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trajectory_analysis.py

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  • Gabriel Studer's avatar
    Studer Gabriel authored
    This commit doesn't make OpenStructure work with Python 3. The goal of this
    commit was to perform an automated port of the Python code and make it compile.
    The performed steps:
    
    - Edited CMakeLists.txt to search for Python with 3.6 as min version 3.6 is the
      Python version shipped by default with Ubuntu 18.04 LTS
    - Add version 3.6 to cmake_support/FindPython.cmake
    - Adapt setup_boost macro in cmake_support/OST.cmake to prefer versioned
      libraries and not first check for boost_python.so. In the example of
      Ubuntu 18.04, libboost_python.so is specific for Python 2 but
      libboost_python3.so is the one we want.
    - apply the following command: 2to3-2.7 -n -w <OST_DIR>
    - adapt base/pymod/wrap_base.cc, gui/pymod/wrap_gui.cc and
      gui/pymod/export_message_widget.cc as PyString functionalities do not exist
      anymore in the Python 3 interpreter (replaced by PyUnicode)
    - adapt gui/src/python_shell/python_interpreter_worker.hh to resolve issue
      discussed in https://stackoverflow.com/questions/23068700/embedding-python3-in-qt-5
      Long story short: Qt does a typedef for "slots" which causes trouble with
      other headers that are pulled in from the Python interpreter
    6e60b71d
    History
    trajectory_analysis.py 9.69 KiB
    """
    **This Module requires numpy**
    
    This module contains functions to analyze trajectories, mainly 
    similiraty measures baed on RMSDS and pairwise distances.
    
    Author: Niklaus Johner (niklaus.johner@unibas.ch)
    """
    
    import ost.mol.alg
    import ost.geom
    from ost import LogError
    import os
    
    def smooth(vec,n):
    #Function to smooth a vector or a list of floats
    #for each element it takes the average over itself and the
    #n elements on each side, so over (2n+1) elements
      try:
        vec2=vec.copy()
      except:
        vec2=vec[:]
      for i in range(n):
        v=0.0
        count=1.0
        v+=vec[i]
        for j in range(n):
          count+=1
          v+=vec[i+j+1]
        for j in range(i):
          count+=1
          v+=vec[i-(j+1)]
        vec2[i]=v/float(count)
      for i in range(1,n+1):
        v=0.0
        count=1.0
        v+=vec[-i]
        for j in range(n):
          count+=1
          v+=vec[-(i+j+1)]
        for j in range(i-1):
          count+=1
          v+=vec[-i+j+1]
        vec2[-i]=v/float(count)
      for i in range(n,len(vec2)-n):
        v=vec[i]
        for j in range(n):
          v+=vec[i+j+1]
          v+=vec[i-j-1]
        vec2[i]=v/float(2.*n+1.)
      return vec2
    
    
    """
    From here on the module needs numpy
    """
    
    def RMSD_Matrix_From_Traj(t,sele,first=0,last=-1,align=True,align_sele=None):
      """
      This function calculates a matrix M such that M[i,j] is the
      RMSD (calculated on **sele**) between frames i and j of the trajectory **t**
      aligned on sele.
    
      :param t: the trajectory
      :param sele: the selection used for alignment and RMSD calculation
      :param first: the first frame of t to be used
      :param last: the last frame of t to be used
      :type t: :class:`~ost.mol.CoordGroupHandle`
      :type sele: :class:`~ost.mol.EntityView`
      :type first: :class:`int`
      :type last: :class:`int`
    
      :return: Returns a numpy N\ :subscript:`frames`\ xN\ :subscript:`frames` matrix, 
       where N\ :subscript:`frames` is the number of frames.
      """
      if not align_sele:align_sele=sele
      try:
        import numpy as npy
        if last==-1:last=t.GetFrameCount()
        n_frames=last-first
        rmsd_matrix=npy.identity(n_frames)
        for i in range(n_frames):
          if align:
            t=ost.mol.alg.SuperposeFrames(t,align_sele,begin=first,end=last,ref=i)
            eh=t.GetEntity()
          t.CopyFrame(i)
          rmsd_matrix[i,:]=ost.mol.alg.AnalyzeRMSD(t,sele,sele)
          if i==0:
            last=last-first
            first=0
        return rmsd_matrix
      except ImportError:
        LogError("Function needs numpy, but I could not import it.")
        raise
    
    
    def PairwiseDistancesFromTraj(t,sele,first=0,last=-1,seq_sep=1):
      """
      This function calculates the distances between any pair of atoms in **sele**  
      with sequence separation larger than **seq_sep** from a trajectory **t**.
      It return a matrix containing one line for each atom pair and N\ :subscript:`frames` columns, where
      N\ :subscript:`frames` is the number of frames in the trajectory.
      
