AttributeError: 'tuple' object has no attribute 'shape' about mgwr HOT 6 CLOSED

ran the example code at https://mgwr.readthedocs.io/en/latest/generated/mgwr.gwr.GWR.html#mgwr.gwr.GWR
tried #basic model calibration, which is
import libpysal as ps
from mgwr.gwr import GWR
data = ps.io.open(ps.examples.get_path('GData_utm.csv'))
coords = list(zip(data.by_col('X'), data.by_col('Y')))
y = np.array(data.by_col('PctBach')).reshape((-1,1))
rural = np.array(data.by_col('PctRural')).reshape((-1,1))
pov = np.array(data.by_col('PctPov')).reshape((-1,1))
african_amer = np.array(data.by_col('PctBlack')).reshape((-1,1))
X = np.hstack([rural, pov, african_amer])
model = GWR(coords, y, X, bw=90.000, fixed=False, kernel='bisquare')

also returned: AttributeError: 'tuple' object has no attribute 'shape'

Python3.8. Any comments or suggestions?

from mgwr.

Hello @kkyyhh96 and @shughestr,

I locate the problem. This happened because a recent update on spreg hasn't been reflected in the mgwr. There is a current open PR #83 from @weikang9009 should fix this problem, but it hasn't been merged yet.

A temporary fix would be to pin spreg to an earlier version e.g. v.1.1.1. pip install spreg==1.1.1.

Cheers,
Ziqi

from mgwr.

from mgwr.

Solved in #83

from mgwr.

from mgwr.

Hi Ziqi, We are still experiencing some issues with the GWR approach/library. We wonder if you'll have time to have a quick Zoom chat with us. We have applied SVM, Ridge Regression, XGBoost on the dataset. As we are new in this field, we can really use your help and guidance. Just FYI, I am working on a pro bono basis with some graduate students in Canadian universities on a Real Estate price trend forecast project. I currently work for a Canadian government agency. Let me know. Thanks. Regards, Dave Dong
…

Hi Dave. I could do that, could you send me an email at liziqi1992[at]gmail.com?

from mgwr.