problem: input parameters #4
Description
if i input number of out function equels 0, the code will get an error like :
UnboundLocalError Traceback (most recent call last)
Cell In[47], line 4
1 features.to_csv("features.csv", header=False)
2 from parallel_principal_feature_analysis import par_pfa # import the main pfa function
----> 4 par_pfa("features.csv",0,1)
File /opt/conda/lib/python3.10/site-packages/parallel_principal_feature_analysis/execute_PFA.py:38, in par_pfa(path, number_output_functions, number_sweeps, cluster_size, alpha, min_n_datapoints_a_bin, shuffle_feature_numbers, frac, calculate_mutual_information, basis_log_mutual_information)
36 for sweep in range(0,number_sweeps):
37 print("Sweep number: " + str(sweep+1))
---> 38 pf_ds,pf,indices_principal_feature_values=find_relevant_principal_features(data,number_output_functions,cluster_size,alpha,min_n_datapoints_a_bin,shuffle_feature_numbers,frac)
39 list_pf_ds.append(pf_ds)
40 # Output the principal features related to the output function in a list where the numbers correspod to the rows of the input csv-file
File /opt/conda/lib/python3.10/site-packages/parallel_principal_feature_analysis/find_relevant_principal_features.py:122, in find_relevant_principal_features(data, number_output_functions, cluster_size, alpha, min_n_datapoints_a_bin, shuffle_feature_numbers, frac)
120 intermediate_list_not_depending_on_system_state.append(j)
121 pv=1.1
--> 122 indices_principal_feature_values=np.concatenate((indices_principal_feature_values, np.array([j, pv]).reshape((1, 2))), axis=0)
124 #Output the result
125 intermediate_list_depending_on_system_state_empty = 1
UnboundLocalError: local variable 'pv' referenced before assignment