def get_distribution_function(self):
if 'feature_name' in self.ctx.params:
fname = self.ctx.params['feature_name']
feature = self.ftable.get_feature(fname)
fq = FeatureQuery(feature)
return self.success(data=fq.get_frequency_distribution())
else:
return self.error('No feature name defined')
def _query(self,query):
#check if cached
cached_result = cache.get(self._get_cache_key())
if cached_result is not None:
return cached_result
feature_y, feature_x, options = nlq_parse(query,self.ftable.get_feature_names())
result_type = None
data = None
filter_function = None
if 'filter' in self.ctx.params:
filter_code = self.ctx.params['filter']
filter_function = compile_func_code(filter_code)
if feature_y is not None and feature_x is None: #single feature analysis
feature = self.ftable.get_feature(feature_y)
fq = FeatureQuery(feature)
fq.filter_function = filter_function
data = fq.get_frequency_distribution()
if feature.has_class():
result_type = 'pie'
elif feature.get_type() == TEXT_TYPE:
result_type = 'wordcloud'
else:
result_type = 'bar'
elif feature_y is not None and feature_x is not None: #two features analysis
fx = self.ftable.get_feature(feature_x)
fy = self.ftable.get_feature(feature_y)
analysis = AnalysisQuery(fx,fy)
analysis.filter_function = filter_function
result_type,data = analysis.correlate()
else: #search in datahub or show all
result_type = 'table'
if 'num_page' in options:
num_page = int(options['num_page'])
else:
num_page = 0
data = self.ftable.get_datatable(from_page=num_page,filter_function=filter_function)
cache.set(self._get_cache_key(),(result_type,data),60*60*24*10)
return (result_type,data)
