Merge pull request #29 from scipion-em/devel

Release 3.1.1

CHANGES.txt

@@ -1,2 +1,4 @@
+v3.1.1:
+  - Installer updated: binaries are automatically downloaded now. Thanks to José Jesús Fernández.
 v3.1.0:
   - First plugin release

README.rst

@@ -1,6 +1,22 @@
-==============================
-Scipion - TomoSegMemTV plugin
-==============================
+=====================================================
+Scipion plugin for TomoSegMemTV and MembraneAnnotator
+=====================================================
+
+.. image:: https://img.shields.io/pypi/v/scipion-em-tomosegmemtv.svg
+        :target: https://pypi.python.org/pypi/scipion-em-tomosegmemtv
+        :alt: PyPI release
+
+.. image:: https://img.shields.io/pypi/l/scipion-em-tomosegmemtv.svg
+        :target: https://pypi.python.org/pypi/scipion-em-tomosegmemtv
+        :alt: License
+
+.. image:: https://img.shields.io/pypi/pyversions/scipion-em-tomosegmemtv.svg
+        :target: https://pypi.python.org/pypi/scipion-em-tomosegmemtv
+        :alt: Supported Python versions
+
+.. image:: https://img.shields.io/pypi/dm/scipion-em-tomosegmemtv
+        :target: https://pypi.python.org/pypi/scipion-em-tomosegmemtv
+        :alt: Downloads
 
 Scipion plugin for segmentation and annotation of membranes in tomograms (with TomoSegmenTV_ and memb-annotator_,
 respectively)
@@ -30,25 +46,6 @@ The plugin can be installed in user (stable) or developer (latest, may be unstab
 
     scipion3 installp -p local/path/to/scipion-em-tomosegmemtv --devel
 
-
-=====================================
-Getting the binaries for tomoSegmenTV
-=====================================
-
-TomoSegmenTV binaries must be downloaded from the following site
-https://sites.google.com/site/3demimageprocessing/tomosegmemtv, where a form must be filled and submitted to get
-instant download access. Download the standalone version (which will be a zip file), unzip it and move the binary file
-to the directory SCIPION_HOME/software/em/TOMOSEGMEMB_DIRECTORY/tomoSegMemTV/bin/. It can be directly done executing
-the following command on a terminal:
-
-.. code-block::
-
-    cd DOWNLOADED_FILE_DIRECTORY
-
-.. code-block::
-
-    unzip DOWNLOADED/FILE -d SCIPION_HOME/software/em/TOMOSEGMEM_DIRECTORY/tomoSegMemTV/bin/
-
 =========
 Protocols
 =========

setup.py

@@ -28,18 +28,40 @@
 setup(
     name='scipion-em-tomosegmemtv',  # Required
     version=__version__,  # Required
-    description='Scipion plugin tomosegmemtv.',  # Required
+    description='Scipion plugin for softare packages tomosegmemTV and membraneAnnotator.',  # Required
     long_description=long_description,  # Optional
-    url='https://github.com/scipion-em/scipion-em-tomosegmembtv',  # Optional
-    author='you',  # Optional
-    author_email='[email protected]',  # Optional
+    url='https://github.com/scipion-em/scipion-em-tomosegmemtv',  # Optional
+    author='I2PC',  # Optional
+    author_email='[email protected]',  # Optional
     keywords='scipion cryoem cryoet imageprocessing scipion-3.0',  # Optional
     packages=find_packages(),
     install_requires=[requirements],
     entry_points={
         'pyworkflow.plugin': 'tomosegmemtv = tomosegmemtv'
     },
     package_data={  # Optional
-       'tomosegmemtv': ['protocols.conf', 'icon.png'],
-    }
+        'tomosegmemtv': ['protocols.conf', 'icon.png'],
+    },
+    # For a list of valid classifiers, see
+    # https://pypi.python.org/pypi?%3Aaction=list_classifiers
+    classifiers=[  # Optional
+        # How mature is this project? Common values are
+        #   3 - Alpha
+        #   4 - Beta
+        #   5 - Production/Stable
+        'Development Status :: Production/Stable',
+
+        # Indicate who your project is intended for
+        #   'Intended Audience :: Users',
+
+        # Pick your license as you wish
+        'License :: OSI Approved :: GNU General Public License v3 (GPLv3)',
+
+        # Specify the Python versions you support here. In particular, ensure
+        # that you indicate whether you support Python 2, Python 3 or both.
+        'Programming Language :: Python :: 3',
+
+        # Specify Framework
+        'Framework :: Scipion :: 3'
+    ],
 )

