Increase QA on diffusion branch

[ebridge2]

• add more thorough QA to diffusion pipeline. can use existing script qa_func.py utilities.
• Using class attributes, you can easily save relevant tmp filepaths and use them to create qa. This can be accomplished by doing something like:

class preproc(inputs):
    self.local_attr1 = ...
    self.local_attr2 = ...

def subfunc(self):
    # functions
    self.intermediate_from_subfunc = ...

def driver(self):
    ...
    self.local_intermediate = ...

def ndmg_dwi_pipeline():
    ...
    qa_util = # qa_func utility, generalized for dmri as well
    namer = # bids utility
    ndp = preproc(inputs)
    qa_util.preproc_qa(ndp, namer)

class qa_util():
    def preproc_qa(preproc_instance, namer):
        # access preproc_instance.intermediates here

The script is already about half ready for this type of drop-in; when I did this for the fMRI, I modified the dMRI enough such that the it was compliant with the naming utility; the rest of the integration process should be mostly restructuring dMRI class instances to store local intermediate paths, as well as adding dMRI specific QA to the qa_func module. Much of the qa_func module can be recycled for dMRI by suitably naming things such as registration and preprocessing intermediate attributes to the corresponding modules.