Source Code for Module functions.jw_mf

  1  from Numeric import Float64, zeros 
  2  from re import match 
  3   
  4 -class Jw: 
  5 -        def __init__(self): 
  6                  "Function for creating the model-free spectral density values." 
  7   
  8   
  9 -        def Jw(self): 
 10                  """Function to create the model-free spectral density values." 
 11   
 12                  The spectral density equation 
 13                  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 
 14   
 15                  Data structure:  self.data.jw 
 16                  Dimension:  2D, (number of NMR frequencies, 5 spectral density frequencies) 
 17                  Type:  Numeric matrix, Float64 
 18                  Dependencies:  None 
 19                  Required by:  self.data.ri, self.data.dri, self.data.d2ri 
 20   
 21   
 22                  Formulae 
 23                  ~~~~~~~~ 
 24   
 25                  Original 
 26                  ~~~~~~~~ 
 27   
 28                                   2 /    S2 . tm        (1 - S2) . te' \  
 29                          J(w)  =  - | -------------  +  -------------- | 
 30                                   5 \ 1 + (w.tm)**2     1 + (w.te')**2 / 
 31   
 32   
 33                  Extended 
 34                  ~~~~~~~~ 
 35   
 36                                   2 /    S2 . tm        (1 - Sf2) . tf'     (S2f - S2) . ts' \  
 37                          J(w)  =  - | -------------  +  ---------------  +  ---------------- | 
 38                                   5 \ 1 + (w.tm)**2     1 + (w.tf')**2       1 + (w.ts')**2  / 
 39   
 40                  """ 
 41   
 42                  # Calculate frequency independent terms (to increase speed) 
 43                  self.initialise_jw_values() 
 44   
 45                  # Initialise the spectral density values. 
 46                  self.data.jw = zeros((self.mf.data.num_frq, 5), Float64) 
 47   
 48                  # Isotropic rotational diffusion. 
 49                  if match(self.data.diff_type, 'iso'): 
 50                          if match('m[13]', self.data.model): 
 51                                  for i in range(self.mf.data.num_frq): 
 52                                          self.data.jw[i, 0] = self.calc_jw_iso_m13(i, 0) 
 53                                          self.data.jw[i, 1] = self.calc_jw_iso_m13(i, 1) 
 54                                          self.data.jw[i, 2] = self.calc_jw_iso_m13(i, 2) 
 55                                          self.data.jw[i, 3] = self.calc_jw_iso_m13(i, 3) 
 56                                          self.data.jw[i, 4] = self.calc_jw_iso_m13(i, 4) 
 57                          elif match('m[24]', self.data.model): 
 58                                  for i in range(self.mf.data.num_frq): 
 59                                          self.data.jw[i, 0] = self.calc_jw_iso_m24(i, 0) 
 60                                          self.data.jw[i, 1] = self.calc_jw_iso_m24(i, 1) 
 61                                          self.data.jw[i, 2] = self.calc_jw_iso_m24(i, 2) 
 62                                          self.data.jw[i, 3] = self.calc_jw_iso_m24(i, 3) 
 63                                          self.data.jw[i, 4] = self.calc_jw_iso_m24(i, 4) 
 64                          elif match('m5', self.data.model): 
 65                                  for i in range(self.mf.data.num_frq): 
 66                                          self.data.jw[i, 0] = self.calc_jw_iso_m5(i, 0) 
 67                                          self.data.jw[i, 1] = self.calc_jw_iso_m5(i, 1) 
 68                                          self.data.jw[i, 2] = self.calc_jw_iso_m5(i, 2) 
 69                                          self.data.jw[i, 3] = self.calc_jw_iso_m5(i, 3) 
 70                                          self.data.jw[i, 4] = self.calc_jw_iso_m5(i, 4) 
 71   
 72                  # Axially symmetric rotational diffusion. 
 73                  elif match(self.data.diff_type, 'axail'): 
 74                          raise NameError, "Axially symetric diffusion not implemented yet, quitting program." 
 75   
 76                  # Anisotropic rotational diffusion. 
 77                  elif match(self.data.diff_type, 'aniso'): 
 78                          raise NameError, "Anisotropic diffusion not implemented yet, quitting program." 