      :param t: the trajectory
      :param sele: the selection used to determine the atom pairs
      :param first: the first frame of t to be used
      :param last: the last frame of t to be used
      :param seq_sep: The minimal sequence separation between atom pairs
      :type t: :class:`~ost.mol.CoordGroupHandle`
      :type sele: :class:`~ost.mol.EntityView`
      :type first: :class:`int`
      :type last: :class:`int`
      :type seq_sep: :class:`int`
    
      :return: a numpy N\ :subscript:`pairs`\ xN\ :subscript:`frames` matrix.
      """
      try:
        import numpy as npy
        if last==-1:last=t.GetFrameCount()
        n_frames=last-first
        n_var=0
        for i,a1 in enumerate(sele.atoms):
          for j,a2 in enumerate(sele.atoms):
            if not j-i<seq_sep:n_var+=1
        #n_var=sele.GetAtomCount()
        #n_var=(n_var-1)*(n_var)/2.
        dist_matrix=npy.zeros(n_frames*n_var)
        dist_matrix=dist_matrix.reshape(n_var,n_frames)
        k=0
        for i,a1 in enumerate(sele.atoms):
          for j,a2 in enumerate(sele.atoms):
            if j-i<seq_sep:continue
            dist_matrix[k]=ost.mol.alg.AnalyzeDistanceBetwAtoms(t,a1.GetHandle(),a2.GetHandle())[first:last]
            k+=1
        return dist_matrix
      except ImportError:
        LogError("Function needs numpy, but I could not import it.")
        raise
        
    def DistanceMatrixFromPairwiseDistances(distances,p=2):
      """
      This function calculates an distance matrix M(N\ :subscript:`frames`\ xN\ :subscript:`frames`\ ) from
      the pairwise distances matrix D(N\ :subscript:`pairs`\ xN\ :subscript:`frames`\ ), where 
      N\ :subscript:`frames` is the number of frames in the trajectory
      and N\ :subscript:`pairs` the number of atom pairs.
      M[i,j] is the distance between frame i and frame j
      calculated as a p-norm of the differences in distances
      from the two frames (distance-RMSD for p=2).
    
      :param distances: a pairwise distance matrix as obtained from 
       :py:func:`~mol.alg.trajectory_analysis.PairwiseDistancesFromTraj`
      :param p: exponent used for the p-norm.
    
      :return: a numpy N\ :subscript:`frames`\ xN\ :subscript:`frames` matrix, where N\ :subscript:`frames`
       is the number of frames.
      """
      try:
        import numpy as npy
        n1=distances.shape[0]
        n2=distances.shape[1]
        dist_mat=npy.identity(n2)
        for i in range(n2):
          for j in range(n2):
            if j<=i:continue
            d=(((abs(distances[:,i]-distances[:,j])**p).sum())/float(n1))**(1./p)
            dist_mat[i,j]=d
            dist_mat[j,i]=d
        return dist_mat
      except ImportError:
        LogError("Function needs numpy, but I could not import it.")
        raise
    
    def DistRMSDFromTraj(t,sele,ref_sele,radius=7.0,average=False,seq_sep=4,first=0,last=-1):
      """
      This function calculates the distance RMSD from a trajectory.
      The distances selected for the calculation are all the distances
      between pair of atoms from residues that are at least **seq_sep** apart
      in the sequence and that are smaller than **radius** in **ref_sel**.
      The number and order of atoms in **ref_sele** and **sele** should be the same.
    
