Source Code for Module maths_fns.consistency_tests

  1  ############################################################################### 
  2  #                                                                             # 
  3  # Copyright (C) 2004 Edward d'Auvergne                                        # 
  4  # Copyright (C) 2007-2008 Sebastien Morin                                     # 
  5  #                                                                             # 
  6  # This file is part of the program relax.                                     # 
  7  #                                                                             # 
  8  # relax is free software; you can redistribute it and/or modify               # 
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 10  # the Free Software Foundation; either version 2 of the License, or           # 
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 13  # relax is distributed in the hope that it will be useful,                    # 
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 16  # GNU General Public License for more details.                                # 
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 20  # Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA  02111-1307  USA   # 
 21  #                                                                             # 
 22  ############################################################################### 
 23   
 24  from Numeric import Float64, zeros 
 25  from math import pi, cos 
 26   
 27  from ri_comps import calc_fixed_csa, calc_fixed_dip, comp_csa_const_func, comp_dip_const_func 
 28   
 29   
 30 -class Consistency: 
 31 -    def __init__(self, frq=None, gx=None, gh=None, mu0=None, h_bar=None): 
 32          """Consistency tests for data acquired at different magnetic fields. 
 33   
 34          These three tests are used to assess the consistency of datasets aquired at different 
 35          magnetic fields. Inconsistency can affect extracted information from experimental data and 
 36          can be caused by variations in temperature, concentration, pH, water suppression, etc. 
 37   
 38          This code calculates three functions for each residue. When comparing datasets from 
 39          different magnetic field, the value should be the same for each function as these are field 
 40          independent. The J(0) function is the spectral density at the zero frequency and is obtained 
 41          using a reduced spectral density approach. The F_eta and F_R2 functions are the 
 42          consistency functions proposed by Fushman D. et al. (1998) JACS, 120: 10947-10952. 
 43   
 44          To assess the consistency of its datasets, one should first calculate those values (J(0), 
 45          F_eta and F_R2) for each field. Then, the user should compare values obtained for different 
 46          magnetic fields. Comparisons could proceed using correlation plots and histograms, and the 
 47          user could also calculate correlation, skewness and kurtosis coefficients. 
 48          """ 
 49   
 50          # Initialise the data container. 
 51          self.data = Data() 
 52   
 53          # Add the initial data to self.data. 
 54          self.data.gx = gx 
 55          self.data.gh = gh 
 56          self.data.mu0 = mu0 
 57          self.data.h_bar = h_bar 
 58   
 59          # The number of frequencies. 
 60          self.data.num_frq = 1 
 61   
 62          # Dipolar and CSA data structures. 
 63          self.data.dip_const_fixed = 0.0 
 64          self.data.csa_const_fixed = [0.0] 
 65          self.data.dip_const_func = 0.0 
 66          self.data.csa_const_func = zeros(1, Float64) 
 67   
 68          # Nuclear frequencies. 
 69          frq = frq * 2 * pi 
 70          frqX = frq * self.data.gx / self.data.gh 
 71   
 72          # Calculate the five frequencies which cause R1, R2, and NOE relaxation. 
 73          self.data.frq_list = zeros((1, 5), Float64) 
 74          self.data.frq_list[0, 1] = frqX 
 75          self.data.frq_list[0, 2] = frq - frqX 
 76          self.data.frq_list[0, 3] = frq 
 77          self.data.frq_list[0, 4] = frq + frqX 
 78          self.data.frq_sqrd_list = self.data.frq_list ** 2 
 79   
 80   
 81 -    def calc_sigma_noe(self, noe, r1): 
 82          """Function for calculating the sigma NOE value.""" 
 83   
 84          return (noe - 1.0) * r1 * self.data.gx / self.data.gh 
 85   
 86   
 87 -    def func(self, orientation=None, tc=None, r=None, csa=None, r1=None, r2=None, noe=None): 
 88          """Function for calculating the three consistency testing values. 
 89   
 90          Three values are returned, J(0), F_eta and F_R2. 
 91          """ 
 92   
 93          # Calculate the fixed component of the dipolar and CSA constants. 
 94          calc_fixed_dip(self.data) 
 95          calc_fixed_csa(self.data) 
 96   
 97          # Calculate the dipolar and CSA constants. 
 98          comp_dip_const_func(self.data, r) 
 99          comp_csa_const_func(self.data, csa) 
100   
101          # Rename the dipolar and CSA constants. 
102          d = self.data.dip_const_func 
103          c = self.data.csa_const_func[0] 
104   
105          # Calculate the sigma NOE value. 
106          sigma_noe = self.calc_sigma_noe(noe, r1) 
107   
108          # Calculate J(0). 
109          j0 = -1.5 / (3.0*d + c) * (0.5*r1 - r2 + 0.6*sigma_noe) 
110   
111          # Calculate J(wX). 
112          jwx = 1.0 / (3.0*d + c) * (r1 - 1.4*sigma_noe) 
113   
114          # Calculate P_2. 
115          # p_2 is a second rank Legendre polynomial as p_2(x) = 0.5 * (3 * (x ** 2) -1) 
116          # where x is the cosine of the angle Theta when expressed in radians. 
117          # 
118          # Note that the angle Theta (called 'orientation' in relax) is the angle between the 15N-1H 
119          # vector and the principal axis of the 15N chemical shift tensor. 
120          p_2 = 0.5 * ((3.0 * (cos(orientation * pi / 180)) ** 2) -1) 
121   
122          # Calculate eta. 
123          # eta is the cross-correlation rate between 15N CSA and 15N-1H dipolar interaction. It is 
124          # expressed here as proposed in Fushman D. & Cowburn D. (1998) JACS, 120: 7109-7110. 
125          eta = ((d * c/3.0) ** 0.5) * (4.0 * j0 + 3.0 * jwx) * p_2 
126   
127          # Calculate F_eta. 
128          # F_eta is independent of the magnetic field for residues with local mobility 
129          f_eta = eta * self.data.gh / (self.data.frq_list[0, 3] * (4.0 + 3.0 / (1 + (self.data.frq_list[0, 1] * tc) ** 2))) 
130   
131          # Calculate P_HF. 
132          # P_HF is the contribution to R2 from high frequency motions. 
133          # P_HF = 0.5 * d * [J(wH-wN) + 6 * J(wH) + 6 * J(wH+wN)]. 
134          # Here, P_HF is described using a reduced spectral density approach. 
135          p_hf = 1.3 * (self.data.gx / self.data.gh) * (1.0 - noe) * r1 
136   
137          # Calculate F_R2. 
138          # F_R2 tests the consistency of the transverse relaxation data. 
139          f_r2 = (r2 - p_hf) / ((4.0 + 3.0 / (1 + (self.data.frq_list[0, 1] * tc) ** 2)) * (d + c/3.0)) 
140   
141          # Return the three values. 
142          return j0, f_eta, f_r2 
143   
144   
145 -class Data: 
146 -    def __init__(self): 
147          """Empty container for storing data.""" 
148