tomosegmemtv/__init__.py

@@ -31,21 +31,21 @@
 import pwem
 import os
 
-from pyworkflow.utils import Environ
+from pyworkflow.utils import Environ, replaceExt
 
 from tomosegmemtv.constants import TOMOSEGMEMTV_HOME, TOMOSEGMEMTV, TOMOSEGMEMTV_DEFAULT_VERSION, MEMBANNOTATOR, \
     MEMBANNOTATOR_DEFAULT_VERSION, MEMBANNOTATOR_EM_DIR, TOMOSEGMEMTV_DIR, TOMOSEGMEMTV_EM_DIR, MEMBANNOTATOR_BIN
 
 _references = ['MartinezSanchez2014']
-__version__ = '3.1.0'
+__version__ = '3.1.1'
 _logo = "icon.png"
 
 
 class Plugin(pwem.Plugin):
 
     _homeVar = TOMOSEGMEMTV_HOME
     _pathVars = [TOMOSEGMEMTV_HOME]
-    _url = "https://github.com/scipion-em/scipion-em-tomosegmemtv"
+    _url = "https://sites.google.com/site/3demimageprocessing/tomosegmemtv"
 
     @classmethod
     def _defineVariables(cls):
@@ -76,20 +76,27 @@ def defineBinaries(cls, env):
         pluginHome = join(pwem.Config.EM_ROOT, TOMOSEGMEMTV_EM_DIR)
         tomoSegmenTVHome = join(pluginHome, TOMOSEGMEMTV)
         membraneAnnotatorHome = join(pluginHome, MEMBANNOTATOR_EM_DIR)
-        # membraneAnnotatorTar = join(pwem.Config.EM_ROOT, MEMBANNOTATOR_EM_DIR + '.tar.gz')
 
-        TOMOSEGMEMTV_INSTALLED = '%s_installed' % TOMOSEGMEMTV
-
-        # TomosegmenTV: only the directory will be generated, because the binaries must be downloaded manually from José
-        # Jesús website, filling a form
-        installationCmd = cls._genMembAnnCmd(membraneAnnotatorHome)
-        installationCmd += 'mkdir %s && ' % tomoSegmenTVHome
-        installationCmd += 'cd %s && ' % pluginHome
-        installationCmd += 'touch %s' % TOMOSEGMEMTV_INSTALLED  # Flag installation finished
+        pattern = '%s_installed'
+        TOMOSEGMEMTV_INSTALLED = pattern % TOMOSEGMEMTV
+        MEMBRANE_ANN_INSTALLED = pattern % MEMBANNOTATOR
+
+        # Tomosegmemtv installation cmd
+        dlZipFileName = TOMOSEGMEMTV + '.zip'
+        tomosegmemtvInstallCmd = 'wget http://tiny.cc/vvu7vz -O %s && ' % dlZipFileName
+        tomosegmemtvInstallCmd += 'mkdir %s && ' % tomoSegmenTVHome
+        tomosegmemtvInstallCmd += 'unzip %s -d %s && ' % (dlZipFileName, tomoSegmenTVHome)
+        tomosegmemtvInstallCmd += 'touch %s' % TOMOSEGMEMTV_INSTALLED
+
+        # Membrane annotator installation cmd
+        membAnnInstallCmd = cls._genMembAnnCmd(membraneAnnotatorHome)
+        membAnnInstallCmd += 'cd %s && ' % pluginHome
+        membAnnInstallCmd += 'touch %s' % MEMBRANE_ANN_INSTALLED  # Flag installation finished
         env.addPackage(TOMOSEGMEMTV,
                        version=TOMOSEGMEMTV_DEFAULT_VERSION,
                        tar='void.tgz',
-                       commands=[(installationCmd, TOMOSEGMEMTV_INSTALLED)],
+                       commands=[(tomosegmemtvInstallCmd, TOMOSEGMEMTV_INSTALLED),
+                                 (membAnnInstallCmd, MEMBRANE_ANN_INSTALLED)],
                        neededProgs=["wget", "tar"],
                        default=True)
 
