Package specific_analyses :: Package model_free :: Module uf
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Source Code for Module specific_analyses.model_free.uf

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  2  #                                                                             # 
  3  # Copyright (C) 2003-2014 Edward d'Auvergne                                   # 
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 21   
 22  # Module docstring. 
 23  """The model-free analysis user functions.""" 
 24   
 25  # Python module imports. 
 26  from re import match 
 27   
 28  # relax module imports. 
 29  from lib.errors import RelaxError, RelaxFuncSetupError, RelaxNoSequenceError, RelaxTensorError 
 30  from pipe_control import pipes 
 31  from pipe_control.mol_res_spin import exists_mol_res_spin_data, spin_loop 
 32  import specific_analyses 
 33  from specific_analyses.model_free.api import Model_free 
 34  from specific_analyses.model_free.model import model_map 
 35  from user_functions.data import Uf_tables; uf_tables = Uf_tables() 
 36  from user_functions.objects import Desc_container 
 37   
 38  # The API object. 
 39  api_model_free = Model_free() 
 40   
 41   
 42  # Classic style documentation. 
 43  classic_style_doc = Desc_container("Model-free classic style") 
 44  classic_style_doc.add_paragraph("Creator:  Edward d'Auvergne") 
 45  classic_style_doc.add_paragraph("Argument string:  \"classic\"") 
 46  classic_style_doc.add_paragraph("Description:  The classic style draws the backbone of a protein in a cylindrical bond style.  Rather than colouring the amino acids to which the NH bond belongs, the three covalent bonds of the peptide bond from Ca to Ca in which the NH bond is located are coloured.  Deselected residues are shown as black lines.") 
 47  classic_style_doc.add_paragraph("Supported data types:") 
 48  table = uf_tables.add_table(label="table: model-free macro classic style", caption="The model-free classic style for mapping model spin specific data onto 3D molecular structures using either PyMOL or Molmol.", caption_short="The model-free classic style for PyMOL and Molmol data mapping.") 
 49  table.add_headings(["Data type", "String", "Description"]) 
 50  table.add_row(["S2.", "'s2'", "The standard model-free order parameter, equal to S2f.S2s for the two timescale models.  The default colour gradient starts at 'yellow' and ends at 'red'."]) 
 51  table.add_row(["S2f.", "'s2f'", "The order parameter of the faster of two internal motions.  Residues which are described by model-free models m1 to m4, the single timescale models, are illustrated as white neon bonds.  The default colour gradient is the same as that for the S2 data type."]) 
 52  table.add_row(["S2s.", "'s2s'", "The order parameter of the slower of two internal motions.  This functions exactly as S2f except that S2s is plotted instead."]) 
 53  table.add_row(["Amplitude of fast motions.", "'amp_fast'", "Model independent display of the amplite of fast motions.  For residues described by model-free models m5 to m8, the value plotted is that of S2f.  However, for residues described by models m1 to m4, what is shown is dependent on the timescale of the motions.  This is because these single timescale models can, at times, be perfect approximations to the more complex two timescale models.  Hence if te is less than 200 ps, S2 is plotted.  Otherwise the peptide bond is coloured white.  The default colour gradient  is the same as that for S2."]) 
 54  table.add_row(["Amplitude of slow motions.", "'amp_slow'", "Model independent display of the amplite of slow motions, arbitrarily defined as motions slower than 200 ps.  For residues described by model-free models m5 to m8, the order parameter S2 is plotted if ts > 200 ps.  For models m1 to m4, S2 is plotted if te > 200 ps.  The default colour gradient is the same as that for S2."]) 
 55  table.add_row(["te.", "'te'", "The correlation time, te.  The default colour gradient starts at 'turquoise' and ends at 'blue'."]) 
 56  table.add_row(["tf.", "'tf'", "The correlation time, tf.  The default colour gradient is the same as that of te."]) 
 57  table.add_row(["ts.", "'ts'", "The correlation time, ts.  The default colour gradient starts at 'blue' and ends at 'black'."]) 
