Hm.
That is too much work.
Can I write the default values into the
specific_analysis/relax_disp/parameter_object.py.
So I can simply call:
from specific_analyses.relax_disp.parameter_object import Relax_disp_params
PARAMS = Relax_disp_params()
PARAMS.default_value('pA')
PARAMS.grid_upper('pA')
Then I wont touch the API.
Best
Troels
2014-05-28 15:30 GMT+02:00 Edward d'Auvergne <[email protected]>:
> Hi,
>
> If you have the time and would like to implement this, such a change
> must be done for the entire specific API. It cannot be just for the
> relaxation dispersion analysis. The API change must be complete -
> otherwise the changes will not be accepted as that will result in huge
> amounts of maintenance work for me in the future, much more than the
> effort of making the API consistent for all analyses. Though if you
> set up one analysis type, the rest should be easy (half don't perform
> minimisation, so the grid limits are not defined). The best way to
> implement this would be:
>
> - Create a new svn branch from the trunk for the developments.
> - Add the self._grid_lower and self._grid_upper objects and
> corresponding arguments to specific_analyses.parameter_objects.
> - Go into specific_analyses, and run 'grep lower.append */*' to see
> all the places this needs changing.
> - Shift all of these hard coded values into the specific
> parameter_object modules.
> - Import the parameter_object singleton into the modules requiring the
> default bounds.
> - Replace all the hard coded values with the
> parameter_object.grid_lower() and parameter_object.grid_upper()
> function calls. Note the places where the limits are dynamically
> changed - these must remain.
> - Make sure the test suite passes.
> - Ask for the branch to be merged back.
>
> The API function grid_lower() should not be added, as these methods
> are really designed for use outside of the specific API. If you wish
> to do this, feel free.
>
> Regards,
>
> Edward
>
>
>
>
> On 28 May 2014 15:00, Troels Emtekær Linnet <[email protected]> wrote:
>> Hi Ed.
>>
>> I would like to collect the grid seach lower and upper bounds into the table
>> of
>> specific_analysis/relax_disp/parameter_object.py
>>
>> This is to make one place, where such details are collected.
>>
>> And the lower and upper bounds can be extracted for unit tests, and
>> for example dx.map more easily.
>>
>> I have worked it out for lower bounds of pA, and tested it.
>>
>> --- a/specific_analyses/api_base.py
>> +++ b/specific_analyses/api_base.py
>> @@ -314,6 +314,22 @@ class API_base(object):
>> raise RelaxImplementError('grid_search')
>>
>>
>> + def grid_lower(self, param):
>> + """Return the default lower bounds of paramater for the grid search.
>> +
>> + This basic method will first search for a global parameter
>> and, if not found, then a spin parameter.
>> +
>> +
>> + @param param: The specific analysis parameter.
>> + @type param: str
>> + @return: The default value.
>> + @rtype: float
>> + """
>> +
>> + # Return the value.
>> + return self._PARAMS.grid_lower(param)
>> +
>> +
>> def has_errors(self):
>> """Test if errors exist for the current data pipe.
>>
>> diff --git a/specific_analyses/parameter_object.py
>> b/specific_analyses/parameter_object.py
>> index b626a83..8e7abab 100644
>> --- a/specific_analyses/parameter_object.py
>> +++ b/specific_analyses/parameter_object.py
>> @@ -54,6 +54,7 @@ class Param_list(object):
>> self._scope = {}
>> self._string = {}
>> self._defaults = {}
>> + self._grid_lowers = {}
>> self._units = {}
>> self._desc = {}
>> self._py_types = {}
>> @@ -92,7 +93,7 @@ class Param_list(object):
>> return cls._instance
>>
>>
>> - def _add(self, name, scope=None, string=None, default=None,
>> units=None, desc=None, py_type=None, set='all', conv_factor=None,
>> grace_string=None, err=False, sim=False):
>> + def _add(self, name, scope=None, string=None, default=None,
>> grid_lower=None, units=None, desc=None, py_type=None, set='all',
>> conv_factor=None, grace_string=None, err=False, sim=False):
>> """Add a parameter to the list.
>>
>> @param name: The name of the parameter. This will
>> be used as the variable name.
>> @@ -103,6 +104,8 @@ class Param_list(object):
>> @type string: None or str
>> @keyword default: The default value of the parameter.
>> @type default: anything
>> + @keyword grid_lower: The default lower bounds of the grid search.
>> + @type grid_lower: float
>> @keyword units: A string representing the parameters units.
>> @type units: None or str
>> @keyword desc: The text description of the parameter.
>> @@ -134,6 +137,7 @@ class Param_list(object):
>> self._names.append(name)
>> self._scope[name] = scope
>> self._defaults[name] = default
>> + self._grid_lowers[name] = grid_lower
>> self._units[name] = units
>> self._desc[name] = desc
>> self._py_types[name] = py_type
>> @@ -540,6 +544,22 @@ class Param_list(object):
>> return self._grace_string[name]
>>
>>
>> + def grid_lower(self, name):
>> + """Return the default lower bounds of paramater for the grid search.
>> +
>> + @param name: The name of the parameter.
