View GitHub Repository pyActLearn

Schedule Inspection
Subscribe

Code Duplication    Length = 20-20 lines in 2 locations

pyActLearn/CASAS/fuel.py 2 locations

@@ 168-187 (lines=20) @@
165 
            top_n (:obj:`int`): Back annotate top n probabilities.
166 
        """
167 
        # Verify split id first
168 
        if split_id == -1:
169 
            if type(split_name) is tuple:
170 
                time_array = []
171 
                for each_split in split_name:
172 
                    each_split_id = self.info['split_sets'].index(each_split)
173 
                    if 0 < each_split_id < len(self.info['split_sets']):
174 
                        time_array += self.info['split_timearray'][each_split_id]
175 
            else:
176 
                if split_name in self.info['split_sets']:
177 
                    split_id = self.info['split_sets'].index(split_name)
178 
                    if 0 < split_id < len(self.info['split_sets']):
179 
                        time_array = self.info['split_timearray'][split_id]
180 
                else:
181 
                    logger.error('Failed to find split set with name %s.' % split_name)
182 
                    return
183 
        elif 0 < split_id < len(self.info['split_sets']):
184 
            time_array = self.info['split_timearray'][split_id]
185 
        else:
186 
            logger.error('Split set index %d out of bound.' % split_id)
187 
            return
188 
        # Check length of prediction and time array
189 
        if prediction_proba.shape[0] != len(time_array):
190 
            logger.error('Prediction size miss-match. There are %d time points with only %d labels given.' %
@@ 125-144 (lines=20) @@
122 
            split_name (:obj:`str`): The name of the split set to be annotated (required if split_id is not specified).
123 
        """
124 
        # Verify split id first
125 
        if split_id == -1:
126 
            if type(split_name) is tuple:
127 
                time_array = []
128 
                for each_split in split_name:
129 
                    each_split_id = self.info['split_sets'].index(each_split)
130 
                    if 0 < each_split_id < len(self.info['split_sets']):
131 
                        time_array += self.info['split_timearray'][each_split_id]
132 
            else:
133 
                if split_name in self.info['split_sets']:
134 
                    split_id = self.info['split_sets'].index(split_name)
135 
                    if 0 < split_id < len(self.info['split_sets']):
136 
                        time_array = self.info['split_timearray'][split_id]
137 
                else:
138 
                    logger.error('Failed to find split set with name %s.' % split_name)
139 
                    return
140 
        elif 0 < split_id < len(self.info['split_sets']):
141 
            time_array = self.info['split_timearray'][split_id]
142 
        else:
143 
            logger.error('Split set index %d out of bound.' % split_id)
144 
            return
145 
        # Check length of prediction and time array
146 
        if prediction.shape[0] != len(time_array):
147 
            logger.error('Prediction size miss-match. There are %d time points with only %d labels given.' %