This version introduces major changes to the way reporters' mask is handled.

(Major)

Instead of creating a custom reporter's mask, users are now encouraged to choose from three preset reporting scenarios that are hardcoded into the code:
- reporting_scenario = 1 (single-sampling, excluding self-loops)
- reporting_scenario = 2 (double-sampling, excluding self-loops)
- reporting_scenario = 3 (nodes can report any ties in the network, excluding self-loops)
Updated the internal logic of the Python function read_from_edgelist() (Python) to properly enforce the new parameter reporting_scenario or a custom reporter mask, if informed. This function is also involked by the R package when the user passes an data.frame as input. The logic behind reporters' mask is now handled in the following priority order:
1. For backward compatibility, the function first checks if the parameter reporters (a list) was passed to the function (i.e. read_from_edgelist(edgelist, reporters=reporting_nodes)). If it was, the reporters' mask is set to double-sampling (i.e. reporting_scenario = 2), but applied only to the subset of nodes passed as reporters.
2. If no reporters parameter is passed, the function checks if the parameter R was passed to the function (i.e., read_from_edgelist(edgelist, R=custom_mask)). If it was, then this custom mask is checked for validity and used as the reporters' mask.
3. If neither reporters nor R parameters are passed, the reporting_scenario parameter is used to determine the reporting scenario.

(R)

Adds reporting_scenario (int) parameter to vimure() function.
Adds reporting_scenario (int) parameter to generate_X() function, used when creating synthetic X data.
Removes flag_self_reporter parameter from generate_X() function, as this functionality is now handled by the reporting_scenario parameter.
Remove a warning message that was printed when no custom reporter mask was passed to vimure() function . By default, the model will use the double-sampling scenario and does not expect a custom reporter mask.
[TESTS] Adds two new unit tests to address GitHub Issue '#92 [BUG] Custom reporter_mask being ignored by the R package': 1) Check that custom reporters' mask are enforced 2) Check that custom reporters' mask are enforced when input is edgelist.

(Python)

Adds reporting_scenario (int) parameter to VIMureModel() constructor.
Adds reporting_scenario (int) parameter to _build_X() method, used when creating synthetic X data.
Removes flag_self_reporter parameter from _build_X() method, as this functionality is now handled by the reporting_scenario parameter.
Remove a warning message that was printed when no custom reporter mask was passed to VIMureModel#fit() method. By default, the model will use the double-sampling scenario and does not expect a custom reporter mask.
[TESTS] Adds new unit tests within the class TestSyntheticWithReportingScenarios to ensure the new reporting scenarios work as expected.
[TESTS] Add a new test test_data_as_edgelist_reporting_scenario_2, using Karnataka data, to check if the reporting_scenario parameter is working as expected when the real data is passed as an edgelist.

(Internal)

There were multiple functions, in the Python code, that created a reporters' mask. These functions were refactored to a single function called build_self_reporters_mask(reporting_scenario, L, N, M) hosted in the utils.py file. This function is now used by the read_from_edgelist() function to create the reporters' mask, by the generate_X() function to create the synthetic X data and by the VIMureModel#fit() method to create the reporters' mask for the model.

What does that mean for users?

If your data is double-sampled, you shouldn't need to change anything. Just run the vimure() function (R) or vimure_object.fit() method as usual, just like what is described in Step 3 of Tutorial 2. By default, reporting_scenario=2, which means all users in the network can only report on ties they are involved in as either ego or alter (self-loops excluded).
Pass reporting_scenario=1 to the function if the nodes in your network should only be allowed to report the ties they are involved in as ego, or reporting_scenario=3 if the nodes could report on any ties, even those they are not involved in.

# Example of R code
vimure(edgelist, reporting_scenario=1)

If not all the egos and alters in your network are reporters, you can model this by passing an explicit list of reporters:

vimure(edgelist, reporters=list_of_reporter_ids)

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