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use libpysal in docstrings and adapt to python 3 syntax #29

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Merged
TaylorOshan merged 2 commits into from
Sep 7, 2018
Merged

use libpysal in docstrings and adapt to python 3 syntax #29

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f3f483d
fix docstrings
weikang9009 Aug 27, 2018
26f01ff
Merge branch 'master' of https://github.com/pysal/mgwr into libpysal
weikang9009 Sep 7, 2018
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22 changes: 11 additions & 11 deletions mgwr/sel_bw.py
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Original file line number Diff line number Diff line change
Expand Up @@ -138,10 +138,10 @@ class Sel_BW(object):
Examples
________

>>> import pysal
>>> from pysal.contrib.gwr.sel_bw import Sel_BW
>>> data = pysal.open(pysal.examples.get_path('GData_utm.csv'))
>>> coords = zip(data.bycol('X'), data.by_col('Y'))
>>> import libpysal as ps
>>> from mgwr.sel_bw import Sel_BW
>>> 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))
Expand All @@ -150,28 +150,28 @@ class Sel_BW(object):

#Golden section search AICc - adaptive bisquare
>>> bw = Sel_BW(coords, y, X).search(criterion='AICc')
>>> print bw
>>> print(bw)
93.0

#Golden section search AIC - adaptive Gaussian
>>> bw = Sel_BW(coords, y, X, kernel='gaussian').search(criterion='AIC')
>>> print bw
>>> print(bw)
50.0

#Golden section search BIC - adaptive Gaussian
>>> bw = Sel_BW(coords, y, X, kernel='gaussian').search(criterion='BIC')
>>> print bw
>>> print(bw)
62.0

#Golden section search CV - adaptive Gaussian
>>> bw = Sel_BW(coords, y, X, kernel='gaussian').search(criterion='CV')
>>> print bw
>>> print(bw)
68.0

#Interval AICc - fixed bisquare
>>> sel = Sel_BW(coords, y, X, fixed=True).
>>> bw = sel.search(search_method='interval', bw_min=211001.0, bw_max=211035.0, interval=2)
>>> print bw
>>> sel = Sel_BW(coords, y, X, fixed=True)
>>> bw = sel.search(search_method='interval', bw_min=211001.0, bw_max=211035.0, interval=2)
>>> print(bw)
211025.0

"""
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