      :param t: the trajectory
      :param sele: the selection used to calculate the distance RMSD
      :param ref_sele: the reference selection used to determine the atom pairs and reference distances
      :param radius: the upper limit of distances in ref_sele considered for the calculation
      :param seq_sep: the minimal sequence separation between atom pairs considered for the calculation 
      :param average: use the average distance in the trajectory as reference instead of the distance obtained from ref_sele
      :param first: the first frame of t to be used
      :param last: the last frame of t to be used
      
      :type t: :class:`~ost.mol.CoordGroupHandle`
      :type sele: :class:`~ost.mol.EntityView`
      :type ref_sele: :class:`~ost.mol.EntityView`
      :type radius: :class:`float`
      :type average: :class:`bool`
      :type first: :class:`int`
      :type last: :class:`int`
      :type seq_sep: :class:`int`
    
      :return: a numpy vecor dist_rmsd(N\ :subscript:`frames`).  
      """
      if not sele.GetAtomCount()==ref_sele.GetAtomCount():
        print('Not same number of atoms in the two views')
        return
      try:
        import numpy as npy
        if last==-1:last=t.GetFrameCount()
        n_frames=last-first
        dist_rmsd=npy.zeros(n_frames)
        pair_count=0.0
        for i,a1 in enumerate(ref_sele.atoms):
          for j,a2 in enumerate(ref_sele.atoms):
            if j<=i:continue
            r1=a1.GetResidue()
            c1=r1.GetChain()
            r2=a2.GetResidue()
            c2=r2.GetChain()      
            if c1==c2 and abs(r2.GetNumber().num-r1.GetNumber().num)<seq_sep:continue
            d=ost.geom.Distance(a1.pos,a2.pos)
            if d<radius:
              a3=sele.atoms[i]
              a4=sele.atoms[j]
              d_traj=ost.mol.alg.AnalyzeDistanceBetwAtoms(t,a3.GetHandle(),a4.GetHandle())[first:last]
              if average:d=npy.mean(d_traj)
              for k,el in enumerate(d_traj):
                dist_rmsd[k]+=(el-d)**2.0
              pair_count+=1.0
        return (dist_rmsd/float(pair_count))**0.5
      except ImportError:
        LogError("Function needs numpy, but I could not import it.")
        raise
        
    def AverageDistanceMatrixFromTraj(t,sele,first=0,last=-1):
      """
      This function calcultes the distance between each pair of atoms
      in **sele**, averaged over the trajectory **t**.
    
      :param t: the trajectory
      :param sele: the selection used to determine the atom pairs
      :param first: the first frame of t to be used
      :param last: the last frame of t to be used
      :type t: :class:`~ost.mol.CoordGroupHandle`
      :type sele: :class:`~ost.mol.EntityView`
      :type first: :class:`int`
      :type last: :class:`int`
    
      :return: a numpy N\ :subscript:`pairs`\ xN\ :subscript:`pairs` matrix, where N\ :subscript:`pairs`
       is the number of atom pairs in **sele**.
      """
      try:
        import numpy as npy
      except ImportError:
        LogError("Function needs numpy, but I could not import it.")
        raise
      n_atoms=sele.GetAtomCount()
      M=npy.zeros([n_atoms,n_atoms])
      for i,a1 in enumerate(sele.atoms):
        for j,a2 in enumerate(sele.atoms):
          if j>i:continue
          d=ost.mol.alg.AnalyzeDistanceBetwAtoms(t,a1.GetHandle(),a2.GetHandle())[first:last]
          M[i,j]=npy.mean(d)
          M[j,i]=npy.mean(d)
      return M
    
    def AnalyzeDistanceFluctuationMatrix(t,sele,first=0,last=-1):
      try:
        import numpy as npy
      except ImportError:
        LogError("Function needs numpy, but I could not import it.")
        raise
      n_atoms=sele.GetAtomCount()
      M=npy.zeros([n_atoms,n_atoms])
      for i,a1 in enumerate(sele.atoms):
        for j,a2 in enumerate(sele.atoms):
          if i>j:continue
          d=ost.mol.alg.AnalyzeDistanceBetwAtoms(t,a1.GetHandle(),a2.GetHandle())[first:last]
          M[j,i]=npy.std(d)
          M[i,j]=npy.std(d)
      return M
      
    def IterativeSuperposition(t,sele,threshold=1.0,initial_sele=None,iterations=5,ref_frame=0):
      if initial_sele:current_sele=initial_sele
      else: current_sele=sele
      for i in range(iterations):
        t=ost.mol.alg.SuperposeFrames(t,current_sele,ref=ref_frame)
        al=[a for a in sele.atoms if ost.mol.alg.AnalyzeRMSF(t,ost.mol.CreateViewFromAtoms([a]))<threshold]
        if len(al)==0:return
        current_sele=ost.mol.CreateViewFromAtoms(al)
      return current_sele