@@ -105,7 +112,7 @@ def getProgram(cls, program):
     @classmethod
     def runTomoSegmenTV(cls, protocol, program, args, cwd=None):
         """ Run tomoSegmenTV command from a given protocol. """
-        protocol.runJob( cls.getProgram(program), args, cwd=cwd)
+        protocol.runJob(cls.getProgram(program), args, cwd=cwd)
 
     @classmethod
     def getMCRPath(cls):

tomosegmemtv/protocols/protocol_annotate_membranes.py

@@ -26,7 +26,6 @@
 from enum import Enum
 
 from pwem.protocols import EMProtocol
-from pyworkflow import BETA
 from pyworkflow.object import Integer
 from pyworkflow.protocol import PointerParam
 from pyworkflow.utils import removeBaseExt
@@ -44,7 +43,6 @@ class ProtAnnotateMembranes(EMProtocol):
     """ Manual annotation tool for segmented membranes
     """
     _label = 'annotate segmented membranes'
-    _devStatus = BETA
     _possibleOutputs = outputObjects
 
     def __init__(self, **kwargs):

tomosegmemtv/protocols/protocol_resize_tomomask.py

@@ -31,7 +31,6 @@
 import numpy as np
 from pwem.emlib.image import ImageHandler
 from pwem.protocols import EMProtocol
-from pyworkflow import BETA
 from pyworkflow.protocol import PointerParam
 from pyworkflow.utils import Message, removeBaseExt, getExt, getParentFolder
 from tomo.objects import SetOfTomoMasks, TomoMask
@@ -45,7 +44,6 @@ class ProtResizeSegmentedVolume(EMProtocol):
     """Resize segmented volumes or annotated (TomoMasks)."""
 
     _label = 'Resize segmented or annotated volume'
-    _devStatus = BETA
     _possibleOutputs = outputObjects
     resizedFileList = []
 

tomosegmemtv/protocols/protocol_tomosegmentv.py

@@ -27,7 +27,6 @@
 from os import remove
 from os.path import abspath
 from pwem.protocols import EMProtocol
-from pyworkflow import BETA
 from pyworkflow.protocol import PointerParam, IntParam, GT, FloatParam, BooleanParam, LEVEL_ADVANCED
 from pyworkflow.utils import Message, removeBaseExt, replaceBaseExt, createLink
 from tomo.objects import SetOfTomoMasks, TomoMask
@@ -55,7 +54,6 @@ class ProtTomoSegmenTV(EMProtocol):
     """Segment membranes in tomograms"""
 
     _label = 'tomogram segmentation'
-    _devStatus = BETA
     _possibleOutputs = outputObjects
     tomoMaskListDelineated = []
 
@@ -145,6 +143,8 @@ def _defineParams(self, form):
                            '   - Saliency --> *filename%s.mrc*' % (S2, TV, SURF, TV2, FLT)
                       )
 
