prompt.diffusion

29 - def __init__(self, relax):

30 # Help. 31 self.__relax_help__ = \ 32 """Class for manipulating the diffusion tensor.""" 33 34 # Add the generic help string. 35 self.__relax_help__ = self.__relax_help__ + "\n" + help.relax_class_help 36 37 # Place relax in the class namespace. 38 self.__relax__ = relax

39 40

41 - def copy(self, run1=None, run2=None):

42 """Function for copying diffusion tensor data from run1 to run2. 43 44 Keyword Arguments 45 ~~~~~~~~~~~~~~~~~ 46 47 run1: The name of the run to copy the sequence from. 48 49 run2: The name of the run to copy the sequence to. 50 51 52 Description 53 ~~~~~~~~~~~ 54 55 This function will copy the diffusion tensor data from 'run1' to 'run2'. 'run2' must not 56 contain any diffusion tensor data. 57 58 59 Examples 60 ~~~~~~~~ 61 62 To copy the diffusion tensor from run 'm1' to run 'm2', type: 63 64 relax> diffusion_tensor.copy('m1', 'm2') 65 """ 66 67 # Function intro text. 68 if self.__relax__.interpreter.intro: 69 text = sys.ps3 + "diffusion_tensor.copy(" 70 text = text + "run1=" + `run1` 71 text = text + ", run2=" + `run2` + ")" 72 print text 73 74 # The run1 argument. 75 if type(run1) != str: 76 raise RelaxStrError, ('run1', run1) 77 78 # The run2 argument. 79 if type(run2) != str: 80 raise RelaxStrError, ('run2', run2) 81 82 # Execute the functional code. 83 self.__relax__.generic.diffusion_tensor.copy(run1=run1, run2=run2)

84 85

86 - def delete(self, run=None):

87 """Function for deleting diffusion tensor data. 88 89 Keyword Arguments 90 ~~~~~~~~~~~~~~~~~ 91 92 run: The name of the run. 93 94 95 96 Description 97 ~~~~~~~~~~~ 98 99 This function will delete all diffusion tensor data for the given run. 100 """ 101 102 # Function intro text. 103 if self.__relax__.interpreter.intro: 104 text = sys.ps3 + "diffusion_tensor.delete(" 105 text = text + "run=" + `run` + ")" 106 print text 107 108 # The run argument. 109 if type(run) != str: 110 raise RelaxStrError, ('run', run) 111 112 # Execute the functional code. 113 self.__relax__.generic.diffusion_tensor.delete(run=run)

114 115

116 - def display(self, run=None):

117 """Function for displaying the diffusion tensor. 118 119 Keyword Arguments 120 ~~~~~~~~~~~~~~~~~ 121 122 run: The name of the run. 123 """ 124 125 # Function intro text. 126 if self.__relax__.interpreter.intro: 127 text = sys.ps3 + "diffusion_tensor.display(" 128 text = text + "run=" + `run` + ")" 129 print text 130 131 # The run argument. 132 if type(run) != str: 133 raise RelaxStrError, ('run', run) 134 135 # Execute the functional code. 136 self.__relax__.generic.diffusion_tensor.display(run=run)

137 138

139 - def set(self, run=None, params=None, time_scale=1.0, d_scale=1.0, angle_units='deg', param_types=0, axial_type=None, fixed=1):

