data_convertor – Convert Tripoli-4 results to Dataset

This module converts Tripoli-4 data from parsing in Dataset.

valjean.eponine.tripoli4.data_convertor.bins_reduction(def_bins, reduced_dims)[source]

Reduce number of bins for integrated results (on one or more dimension).

For the reduced dimensions, all the bounds are suppressed except the first and the last one. This is also the case if they represent center of bins. The dimension is supposed to be squeezed afterwards.

Parameters:
Returns:

collections.OrderedDict (str, numpy.ndarray), i.e. adapted bins

>>> ibins = OrderedDict([('a', np.array([0, 1, 2, 3, 4])),
...                      ('b', np.array([-10, 0, 10]))])
>>> dshape_1 = (5, 3)
>>> b11 = bins_reduction(ibins, [True, True])
>>> b11['a']
array([0, 4])
>>> b11['b']
array([-10,  10])
>>> b51 = bins_reduction(ibins, [False, True])
>>> b51['a']
array([0, 1, 2, 3, 4])
>>> b51['b']
array([-10,  10])
valjean.eponine.tripoli4.data_convertor.special_array(array, score, bins, array_key='array', name='', what='')[source]

Convert special arrays in Dataset.

These special cases are typically vov results or uncertainty spectrum associated to a perturbation result. No error is associated to the score in that case. Bins are given by the spectrum.

Parameters:

  • array (dict) – result

  • score (str) – key of the score to get

  • bins (collections.OrderedDict) – bins correspondig to required array

  • array_key (str) – default=``’array’`` but it can be an integrated array for example, should be a key inside farray_res

  • name (str) – name of dataset

  • what (str) – what attribute of dataset

Return type:

Dataset

valjean.eponine.tripoli4.data_convertor.array_result(farray_res, res_type, name='', what='', array_key='array', score='score')[source]

Conversion of arrays in Dataset.

Parameters:

  • farray_res (dict) – results dictionary containing res_type key

  • res_type (str) – result type, like 'spectrum', 'mesh'

  • array_key (str) – default=``’array’`` but it can be an integrated array for example, should be a key inside farray_res

  • name (str) – name of dataset

  • what (str) – what attribute of dataset

Returns:

Dataset

valjean.eponine.tripoli4.data_convertor.masked_array_result(farray_res, res_type, name='', what='', array_key='array', score='score')[source]

Mask invalid (np.nan and np.inf) values.

valjean.eponine.tripoli4.data_convertor.integrated_result(result, res_type='integrated', name='', what='', score='score', sigma='sigma')[source]

Conversion of generic score (or energy integrated result) in Dataset.

Bins are squeezed according to the integrated dimension obtained from another array stored in the same result. Default full arrays are ‘spectrum’ and ‘mesh’. A case is also foreseen for uncertainty results (in perturbation cases).

Parameters:

  • result (dict) – results dictionary containing res_type key

  • res_type (str) – should be ‘integrated’

  • name (str) – name of dataset

  • what (str) – what attribute of dataset

  • score (str) – score key in results array like ‘score’ or ‘score/lethargy’

  • sigma (str) – sigma key in results array, usually ‘sigma’

Returns:

Dataset

valjean.eponine.tripoli4.data_convertor.results_wo_error(result, res_type, name='', what='', score=None)[source]

Conversion of results without error, allowing multiple scores in the same container.

Dict result:

results dictionary containing res_type key

Parameters:

  • res_type (str) – key in result allowing access to the desired quantity

  • name (str) – name of dataset

  • what (str) – what attribute of dataset

  • score (str) – score key in results array like ‘score’

Returns:

Dataset

valjean.eponine.tripoli4.data_convertor.result_wo_error(result, res_type, name='', what='')[source]

Conversion of a result without error.

The result can be of any dimension (matrix, vector, scalar) or any type (float, int, complex).

Dict result:

results dictionary containing res_type key

Parameters:

  • res_type (str) – key in result allowing access to the desired quantity

  • name (str) – name of dataset

  • what (str) – what attribute of dataset

Returns:

Dataset

valjean.eponine.tripoli4.data_convertor.result_with_error(result, res_type, name='', what='', score='score', sigma='sigma')[source]

Conversion of generic score (or energy integrated result) in Dataset.

Parameters:

  • result (dict) – results dictionary containing res_type key

  • res_type (str) – should be ‘generic’

  • name (str) – name of dataset

  • what (str) – what attribute of dataset

  • score (str) – score key in results array like ‘score’ or ‘score/lethargy’

  • sigma (str) – sigma key in results array, usually ‘sigma’

Returns:

Dataset

valjean.eponine.tripoli4.data_convertor.unbinned_result(result, res_type, name='', what='', score=None, sigma=None)[source]

Conversion of all unbinned results in Dataset.

Dict result:

results dictionary containing res_type key

Parameters:

  • res_type (str) – key in result allowing access to the desired quantity

  • name (str) – name of dataset

  • what (str) – what attribute of dataset

  • score (str) – score key in results array like ‘score’ or ‘score/lethargy’

  • sigma (str) – sigma key in results array, usually ‘sigma’

Returns:

Dataset

valjean.eponine.tripoli4.data_convertor.nan_result(name='', what='')[source]

Returns a NaN Dataset (value and error).

This Dataset can be returned for example in case of non converged results or when no dataset can be built.

Values are scalar per default, not arrays.

Parameters:

  • name (str) – name of dataset

  • what (str) – what attribute of dataset

Return type:

Dataset

Returns:

dataset containing NaN as value and error

valjean.eponine.tripoli4.data_convertor.convert_data(data, data_type, name='', what='', **kwargs)[source]

Test for data conversion using dict or default.

An exception for integrated is for the moment needed as they can come from spectrum res or generic scores but are treated a bit differently. To be homogenized.

Parameters:

  • data (dict) – results dictionary containing data_type key

  • data_type (str) – data key

  • kwargs – keyword arguements if needed

Returns:

Dataset