progress bar in GWRResults spatial_variability

[pareyesv]

Considering spatial_variability is very computationally demanding, it'd be nice to add a progress bar (tqdm) to the for-loop here:

mgwr/mgwr/gwr.py

Lines 1217 to 1225 in 5e7fa3f

	for x in range(n_iters):
	temp_coords = np.random.permutation(self.model.coords)
	temp_sel.coords = temp_coords
	temp_bw = temp_sel.search(**search_params)
	temp_gwr.bw = temp_bw
	temp_gwr.coords = temp_coords
	temp_params = temp_gwr.fit(**fit_params).params
	temp_sd = np.std(temp_params, axis=0)
	SDs.append(temp_sd)

tqdm is already used here

mgwr/mgwr/search.py

Lines 202 to 209 in 5e7fa3f

	try:
	from tqdm.auto import tqdm #if they have it, let users have a progress bar
	except ImportError:
	def tqdm(x, desc=''): #otherwise, just passthrough the range
	return x
	for iters in tqdm(range(1, max_iter + 1), desc='Backfitting'):

so I guess the same code should work:

    try:
        from tqdm.auto import tqdm  #if they have it, let users have a progress bar
    except ImportError:

        def tqdm(x, desc=""):  #otherwise, just passthrough the range
            return x

    for x in tqdm(range(n_iters), desc="Testing"):  # Is "Testing" the right description? ¯\_(ツ)_/¯ 
        # ...

Let me know what you think. I can do the PR (If this is the case, I'd need ideas for the description text: desc="Testing" ?)

[TaylorOshan]

Good idea! PR would be very welcome. Only difference in those two examples is that I believe n_iters here is endogenously set based on the data, whereas it is (or rather can be) exogenously set by the user (default is 200 IIRC).

[pareyesv]

This is how it looks like (example from GWR_MGWR_example notebook)

[pareyesv]

@TaylorOshan thanks for your time and help! 👏 🎉
Should we close this issue?