+        form.addParallelSection(threads=8, mpi =1)
+
     def _insertAllSteps(self):
         self._insertFunctionStep(self.convertInputStep)
         for tomo in self.inTomograms.get():
@@ -162,22 +162,25 @@ def convertInputStep(self):
     def runTomoSegmenTV(self, tomoFile):
         tomoBaseName = removeBaseExt(tomoFile)
         tomoFile = self._getExtraPath(tomoBaseName + '.mrc')
+
+        Nthreads = self.numberOfThreads.get()
+
         # Scale space
         s2OutputFile = self._getExtraPath(tomoBaseName + S2 + MRC)
-        Plugin.runTomoSegmenTV(self, SCALE_SPACE, self._getScaleSpaceCmd(tomoFile, s2OutputFile))
+        Plugin.runTomoSegmenTV(self, SCALE_SPACE, self._getScaleSpaceCmd(tomoFile, Nthreads, s2OutputFile))
         # Tensor voting
         tVOutputFile = self._getExtraPath(tomoBaseName + TV + MRC)
-        Plugin.runTomoSegmenTV(self, 'dtvoting', self._getTensorVotingCmd(s2OutputFile, tVOutputFile))
+        Plugin.runTomoSegmenTV(self, 'dtvoting', self._getTensorVotingCmd(s2OutputFile, tVOutputFile, Nthreads))
         # Surfaceness
         surfOutputFile = self._getExtraPath(tomoBaseName + SURF + MRC)
-        Plugin.runTomoSegmenTV(self, 'surfaceness', self._getSurfCmd(tVOutputFile, surfOutputFile))
+        Plugin.runTomoSegmenTV(self, 'surfaceness', self._getSurfCmd(tVOutputFile, surfOutputFile, Nthreads))
         # Tensor voting - second round (to fill potential gaps and increase the robustness of the surfaceness map)
         tV2OutputFile = self._getExtraPath(tomoBaseName + TV2 + MRC)
         Plugin.runTomoSegmenTV(self, 'dtvoting',
-                               self._getTensorVotingCmd(surfOutputFile, tV2OutputFile, isFirstRound=False))
+                               self._getTensorVotingCmd(surfOutputFile, tV2OutputFile, Nthreads, isFirstRound=False))
         # Saliency - second round (apply again the surfaceness program, but this time to produce the saliency)
         salOutputFile = self._getExtraPath(tomoBaseName + FLT + MRC)
-        Plugin.runTomoSegmenTV(self, 'surfaceness', self._getSalCmd(tV2OutputFile, salOutputFile))
+        Plugin.runTomoSegmenTV(self, 'surfaceness', self._getSalCmd(tV2OutputFile, salOutputFile, Nthreads))
         self.tomoMaskListDelineated.append(salOutputFile)
         # Remove intermediate files if requested
         if not self.keepAllFiles.get():
@@ -221,33 +224,37 @@ def _validate(self):
 
     # --------------------------- UTIL functions -----------------------------------
 
-    def _getScaleSpaceCmd(self, inputFile, outputFile):
+    def _getScaleSpaceCmd(self, inputFile, Nthreads, outputFile):
         outputCmd = '-s %s ' % self.mbThkPix.get()
         outputCmd += '%s ' % inputFile
         outputCmd += '%s ' % outputFile
+        outputCmd += ' -t %i' % Nthreads
         return outputCmd
 
-    def _getTensorVotingCmd(self, inputFile, outputFile, isFirstRound=True):
+    def _getTensorVotingCmd(self, inputFile, outputFile, Nthreads, isFirstRound=True):
         outputCmd = '-s %s ' % self.mbScaleFactor.get()
         if isFirstRound and not self.blackOverWhite.get():
             outputCmd += '-w '
         elif not isFirstRound:
             outputCmd += '-w '  # After the first tensor voting, the image will be always white over black
         outputCmd += '%s ' % inputFile
         outputCmd += '%s ' % outputFile
+        outputCmd += ' -t %i' % Nthreads
         return outputCmd
 