>> + @type name: str
>> + @return: The default value.
>> + @rtype: None or str
>> + """
>> +
>> + # Parameter check.
>> + self.check_param(name)
>> +
>> + # Return the default value.
>> + return self._grid_lowers[name]
>> +
>> +
>> def is_spin_param(self, name):
>> """Determine whether the given parameter is spin specific.
>>
>> diff --git a/specific_analyses/relax_disp/optimisation.py
>> b/specific_analyses/relax_disp/optimisation.py
>> index a92922e..82bd364 100644
>> --- a/specific_analyses/relax_disp/optimisation.py
>> +++ b/specific_analyses/relax_disp/optimisation.py
>> @@ -38,6 +38,7 @@ from lib.errors import RelaxError
>> from lib.text.sectioning import subsection
>> from multi import Memo, Result_command, Slave_command
>> from pipe_control.mol_res_spin import spin_loop
>> +from specific_analyses.api import return_api
>> from specific_analyses.relax_disp.checks import check_disp_points,
>> check_exp_type, check_exp_type_fixed_time
>> from specific_analyses.relax_disp.data import average_intensity,
>> count_spins, find_intensity_keys, has_exponential_exp_type,
>> has_proton_mmq_cpmg, loop_exp, loop_exp_frq_offset_point,
>> loop_exp_frq_offset_point_time, loop_frq, loop_offset, loop_time,
>> pack_back_calc_r2eff, return_cpmg_frqs, return_offset_data,
>> return_param_key_from_data, return_r1_data, return_r2eff_arrays,
>> return_spin_lock_nu1
>> from specific_analyses.relax_disp.parameters import
>> assemble_param_vector, assemble_scaling_matrix,
>> disassemble_param_vector, linear_constraints, loop_parameters,
>> param_conversion, param_num
>> @@ -296,6 +297,9 @@ def grid_search_setup(spins=None, spin_ids=None,
>> param_vector=None, lower=None,
>> elif isinstance(inc, int):
>> inc = [inc]*n
>>
>> + # The specific analysis API object.
>> + api = return_api()
>> +
>> # Set up the default bounds.
>> if not lower:
>> # Init.
>> @@ -357,7 +361,9 @@ def grid_search_setup(spins=None, spin_ids=None,
>> param_vector=None, lower=None,
>> if spins[si].model == MODEL_M61B:
>> lower.append(0.85)
>> else:
>> - lower.append(0.5)
>> + #lower.append(0.5)
>> + lower.append(api.grid_lower('pA'))
>> + #lower.append(api.default_value('pA'))
>> upper.append(1.0)
>>
>> # The population of state B (for 3-site exchange).
>> diff --git a/specific_analyses/relax_disp/parameter_object.py
>> b/specific_analyses/relax_disp/parameter_object.py
>> index 936d2b1..21dfe99 100644
>> --- a/specific_analyses/relax_disp/parameter_object.py
>> +++ b/specific_analyses/relax_disp/parameter_object.py
>> @@ -61,7 +61,7 @@ class Relax_disp_params(Param_list):
>> self._add('r2', scope='spin', default=10.0, desc='The
>> transversal relaxation rate', set='params', py_type=dict,
>> grace_string='\\qR\\s2\\N\\Q (rad.s\\S-1\\N)', err=True, sim=True)
>> self._add('r2a', scope='spin', default=10.0, desc='The
>> transversal relaxation rate for state A in the absence of exchange',
>> set='params', py_type=dict, grace_string='\\qR\\s2,A\\N\\Q
>> (rad.s\\S-1\\N)', err=True, sim=True)
>> self._add('r2b', scope='spin', default=10.0, desc='The
>> transversal relaxation rate for state B in the absence of exchange',
>> set='params', py_type=dict, grace_string='\\qR\\s2,B\\N\\Q
>> (rad.s\\S-1\\N)', err=True, sim=True)
>> - self._add('pA', scope='spin', default=0.90, desc='The
>> population for state A', set='params', py_type=float,
>> grace_string='\\qp\\sA\\N\\Q', err=True, sim=True)
>> + self._add('pA', scope='spin', default=0.90, grid_lower=0.6,
>> desc='The population for state A', set='params', py_type=float,
>> grace_string='\\qp\\sA\\N\\Q', err=True, sim=True)
>> self._add('pB', scope='spin', default=0.5, desc='The
>> population for state B', set='params', py_type=float,
>> grace_string='\\qp\\sB\\N\\Q', err=True, sim=True)
>> self._add('pC', scope='spin', default=0.5, desc='The
>> population for state C', set='params', py_type=float,
>> grace_string='\\qp\\sC\\N\\Q', err=True, sim=True)
>> self._add('phi_ex', scope='spin', default=5.0, desc='The
>> phi_ex = pA.pB.dw**2 value (ppm^2)', set='params', py_type=float,
>> grace_string='\\xF\\B\\sex\\N = \\q
>> p\\sA\\N.p\\sB\\N.\\xDw\\B\\S2\\N\\Q (ppm\\S2\\N)', err=True,
>> sim=True)
>>
>> Best
>> Troels
>>
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