140 """Function for setting up the diffusion tensor. 141 142 Keyword Arguments 143 ~~~~~~~~~~~~~~~~~ 144 145 run: The name of the run to assign the data to. 146 147 params: The diffusion tensor data. 148 149 time_scale: The correlation time scaling value. 150 151 d_scale: The diffusion tensor eigenvalue scaling value. 152 153 angle_units: The units for the angle parameters. 154 155 param_types: A flag to select different parameter combinations. 156 157 axial_type: A string, which if supplied with axially symmetric parameters, will restrict 158 the tensor to either being 'oblate' or 'prolate'. 159 160 fixed: A flag specifying whether the diffusion tensor is fixed or can be optimised. 161 162 163 Description 164 ~~~~~~~~~~~ 165 166 Isotropic diffusion. 167 168 To select isotropic diffusion, the parameters argument should be a single floating point 169 number. The number is the value of the isotropic global correlation time in seconds. To 170 specify the time in nanoseconds, set the 'time_scale' argument to 1e-9. Alternative 171 parameters can be used by changing the 'param_types' flag to the following integers: 172 173 0 - tm (Default) 174 1 - Diso 175 176 where: 177 tm = 1 / 6Diso 178 179 180 Axially symmetric diffusion. 181 182 To select axially symmetric anisotropic diffusion, the parameters argument should be a tuple 183 of floating point numbers of length four. A tuple is a type of data structure enclosed in 184 round brackets, the elements of which are separated by commas. Alternative sets of 185 parameters, 'param_types', are: 186 187 0 - (tm, Da, theta, phi) (Default) 188 1 - (tm, Dratio, theta, phi) 189 2 - (Dpar, Dper, theta, phi) 190 3 - (Diso, Da, theta, phi) 191 4 - (Diso, Dratio, theta, phi) 192 193 where: 194 tm = 1 / 6Diso 195 Diso = 1/3 (Dpar + 2Dper) 196 Da = 1/3 (Dpar - Dper) 197 Dratio = Dpar / Dper 198 199 The diffusion tensor is defined by the vector Dpar. The angle alpha describes the bond 200 vector with respect to the diffusion frame while the spherical angles {theta, phi} describe 201 the diffusion tensor with respect to the PDB frame. Theta is the polar angle and phi is the 202 azimuthal angle defined between: 203 0 <= theta <= pi 204 0 <= phi <= 2pi 205 The angle alpha is defined between: 206 0 <= alpha <= 2pi 207 208 The 'axial_type' argument should be 'oblate', 'prolate', or None. The argument will be 209 ignored if the diffusion tensor is not axially symmetric. If 'oblate' is given, then the 210 constraint Dper >= Dpar is used. If 'prolate' is given, then the constraint Dper <= Dpar is 211 used. If nothing is supplied, then Dper and Dpar will be allowed to have any values. To 212 prevent minimisation of diffusion tensor parameters in a space with two minima, it is 213 recommended to specify which tensor to be minimised, thereby partitioning the two minima 214 into the two subspaces (the partition is where Da equals 0). 215 216 217 Anisotropic diffusion. 218 219 To select fully anisotropic diffusion, the parameters argument should be a tuple of length 220 six. A tuple is a type of data structure enclosed in round brackets, the elements of which 221 are separated by commas. Alternative sets of parameters, 'param_types', are: 222 223 0 - (tm, Da, Dr, alpha, beta, gamma) (Default) 224 1 - (Diso, Da, Dr, alpha, beta, gamma) 225 2 - (Dx, Dy, Dz, alpha, beta, gamma) 226 227 where: 228 tm = 1 / 6Diso 229 Diso = 1/3 (Dx + Dy + Dz) 230 Da = 1/3 (Dz - (Dx + Dy)/2) 231 Dr = (Dx - Dy)/2 232 233 The angles alpha, beta, and gamma are the Euler angles describing the diffusion tensor 234 within the PDB frame. These angles are defined using the z-y-z axis rotation notation where 235 alpha is the initial rotation angle around the z-axis, beta is the rotation angle around the 236 y-axis, and gamma is the final rotation around the z-axis again. The angles are defined 237 between: 238 0 <= alpha <= 2pi 239 0 <= beta <= pi 240 0 <= gamma <= 2pi 241 Within the PDB frame, the bond vector is described using the spherical angels theta and phi 242 where theta is the polar angle and phi is the azimuthal angle defined between: 243 0 <= theta <= pi 244 0 <= phi <= 2pi 245 246 247 Units. 