 79   
 80                  else: 
 81                          raise NameError, "Diffusion type set incorrectly, quitting program." 
 82   
 83   
 84 -        def calc_jw_iso_m13(self, i, frq_index): 
 85                  "Calculate the model 1 and 3 spectral density values for isotropic rotational diffusion." 
 86   
 87                  temp = 0.4 * (self.data.s2_tm / (1.0 + self.data.omega_tm_sqrd[i, frq_index])) 
 88                  return temp 
 89   
 90   
 91 -        def calc_jw_iso_m24(self, i, frq_index): 
 92                  "Calculate the model 2 and 4 spectral density values for isotropic rotational diffusion." 
 93   
 94                  temp = 0.4 * (self.data.s2_tm / (1.0 + self.data.omega_tm_sqrd[i, frq_index]) + (1.0 - self.data.s2) * self.data.te_prime / (1.0 + self.data.omega_te_prime_sqrd[i, frq_index])) 
 95                  return temp 
 96   
 97   
 98 -        def calc_jw_iso_m5(self, i, frq_index): 
 99                  "Calculate the model 5 spectral density values for isotropic rotational diffusion." 
100   
101                  temp = 0.4 * self.data.s2f * (self.data.s2s_tm / (1.0 + self.data.omega_tm_sqrd[i, frq_index]) + (1.0 - self.data.s2s) * self.data.ts_prime / (1.0 + self.data.omega_ts_prime_sqrd[i, frq_index])) 
102                  return temp 
103   
104   
105 -        def initialise_jw_values(self): 
106                  "Remap the parameters in self.data.params" 
107   
108                  # Isotropic dependent values. 
109                  if match(self.data.diff_type, 'iso'): 
110                          self.data.tm = self.data.diff_params 
111                          self.data.tm_sqrd = self.data.tm ** 2 
112                          self.data.omega_tm_sqrd = zeros((self.mf.data.num_frq, 5), Float64) 
113   
114                  # Diffusion independent values. 
115                  if match('m[13]', self.data.model): 
116                          self.data.s2 = self.data.params[0] 
117                          self.data.s2_tm = self.data.s2 * self.data.tm 
118   
119                  elif match('m[24]', self.data.model): 
120                          self.data.s2 = self.data.params[0] 
121                          self.data.te = self.data.params[1] 
122                          self.data.fact_a = self.data.tm / (self.data.te + self.data.tm) 
123                          self.data.te_prime = self.data.te * self.data.fact_a 
124                          self.data.te_prime_sqrd = self.data.te_prime ** 2 
125                          self.data.s2_tm = self.data.s2 * self.data.tm 
126                          self.data.omega_te_prime_sqrd = zeros((self.mf.data.num_frq, 5), Float64) 
127   
128                  elif match('m5', self.data.model): 
129                          self.data.s2f = self.data.params[0] 
130                          self.data.s2s = self.data.params[1] 
131                          self.data.s2 = self.data.s2f * self.data.s2s 
132                          self.data.ts = self.data.params[2] 
133                          self.data.fact_a = self.data.tm / (self.data.ts + self.data.tm) 
134                          self.data.ts_prime = self.data.ts * self.data.fact_a 
135                          self.data.ts_prime_sqrd = self.data.ts_prime ** 2 
136                          self.data.s2s_tm = self.data.s2s * self.data.tm 
137                          self.data.omega_ts_prime_sqrd = zeros((self.mf.data.num_frq, 5), Float64) 
138   
139                  for i in range(self.mf.data.num_frq): 
140                          for frq_index in range(5): 
141                                  self.data.omega_tm_sqrd[i, frq_index] = self.mf.data.frq_sqrd_list[i][frq_index] * self.data.tm_sqrd 
142                                  if match('m[24]', self.data.model): 
143                                          self.data.omega_te_prime_sqrd[i, frq_index] = self.mf.data.frq_sqrd_list[i][frq_index] * self.data.te_prime_sqrd 
144                                  elif match('m5', self.data.model): 
145                                          self.data.omega_ts_prime_sqrd[i, frq_index] = self.mf.data.frq_sqrd_list[i][frq_index] * self.data.ts_prime_sqrd 
146