CloneSet261


Clone Mass	Clones in CloneSet	Parameter Count	Clone Similarity	Syntax Category [Sequence Length]
2	3	1	0.968	compound_stmt

Clone Abstraction

Parameter Bindings

Clone Instance (Click to see clone)	Line Count	Source Line	Source File
1	2	428	Bio/MarkovModel.py
2	2	440	Bio/MarkovModel.py
3	2	521	Bio/MarkovModel.py

Clone Instance
1

Line Count
2

Source Line
428

Source File

Bio/MarkovModel.py

    for i in range(len(p_transition)): 
         p_transition[i, : ] = p_transition[i, : ]/sum(p_transition[i, : ]) 

     # p_emission is the probability of an output given a state.
     # C(s,o)|C(s) where o is an output and s is a state.

Clone Instance
2

Line Count
2

Source Line
440

Source File

Bio/MarkovModel.py

    for i in range(len(p_emission)): 
         p_emission[i, : ] = p_emission[i, : ]/sum(p_emission[i, : ])

Clone Instance
3

Line Count
2

Source Line
521

Source File

Bio/MarkovModel.py

        for i in range(len(matrix)): 
             matrix[i, : ] = matrix[i, : ]/sum(matrix[i, : ])

Clone Abstraction

Parameter Count: 1

Parameter Bindings

for i in range(len( [[#variable1982eda0]])):
   [[#variable1982eda0]][i, : ] = [[#variable1982eda0]][i, : ]/sum( [[#variable1982eda0]][i, : ]) 
  # p_emission is the probability of an output given a state.
  # C(s,o)|C(s) where o is an output and s is a state.

CloneAbstraction

Parameter Bindings
Parameter Index	Clone Instance	Parameter Name	Value
1	1	`[[#1982eda0]]`	p_transition
1	2	`[[#1982eda0]]`	p_emission
1	3	`[[#1982eda0]]`	matrix