<SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
 The goal of this tutorial is to define an inverse problem according to the recordings and the electrode geometry we have. Then we can try out source localization methods. 
Let's start by loading the data
Step1:  And chose the localization parameters. You can check the parameters necessary in the documentation.
Step2:  You can see the different functions of of the inverse problem object with iPython easily
<ASSISTANT_TASK:>
Python Code:
# Data path/filename
t_ind = 38
data_path = '../data/'
file_name = data_path + 'data_sim_low.hdf5'
data_options = {'flag_cell': True, 'flag_electode': False}
data = data_in(file_name, **data_options)
Explanation: The goal of this tutorial is to define an inverse problem according to the recordings and the electrode geometry we have. Then we can try out source localization methods. 
Let's start by loading the data:
End of explanation
localization_options = {'p_vres':20, 'p_jlen':0, 'p_erad': 5, 't_ind': 38, 'flag_depthweighted': False}
loc = data_out(data, **localization_options)
Explanation: And chose the localization parameters. You can check the parameters necessary in the documentation.
End of explanation
loc.cmp_sloreta()
Explanation: You can see the different functions of of the inverse problem object with iPython easily:
loc.
loc.cmp_fwd_matrix         loc.electrode_pos
loc.cmp_inv_matrix         loc.evaluate_localization
loc.cmp_resolution_matrix  loc.load_with_pickle
loc.cmp_sloreta            loc.options
loc.cmp_weight_matrix      loc.t_ind
loc.create_voxels          loc.voxels
loc.data                   loc.write_with_pickle
And chose a function.
End of explanation
<END_TASK>