Source Code for Module lib.structure.represent.diffusion_tensor

  1  ############################################################################### 
  2  #                                                                             # 
  3  # Copyright (C) 2003-2010,2012-2014 Edward d'Auvergne                         # 
  4  # Copyright (C) 2008 Sebastien Morin                                          # 
  5  #                                                                             # 
  6  # This file is part of the program relax (http://www.nmr-relax.com).          # 
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  8  # This program is free software: you can redistribute it and/or modify        # 
  9  # it under the terms of the GNU General Public License as published by        # 
 10  # the Free Software Foundation, either version 3 of the License, or           # 
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 16  # GNU General Public License for more details.                                # 
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 19  # along with this program.  If not, see <http://www.gnu.org/licenses/>.       # 
 20  #                                                                             # 
 21  ############################################################################### 
 22   
 23  # Python module imports. 
 24  from numpy import array, dot, float64, transpose 
 25   
 26  # relax module imports. 
 27  from lib.structure.geometric import generate_vector_dist, generate_vector_residues 
 28   
 29   
 30 -def diffusion_tensor(mol=None, tensor=None, tensor_diag=None, diff_type=None, rotation=None, axes=None, sim_axes=None, com=None, scale=1.8e-6): 
 31      """Create the structural representation of the diffusion tensor. 
 32   
 33      @keyword mol:           The molecule container. 
 34      @type mol:              MolContainer instance 
 35      @keyword tensor:        The diffusion tensor. 
 36      @type tensor:           numpy rank-2, 3D array 
 37      @keyword tensor_diag:   The diagonalised diffusion tensor in tensor frame. 
 38      @type tensor_diag:      numpy rank-2, 3D array 
 39      @keyword diff_type:     The type of diffusion tensor.  This can be one of 'sphere', 'oblate', 'prolate', 'ellipsoid'. 
 40      @type diff_type:        str 
 41      @keyword rotation:      The diffusion tensor rotation matrix. 
 42      @type rotation:         numpy rank-2, 3D array 
 43      @keyword axes:          The axis system of the tensor.  For the spheroids this is one vector, for the ellipsoid it should be three vectors. 
 44      @type axes:             list of numpy rank-1, 3D arrays 
 45      @keyword sim_axes:      The axis systems of the tensor for each simulation.  For the spheroids this is one vector, for the ellipsoid it should be three vectors.  The first dimension is the axis type (x, y, or z), the second is the simulation, and the third is the vector. 
 46      @type sim_axes:         None or list of lists of numpy rank-1, 3D arrays 
 47      @keyword com:           The centre of mass of the diffusion structure. 
 48      @type com:              numpy rank-1, 3D array 
 49      @keyword scale:         The scaling factor for the diffusion tensor. 
 50      @type scale:            float 
 51      """ 
 52   
 53      # Initialise. 
 54      ############# 
 55   
 56      # Initialise the residue number. 
 57      res_num = 1 
 58   
 59      # Add the central atom. 
 60      mol.atom_add(pdb_record='HETATM', atom_num=1, atom_name='R', res_name='COM', res_num=res_num, pos=com, segment_id=None, element='C') 
 61   
 62      # Increment the residue number. 
 63      res_num = res_num + 1 
 64   
 65   
 66      # Vector distribution. 
 67      ###################### 
 68   
 69      # Print out. 
 70      print("\nGenerating the geometric object.") 
 71   
 72      # Swap the x and y axes for the prolate spheroid (the vector distributions are centred on the z-axis). 
 73      if diff_type == 'prolate': 
 74          # 90 deg rotation about the diffusion frame z-axis. 
 75          z_rot = array([[  0, -1,  0], 
 76                         [  1,  0,  0], 
 77                         [  0,  0,  1]], float64) 
 78   
 79          # Rotate the tensor and rotation matrix. 
 80          rotation = dot(transpose(rotation), z_rot) 
 81          tensor = dot(z_rot, dot(tensor_diag, transpose(z_rot))) 
 82          tensor = dot(rotation, dot(tensor, transpose(rotation))) 
 83   
 84      # Swap the x and z axes for the oblate spheroid (the vector distributions are centred on the z-axis). 
 85      if diff_type == 'oblate': 
 86          # 90 deg rotation about the diffusion frame y-axis. 
 87          y_rot = array([[  0,  0,  1], 
 88                         [  0,  1,  0], 
 89                         [ -1,  0,  0]], float64) 
 90   
 91          # Rotate the tensor and rotation matrix. 
 92          rotation = dot(transpose(rotation), y_rot) 
 93          tensor = dot(y_rot, dot(tensor_diag, transpose(y_rot))) 
 94          tensor = dot(rotation, dot(tensor, transpose(rotation))) 
 95   
 96      # The distribution. 
 97      generate_vector_dist(mol=mol, res_name='TNS', res_num=res_num, centre=com, R=rotation, warp=tensor, scale=scale, inc=20) 
 98   
 99      # Increment the residue number. 
100      res_num = res_num + 1 
101   
102   
103      # Axes of the tensor. 
104      ##################### 
105   
106      # Create the unique axis of the spheroid. 
107      if diff_type in ['oblate', 'prolate']: 
108          # Print out. 
109          print("\nGenerating the unique axis of the diffusion tensor.") 
110          print("    Scaling factor:                      " + repr(scale)) 
111   
112          # Generate the axes representation. 
113          res_num = generate_vector_residues(mol=mol, vector=axes[0], atom_name='Dpar', res_name_vect='AXS', sim_vectors=sim_axes[0], res_num=res_num, origin=com, scale=scale, neg=True) 
114   
115   
116      # Create the three axes of the ellipsoid. 
117      if diff_type == 'ellipsoid': 
118          # Print out. 
119          print("Generating the three axes of the ellipsoid.") 
120          print("    Scaling factor:                      " + repr(scale)) 
121   
122          # Generate the axes representation. 
123          res_num = generate_vector_residues(mol=mol, vector=axes[0], atom_name='Dx', res_name_vect='AXS', sim_vectors=sim_axes[0], res_num=res_num, origin=com, scale=scale, neg=True) 
124          res_num = generate_vector_residues(mol=mol, vector=axes[1], atom_name='Dy', res_name_vect='AXS', sim_vectors=sim_axes[1], res_num=res_num, origin=com, scale=scale, neg=True) 
125          res_num = generate_vector_residues(mol=mol, vector=axes[2], atom_name='Dz', res_name_vect='AXS', sim_vectors=sim_axes[2], res_num=res_num, origin=com, scale=scale, neg=True) 
126