 58  table.add_row(["Timescale of fast motions", "'time_fast'", "Model independent display of the timescale of fast motions.  For models m5 to m8, only the parameter tf is plotted.  For models m2 and m4, the parameter te is plotted only if it is less than 200 ps.  All other residues are assumed to have a correlation time of zero.  The default colour gradient is the same as that of te."]) 
 59  table.add_row(["Timescale of slow motions", "'time_slow'", "Model independent display of the timescale of slow motions.  For models m5 to m8, only the parameter ts is plotted.  For models m2 and m4, the parameter te is plotted only if it is greater than 200 ps.  All other residues are coloured white.  The default colour gradient is the same as that of ts."]) 
 60  table.add_row(["Chemical exchange", "'rex'", "The chemical exchange, Rex.  Residues which experience no chemical exchange are coloured white.  The default colour gradient starts at 'yellow' and finishes at 'red'."]) 
 61  classic_style_doc.add_table(table.label) 
 62   
 63  # Model elimination documentation. 
 64  eliminate_doc = [] 
 65  eliminate_doc.append(Desc_container("Local tm model elimination rule")) 
 66  eliminate_doc[-1].add_paragraph("The local tm, in some cases, may exceed the value expected for a global correlation time. Generally the tm value will be stuck at the upper limit defined for the parameter.  These models are eliminated using the rule:") 
 67  eliminate_doc[-1].add_verbatim("    tm >= c") 
 68  eliminate_doc[-1].add_paragraph("The default value of c is 50 ns, although this can be overridden by supplying the value (in seconds) as the first element of the args tuple.") 
 69  eliminate_doc.append(Desc_container("Internal correlation times {te, tf, ts} model elimination rules")) 
 70  eliminate_doc[-1].add_paragraph("These parameters may experience the same problem as the local tm in that the model fails and the parameter value is stuck at the upper limit.  These parameters are constrained using the formula (te, tf, ts <= 2tm).  These failed models are eliminated using the rule:") 
 71  eliminate_doc[-1].add_verbatim("    te, tf, ts >= c . tm.") 
 72  eliminate_doc[-1].add_paragraph("The default value of c is 1.5.  Because of round-off errors and the constraint algorithm, setting c to 2 will result in no models being eliminated as the minimised parameters will always be less than 2tm.  The value can be changed by supplying the value as the second element of the tuple.") 
 73  eliminate_doc.append(Desc_container("Arguments")) 
 74  eliminate_doc[-1].add_paragraph("The 'args' argument must be a tuple of length 2, the elements of which must be numbers.  For example, to eliminate models which have a local tm value greater than 25 ns and models with internal correlation times greater than 1.5 times tm, set 'args' to (25 * 1e-9, 1.5).") 
 75   
 76   
77 -def create_model(model=None, equation=None, params=None, spin_id=None):
78 """Function for creating a custom model-free model. 79 80 @param model: The name of the model. 81 @type model: str 82 @param equation: The equation type to use. The 3 allowed types are: 'mf_orig' for the original model-free equations with parameters {s2, te}; 'mf_ext' for the extended model-free equations with parameters {s2f, tf, s2, ts}; and 'mf_ext2' for the extended model-free equations with parameters {s2f, tf, s2s, ts}. 83 @type equation: str 84 @param params: A list of the parameters to include in the model. The allowed parameter names includes those for the equation type as well as chemical exchange 'rex', the bond length 'r', and the chemical shift anisotropy 'csa'. 85 @type params: list of str 86 @param spin_id: The spin identification string. 87 @type spin_id: str 88 """ 89 90 # Test if the current data pipe exists. 91 pipes.test() 92 93 # Test if the pipe type is 'mf'. 