def __init__(self, cellmap_df, paramlist, log = False):
self.cellmap_df = cellmap_df
self.log = log
self.cellutil = cellmaputil.cellmaputil()
self.prefix_list = []
self.paramlist = paramlist
for col in self.cellmap_df.columns.values:
if 'source_id' in col: self.prefix_list.append(col.replace('source_id', ''))
type=config.trainingtype, logcycle=config.logcycle)
training_func.starttraining()
log.info('Getting trained cell map')
traicellmap = training_func.givecellmap()
log.info('Saving cell map in csv form')
cellmapdumpfile = os.path.join(config.projectpath, 'trainedcellmap.csv')
log.debug('Saving to: %s' % cellmapdumpfile)
traicellmap.to_csv(cellmapdumpfile, index_label=False, index=False)
log.info('Finish Saving cell map in csv form')
if 'mapping' in config.processlist:
if not 'cellmap_df' in locals():
log.info('Loading cellmap data frame from project file: %s' % config.projectpath)
cellmaputil_func = cellmaputil.cellmaputil()
cellmap_df = cellmaputil_func.loadcellmap(os.path.join(config.projectpath, 'trainedcellmap.csv'))
log.info('Begin mapping source to cell map')
#primary
if 'dev' in config.processlist:
import random
_srtscalledsource_df = primerawsource_df.ix[ random.sample(primerawsource_df.index , 1000)]
mapping_func = mapping2.mapping(cellmap_df, _srtscalledsource_df, config.projectpath, config.paramlist ,
plot=True, log=log, type=config.trainingtype)
else:
mapping_func = mapping2.mapping(cellmap_df, primerawsource_df, config.projectpath, config.paramlist,
plot=True, log=log, type=config.trainingtype)
mappedcellmap_df = mapping_func.mapsource()
