp.keys()):
+            pids.append(feat_temp.patient)
+
+    # Check when we found patient ID's, if we did for all objects
+    if pids:
+        if len(pids) != len(image_features_temp):
+            raise WORCexceptions.WORCValueError(f'Length of pids {len(pids)}' +
+                                                'does not match' +
+                                                'number of objects ' +
+                                                str(len(image_features_temp)) +
+                                                f'Found {pids}.')
+
     # If some objects miss certain features, we will identify these with NaN values
     feature_labels_all.sort()
     image_features = list()
@@ -90,11 +104,18 @@ def load_data(featurefiles, patientinfo=None, label_names=None, modnames=[]):
         # We use the feature files of the first modality to match to patient name
         pfiles = featurefiles[0]
         try:
-            label_data, image_features =\
-                lp.findlabeldata(patientinfo,
-                                 label_names,
-                                 pfiles,
-                                 image_features)
+            if pids:
+                label_data, image_features =\
+                    lp.findlabeldata(patientinfo,
+                                     label_names,
+                                     pids=pids,
+                                     objects=image_features)
+            else:
+                label_data, image_features =\
+                    lp.findlabeldata(patientinfo,
+                                     label_names,
+                                     filenames=pfiles,
+                                     objects=image_features)
         except ValueError as e:
             message = str(e) + '. Please take a look at your labels' +\
                 ' file and make sure it is formatted correctly. ' +\
@@ -178,6 +199,7 @@ def convert_config_pyradiomics(config):
     outputconfig = dict()
     outputconfig['imageType'] = dict()
     outputconfig['setting'] = dict()
+    outputconfig['featureClass'] = dict()
 
     # Take out the specific PyRadiomics values
     outputconfig['setting']['geometryTolerance'] = float(config['PyRadiomics']['geometryTolerance'])
@@ -230,4 +252,20 @@ def convert_config_pyradiomics(config):
         sigmas = [int(s) for s in sigmas]
         outputconfig['imageType']['LoG']['sigma'] = sigmas
 
+    # Determine which features to extract:
+    if config['PyRadiomics']['extract_firstorder'] == 'True':
+        outputconfig['featureClass']['firstorder'] = None
+    if config['PyRadiomics']['extract_shape'] == 'True':
+        outputconfig['featureClass']['shape'] = None
+    if config['PyRadiomics']['texture_GLCM'] == 'True':
+        outputconfig['featureClass']['glcm'] = None
+    if config['PyRadiomics']['texture_GLRLM'] == 'True':
+        outputconfig['featureClass']['glrlm'] = None
+    if config['PyRadiomics']['texture_GLSZM'] == 'True':
+        outputconfig['featureClass']['glszm'] = None
+    if config['PyRadiomics']['texture_GLDM'] == 'True':
+        outputconfig['featureClass']['gldm'] = None
+    if config['PyRadiomics']['texture_NGTDM'] == 'True':
+        outputconfig['featureClass']['ngtdm'] = None
+
     return outputconfig