248 249 The 'time_scale' argument should be a floating point number. Parameters affected by this 250 value are: tm. 251 252 The 'd_scale' argument should also be a floating point number. Parameters affected by this 253 value are: Diso; Dpar; Dper; Da; Dr; Dx; Dy; Dz. 254 255 The 'angle_units' argument should either be the string 'deg' or 'rad'. Parameters affected 256 are: theta; phi; alpha; beta; gamma. 257 258 259 260 Examples 261 ~~~~~~~~ 262 263 To set an isotropic diffusion tensor with a correlation time of 10ns, assigning it to the 264 run 'm1', type: 265 266 relax> diffusion_tensor('m1', 10e-9) 267 relax> diffusion_tensor(run='m1', params=10e-9) 268 relax> diffusion_tensor('m1', 10.0, 1e-9) 269 relax> diffusion_tensor(run='m1', params=10.0, time_scale=1e-9, fixed=1) 270 271 272 To select axially symmetric diffusion with a tm value of 8.5ns, Dratio of 1.1, theta value 273 of 20 degrees, and phi value of 20 degrees, and assign it to the run 'm8', type: 274 275 relax> diffusion_tensor('m8', (8.5e-9, 1.1, 20.0, 20.0), param_types=1) 276 277 278 To select an axially symmetric diffusion tensor with a Dpar value of 1.698e7, Dper value of 279 1.417e7, theta value of 67.174 degrees, and phi value of -83.718 degrees, and assign it to 280 the run 'axial', type one of: 281 282 relax> diffusion_tensor('axial', (1.698e7, 1.417e7, 67.174, -83.718), param_types=1) 283 relax> diffusion_tensor(run='axial', params=(1.698e7, 1.417e7, 67.174, -83.718), 284 param_types=1) 285 relax> diffusion_tensor('axial', (1.698e-1, 1.417e-1, 67.174, -83.718), param_types=1, 286 d_scale=1e8) 287 relax> diffusion_tensor(run='axial', params=(1.698e-1, 1.417e-1, 67.174, -83.718), 288 param_types=1, d_scale=1e8) 289 relax> diffusion_tensor('axial', (1.698e-1, 1.417e-1, 1.1724, -1.4612), param_types=1, 290 d_scale=1e8, angle_units='rad') 291 relax> diffusion_tensor(run='axial', params=(1.698e-1, 1.417e-1, 1.1724, -1.4612), 292 param_types=1, d_scale=1e8, angle_units='rad', fixed=1) 293 294 295 To select fully anisotropic diffusion, type: 296 297 relax> diffusion_tensor('m5', (1.340e7, 1.516e7, 1.691e7, -82.027, -80.573, 65.568), 298 param_types=2) 299 300 301 To select and minimise an isotropic diffusion tensor, type (followed by a minimisation 302 command): 303 304 relax> diffusion_tensor('diff', 10e-9, fixed=0) 305 """ 306 307 # Function intro text. 308 if self.__relax__.interpreter.intro: 309 text = sys.ps3 + "diffusion_tensor.set(" 310 text = text + "run=" + `run` 311 text = text + ", params=" + `params` 312 text = text + ", time_scale=" + `time_scale` 313 text = text + ", d_scale=" + `d_scale` 314 text = text + ", angle_units=" + `angle_units` 315 text = text + ", param_types=" + `param_types` 316 text = text + ", axial_type=" + `axial_type` 317 text = text + ", fixed=" + `fixed` + ")" 318 print text 319 320 # The name of the run. 321 if type(run) != str: 322 raise RelaxStrError, ('run', run) 323 324 # Parameter argument. 325 if type(params) != int and type(params) != float and type(params) != tuple: 326 raise RelaxNumTupleError, ('diffusion parameters', params) 327 if type(params) == tuple: 328 if len(params) != 4 and len(params) != 6: 329 raise RelaxError, "The diffusion parameters argument must either be a number or a tuple of numbers of length 4 or 6." 330 for i in xrange(len(params)): 331 if type(params[i]) != float and type(params[i]) != int: 332 raise RelaxNumTupleError, ('diffusion parameters', params) 333 334 # Time scale argument. 335 if type(time_scale) != float: 336 raise RelaxFloatError, ('time scale', time_scale) 337 338 # D scale argument. 339 if type(d_scale) != float: 340 raise RelaxFloatError, ('D scale', d_scale) 341 342 # Angle scale units argument. 343 if type(angle_units) != str: 344 raise RelaxStrError, ('angle units', angle_units) 345 346 # Parameter types argument. 347 if type(param_types) != int: 348 raise RelaxIntError, ('parameter types', param_types) 349 350 # Axial type argument. 351 if axial_type != None and type(axial_type) != str: 352 raise RelaxNoneStrError, ('axial type', axial_type) 353 354 # The fixed flag. 355 if type(fixed) != int or (fixed != 0 and fixed != 1): 356 raise RelaxBinError, ('fixed flag', fixed) 357 358 # Execute the functional code. 359 self.__relax__.generic.diffusion_tensor.set(run=run, params=params, time_scale=time_scale, d_scale=d_scale, angle_units=angle_units, param_types=param_types, axial_type=axial_type, fixed=fixed)

Source Code for Module prompt.diffusion_tensor