94 function_type = pipes.get_type() 95 if function_type != 'mf': 96 raise RelaxFuncSetupError(specific_analyses.get_string(function_type)) 97 98 # Test if sequence data is loaded. 99 if not exists_mol_res_spin_data(): 100 raise RelaxNoSequenceError 101 102 # Check the validity of the model-free equation type. 103 valid_types = ['mf_orig', 'mf_ext', 'mf_ext2'] 104 if not equation in valid_types: 105 raise RelaxError("The model-free equation type argument " + repr(equation) + " is invalid and should be one of " + repr(valid_types) + ".") 106 107 # Check the validity of the parameter array. 108 s2, te, s2f, tf, s2s, ts, rex, csa, r = 0, 0, 0, 0, 0, 0, 0, 0, 0 109 for i in range(len(params)): 110 # Invalid parameter flag. 111 invalid_param = 0 112 113 # S2. 114 if params[i] == 's2': 115 # Does the array contain more than one instance of S2. 116 if s2: 117 invalid_param = 1 118 s2 = 1 119 120 # Does the array contain S2s. 121 s2s_flag = 0 122 for j in range(len(params)): 123 if params[j] == 's2s': 124 s2s_flag = 1 125 if s2s_flag: 126 invalid_param = 1 127 128 # te. 129 elif params[i] == 'te': 130 # Does the array contain more than one instance of te and has the extended model-free formula been selected. 131 if equation == 'mf_ext' or te: 132 invalid_param = 1 133 te = 1 134 135 # Does the array contain the parameter S2. 136 s2_flag = 0 137 for j in range(len(params)): 138 if params[j] == 's2': 139 s2_flag = 1 140 if not s2_flag: 141 invalid_param = 1 142 143 # S2f. 144 elif params[i] == 's2f': 145 # Does the array contain more than one instance of S2f and has the original model-free formula been selected. 146 if equation == 'mf_orig' or s2f: 147 invalid_param = 1 148 s2f = 1 149 150 # S2s. 151 elif params[i] == 's2s': 152 # Does the array contain more than one instance of S2s and has the original model-free formula been selected. 153 if equation == 'mf_orig' or s2s: 154 invalid_param = 1 155 s2s = 1 156 157 # tf. 158 elif params[i] == 'tf': 159 # Does the array contain more than one instance of tf and has the original model-free formula been selected. 160 if equation == 'mf_orig' or tf: 161 invalid_param = 1 162 tf = 1 163 164 # Does the array contain the parameter S2f. 165 s2f_flag = 0 166 for j in range(len(params)): 167 if params[j] == 's2f': 168 s2f_flag = 1 169 if not s2f_flag: 170 invalid_param = 1 171 172 # ts. 173 elif params[i] == 'ts': 174 # Does the array contain more than one instance of ts and has the original model-free formula been selected. 175 if equation == 'mf_orig' or ts: 176 invalid_param = 1 177 ts = 1 178 179 # Does the array contain the parameter S2 or S2s. 180 flag = 0 181 for j in range(len(params)): 182 if params[j] == 's2' or params[j] == 's2f': 183 flag = 1 184 if not flag: 185 invalid_param = 1 186 187 # Rex. 188 elif params[i] == 'rex': 189 if rex: 190 invalid_param = 1 191 rex = 1 192 193 # Interatomic distances. 194 elif params[i] == 'r': 195 if r: 196 invalid_param = 1 197 r = 1 198 199 # CSA. 200 elif params[i] == 'csa': 201 if csa: 202 invalid_param = 1 203 csa = 1 204 205 # Unknown parameter. 206 else: 207 raise RelaxError("The parameter " + params[i] + " is not supported.") 208 209 # The invalid parameter flag is set. 210 if invalid_param: 211 raise RelaxError("The parameter array " + repr(params) + " contains an invalid combination of parameters.") 212 213 # Set up the model. 214 model_setup(model, equation, params, spin_id)
215 216
217 -def delete():
218 """Delete all the model-free data.""" 219 220 # Test if the current pipe exists. 221 pipes.test() 222 223 # Test if the pipe type is set to 'mf'. 224 function_type = pipes.get_type() 225 if function_type != 'mf': 226 raise RelaxFuncSetupError(specific_analyses.setup.get_string(function_type)) 227 228 # Test if the sequence data is loaded. 229 if not exists_mol_res_spin_data(): 230 raise RelaxNoSequenceError 231 232 # Get all data structure names. 233 names = api_model_free.data_names(scope='spin') 234 235 # Loop over the spins. 236 for spin in spin_loop(): 237 # Loop through the data structure names. 238 for name in names: 239 # Skip the data structure if it does not exist. 240 if not hasattr(spin, name): 241 continue 242 243 # Delete the data. 244 delattr(spin, name)
