concatenate_inference method broken

[mortonjt]

See https://github.com/biocore/BIRDMAn/blob/main/birdman/inference.py#L65

Getting this fixed would be super helpful, since it is much easier to use the xarray ops to compute summary statistics.

Sometimes inference objects don't have sample_stats attributes, which shouldn't cause a failure.

But even after commenting that out, there are weird indexing errors that can arise from merging inference data objects, that should probably be validated ahead of time.

Traceback (most recent call last):
  File "/home/centos/birdman/summarize.py", line 136, in <module>
    samples = concatenate_inferences(inf_list, 'y_predict', 'log_lhood', coords)
              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/centos/birdman/summarize.py", line 116, in concatenate_inferences
    {concatenation_name: coords[concatenation_name],
                         ~~~~~~^^^^^^^^^^^^^^^^^^^^
KeyError: 'feature'

[mortonjt]

Here is a slightly modified version of concatenate_inferences

def concatenate_inferences(
    inf_list: List[az.InferenceData],
    coords: dict,
    concatenation_name: str = "feature"
) -> az.InferenceData:
    """Concatenates multiple single feature fits into one object.                                                                                                                       
                                                                                                                                                                                        
    :param inf_list: List of InferenceData objects for each feature                                                                                                                     
    :type inf_list: List[az.InferenceData]                                                                                                                                              
                                                                                                                                                                                        
    :param coords: Coordinates containing concatenation name labels                                                                                                                     
    :type coords: dict                                                                                                                                                                  
                                                                                                                                                                                        
    :param concatenation_name: Name of feature dimension used when                                                                                                                      
        concatenating, defaults to "feature"                                                                                                                                            
    :type concatenation_name: str                                                                                                                                                       
                                                                                                                                                                                        
    :returns: Combined InferenceData object                                                                                                                                             
    :rtype: az.InferenceData                                                                                                                                                            
    """
    group_list = []
    group_list.append([x.posterior for x in inf_list])
    # group_list.append([x.sample_stats for x in inf_list])                                                                                                                            
    if "log_likelihood" in inf_list[0].groups():
        group_list.append([x.log_likelihood for x in inf_list])
    if "posterior_predictive" in inf_list[0].groups():
        group_list.append([x.posterior_predictive for x in inf_list])

    po_ds = xr.concat(group_list[0], concatenation_name)
    #ss_ds = xr.concat(group_list[1], concatenation_name)                                                                                                                              
    group_dict = {
        "posterior": po_ds,
        #"sample_stats": ss_ds                                                                                                                                                         
    }
    if "log_likelihood" in inf_list[0].groups():
        ll_ds = xr.concat(group_list[1], concatenation_name)
        group_dict["log_likelihood"] = ll_ds
    if "posterior_predictive" in inf_list[0].groups():
        pp_ds = xr.concat(group_list[2], concatenation_name)
        group_dict["posterior_predictive"] = pp_ds

    all_group_inferences = []
    for group in group_dict:
	# Set concatenation dim coords                                                                                                                                                 
	group_ds = group_dict[group].assign_coords(
            {concatenation_name: coords[concatenation_name]}
        )

        group_inf = az.InferenceData(**{group: group_ds})  # hacky                                                                                                                     
        all_group_inferences.append(group_inf)

    return az.concat(*all_group_inferences)

Pull request incoming shortly