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adding back filter t-vals lost in commit squash

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This commit is contained in:
Andy Eschbacher 2017-01-09 14:12:22 +00:00
parent 00567e5272
commit 87890926ad
3 changed files with 13 additions and 6 deletions
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10
src/pg/sql/21_gwr.sql
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@ -1,17 +1,19 @@
CREATE OR REPLACE FUNCTION
CDB_GWR(subquery text, dep_var text, ind_vars text[],
bw numeric default null, fixed boolean default False,
kernel text default 'bisquare')
kernel text default 'bisquare', geom_col text default 'the_geom',
id_col text default 'cartodb_id')
RETURNS table(coeffs JSON, stand_errs JSON, t_vals JSON,
predicted numeric, residuals numeric, r_squared numeric,
bandwidth numeric, rowid bigint)
filtered_t_vals JSON, predicted numeric,
residuals numeric, r_squared numeric, bandwidth numeric,
rowid bigint)
AS $$
from crankshaft.regression import GWR
gwr = GWR()
return gwr.gwr(subquery, dep_var, ind_vars, bw, fixed, kernel)
return gwr.gwr(subquery, dep_var, ind_vars, bw, fixed, kernel, geom_col, id_col)
$$ LANGUAGE plpythonu;

7
src/py/crankshaft/crankshaft/regression/gwr_cs.py
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@ -77,8 +77,11 @@ class GWR:
coeffs = []
stand_errs = []
t_vals = []
filtered_t_vals = []
# extracted model information
c_alpha = model.adj_alpha
filtered_t = model.filter_tvals(c_alpha[1])
predicted = model.predy.flatten()
residuals = model.resid_response
r_squared = model.localR2.flatten()
@ -92,8 +95,10 @@ class GWR:
for k, var in enumerate(ind_vars)}))
t_vals.append(json.dumps({var: model.tvalues[idx, k]
for k, var in enumerate(ind_vars)}))
filtered_t_vals.append(json.dumps({var: filtered_t[idx, k]
for k, var in enumerate(ind_vars)}))
return zip(coeffs, stand_errs, t_vals,
return zip(coeffs, stand_errs, t_vals, filtered_t_vals,
predicted, residuals, r_squared, bw, rowid)
def gwr_predict(self, subquery, dep_var, ind_vars,

2
src/py/crankshaft/test/test_regression_gwr.py
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@ -58,7 +58,7 @@ class GWRTest(unittest.TestCase):
fixed=self.params['fixed'])
# unpack response
coeffs, stand_errs, t_vals, predicteds, residuals, r_squareds, bws, rowids = zip(*gwr_resp)
coeffs, stand_errs, t_vals, t_vals_filtered, predicteds, residuals, r_squareds, bws, rowids = zip(*gwr_resp)
# known_coeffs = self.knowns['coeffs']
# data packed from https://github.com/TaylorOshan/pysal/blob/a44c5541e2e0d10a99ff05edc1b7f81b70f5a82f/pysal/examples/georgia/georgia_BS_NN_listwise.csv