245 246
247 -def model_setup(model=None, equation=None, params=None, spin_id=None):
248 """Function for updating various data structures depending on the model selected. 249 250 @param model: The name of the model. 251 @type model: str 252 @param equation: The equation type to use. The 3 allowed types are: 'mf_orig' for the original model-free equations with parameters {s2, te}; 'mf_ext' for the extended model-free equations with parameters {s2f, tf, s2, ts}; and 'mf_ext2' for the extended model-free equations with parameters {s2f, tf, s2s, ts}. 253 @type equation: str 254 @param params: A list of the parameters to include in the model. The allowed parameter names includes those for the equation type as well as chemical exchange 'rex', the bond length 'r', and the chemical shift anisotropy 'csa'. 255 @type params: list of str 256 @param spin_id: The spin identification string. 257 @type spin_id: str 258 """ 259 260 # Test that no diffusion tensor exists if local tm is a parameter in the model. 261 if params: 262 for param in params: 263 if param == 'local_tm' and hasattr(pipes.get_pipe(), 'diff_tensor'): 264 raise RelaxTensorError('diffusion') 265 266 # Loop over the sequence. 267 for spin in spin_loop(spin_id): 268 # Initialise the data structures (if needed). 269 api_model_free.data_init(spin) 270 271 # Model-free model, equation, and parameter types. 272 spin.model = model 273 spin.equation = equation 274 spin.params = params
275 276
277 -def remove_tm(spin_id=None):
278 """Remove local tm from the set of model-free parameters for the given spins. 279 280 @param spin_id: The spin identification string. 281 @type spin_id: str or None 282 """ 283 284 # Test if the current data pipe exists. 285 pipes.test() 286 287 # Test if the pipe type is 'mf'. 288 function_type = pipes.get_type() 289 if function_type != 'mf': 290 raise RelaxFuncSetupError(specific_analyses.get_string(function_type)) 291 292 # Test if sequence data is loaded. 293 if not exists_mol_res_spin_data(): 294 raise RelaxNoSequenceError 295 296 # Loop over the spins. 297 for spin in spin_loop(spin_id): 298 # Skip deselected spins. 299 if not spin.select: 300 continue 301 302 # Test if a local tm parameter exists. 303 if not hasattr(spin, 'params') or not 'local_tm' in spin.params: 304 continue 305 306 # Remove tm. 307 spin.params.remove('local_tm') 308 309 # Model name. 310 if match('^tm', spin.model): 311 spin.model = spin.model[1:] 312 313 # Delete the local tm variable. 314 del spin.local_tm 315 316 # Set all the minimisation stats to None. 317 spin.chi2 = None 318 spin.iter = None 319 spin.f_count = None 320 spin.g_count = None 321 spin.h_count = None 322 spin.warning = None 323 324 # Set the global minimisation stats to None. 325 cdp.chi2 = None 326 cdp.iter = None 327 cdp.f_count = None 328 cdp.g_count = None 329 cdp.h_count = None 330 cdp.warning = None
331 332
333 -def select_model(model=None, spin_id=None):
334 """Function for the selection of a preset model-free model. 335 336 @param model: The name of the model. 337 @type model: str 338 @param spin_id: The spin identification string. 339 @type spin_id: str 340 """ 341 342 # Test if the current data pipe exists. 343 pipes.test() 344 345 # Test if the pipe type is 'mf'. 346 function_type = pipes.get_type() 347 if function_type != 'mf': 348 raise RelaxFuncSetupError(specific_analyses.get_string(function_type)) 349 350 # Test if sequence data is loaded. 351 if not exists_mol_res_spin_data(): 352 raise RelaxNoSequenceError 353 354 # Obtain the model info. 355 equation, params = model_map(model) 356 357 # Set up the model. 358 model_setup(model, equation, params, spin_id)
359