-    def _getSurfCmd(self, inputFile, outputFile):
+    def _getSurfCmd(self, inputFile, outputFile, Nthreads):
         outputCmd = '-m %s ' % self.mbStrengthTh.get()
         outputCmd += '%s ' % inputFile
         outputCmd += '%s ' % outputFile
+        outputCmd += ' -t %i' % Nthreads
         return outputCmd
 
-    def _getSalCmd(self, inputFile, outputFile):
+    def _getSalCmd(self, inputFile, outputFile, Nthreads):
         outputCmd = '-S '
         outputCmd += '-s %s ' % self.sigmaS.get()
         outputCmd += '-p %s ' % self.sigmaP.get()
         outputCmd += '%s ' % inputFile
         outputCmd += '%s ' % outputFile
+        outputCmd += ' -t %i' % Nthreads
         return outputCmd
 

tomosegmemtv/tests/test_resize_tomomask.py

@@ -64,7 +64,7 @@ def _importTomograms(self):
             samplingRate=self.samplingRate
         )
         protImportTomo = self.launchProtocol(protImportTomo)
-        tomoSet = getattr(protImportTomo, 'outputTomograms', None)
+        tomoSet = protImportTomo.Tomograms
 
         # Validate output tomograms
         self.assertSetSize(tomoSet, size=self.setSize)
@@ -76,7 +76,7 @@ def _importTomograms(self):
     def _normalizeTomo(self, protImportTomo):
         print(magentaStr("\n==> Normalizing the tomograms to binning %i" % self.binning))
         protNormalizeTomo = self.newProtocol(ProtImodTomoNormalization,
-                                             inputSetOfTomograms=getattr(protImportTomo, 'outputTomograms', None),
+                                             inputSetOfTomograms=protImportTomo.Tomograms,
                                              binning=self.binning)
 
         protNormalizeTomo = self.launchProtocol(protNormalizeTomo)
@@ -109,12 +109,12 @@ def _segmentMembranes(self, protNormalizeTomo):
 
         return protTomosegmemTV
 
-    def _resizeTomoMask(self, protTomosegmemTV, protImportTomo):
+    def _resizeTomoMask(self, protTomosegmemTV, protImportTomo:ProtImportTomograms):
         print(magentaStr("\n==> Resizing the tomomasks to the size of the imported tomograms"))
         protResizeTomoMask = self.newProtocol(
             ProtResizeSegmentedVolume,
             inTomoMasks=getattr(protTomosegmemTV, outputObjects.tomoMasks.name, None),
-            inTomos=getattr(protImportTomo, 'outputTomograms', None)
+            inTomos=protImportTomo.Tomograms
         )
         protResizeTomoMask = self.launchProtocol(protResizeTomoMask)
         tomoMaskSet = getattr(protResizeTomoMask, outputObjects.tomoMasks.name, None)

tomosegmemtv/tests/test_tomosegmemtv.py

@@ -59,7 +59,7 @@ def _importTomograms(self):
             samplingRate=self.samplingRate
         )
         protImportTomo = self.launchProtocol(protImportTomo)
-        tomoSet = getattr(protImportTomo, 'outputTomograms', None)
+        tomoSet = protImportTomo.Tomograms
 
         # Validate output tomograms
         self.assertSetSize(tomoSet, size=2)
@@ -68,11 +68,11 @@ def _importTomograms(self):
 
         return protImportTomo
 
-    def _runTomosegmemTV(self, protImportTomo):
+    def _runTomosegmemTV(self, protImportTomo:ProtImportTomograms):
         print(magentaStr("\n==> Segmenting the membranes:"))
         protTomosegmemTV = self.newProtocol(
             ProtTomoSegmenTV,
-            inTomograms=getattr(protImportTomo, 'outputTomograms', None),
+            inTomograms=protImportTomo.Tomograms,
             mbThkPix=2,
             mbScaleFactor=10,
             blackOverWhite=False