Source code for crikit.io.macros

"""
Created on Thu May 26 13:16:12 2016

@author: chc
"""

import crikit.io.lazy5 as lazy5

from crikit.io.meta_configs import (special_nist_bcars2 as _snb,
                                    special_nist_bcars1_sample_scan as _snb1ss)
from crikit.io.meta_process import meta_process as _meta_process
from crikit.io.hdf5 import (hdf_import_data as _hdf_import_data, hdf_import_data_macroraster as _hdf_import_data_macroraster)
from crikit.io.csv_nist import csv_nist_import_data as _csv_nist_import_data

__all__ = ['import_hdf_nist_special', 'import_csv_nist_special1']


def hdf_nist_special_macroraster(pth, filename, dset_list, output_cls_instance, 
                                 interp_kind_spatial='linear', interp_kind_spectral='linear'):
    print('\n')
    import_success = _hdf_import_data_macroraster(pth, filename, dset_list, output_cls_instance,
                                                  interp_kind_spatial='linear', interp_kind_spectral='linear')
    if import_success is False:
        raise ValueError('hdf_import_data_macroraster failed')
        return False
    _meta_process(_snb(), output_cls_instance)
    return True


[docs]def import_hdf_nist_special(pth, filename, dset, output_cls_instance): """ Import data from HDF File as specified by NIST-specific settings Returns ------- Success : bool Whether import was successful """ print('\n') import_success = _hdf_import_data(pth, filename, dset, output_cls_instance) if import_success is False: raise ValueError('hdf_import_data failed') return False _meta_process(_snb(), output_cls_instance) return True
def import_hdf_nist_special_ooc(pth, filename, dset, output_cls_instance): """ Import data from HDF File (OUT-OF-CORE) as specified by NIST-specific settings Returns ------- Success : bool Whether import was successful """ print('\n') try: fid = lazy5.utils.FidOrFile(lazy5.utils.fullpath(filename, pth=pth)).fid output_cls_instance._data = fid[dset] output_cls_instance.meta = lazy5.inspect.get_attrs_dset(fid, dset) _meta_process(_snb(), output_cls_instance) except Exception: raise ValueError('hdf_import_data failed') return False else: return fid
[docs]def import_csv_nist_special1(pth, filename_header, filename_data, output_cls_instance): """ Import data from CSV File as specified by NIST-specific settings Returns ------- Success : bool Whether import was successful """ try: import_success = _csv_nist_import_data(pth, filename_header, filename_data, output_cls_instance) if import_success is None or import_success is False: raise ValueError('csv_import_data returned None') _meta_process(_snb1ss(), output_cls_instance) except Exception: print('Something failed in import_csv_nist_special') return False else: return True
if __name__ == '__main__': # pragma: no cover from crikit.data.spectra import Hsi as _Hsi pth = '../' filename = 'mP2_w_small.h5' img = _Hsi() import_hdf_nist_special(pth, filename, '/BCARSImage/mP2_3_5ms_Pos_2_0/mP2_3_5ms_Pos_2_0_small', img) print('Shape of img: {}'.format(img.shape)) print('Shape of img.mean(): {}'.format(img.mean().shape)) print(img.y_rep.data) # from crikit.data.spectra import Spectrum as _Spectrum # sp = _Spectrum() # pth = '../../../Young_150617/' # filename_header = 'SH-03.h' # filename_data = 'base061715_152213_60ms.txt' # import_csv_nist_special1(pth, filename_header, filename_data, # output_cls_instance=sp)