From e6a9397373d2a4d5a976d1f9ef46ba9074cca2a9 Mon Sep 17 00:00:00 2001 From: Andy Eschbacher Date: Tue, 29 Nov 2016 13:30:07 -0500 Subject: [PATCH] pep8 updates --- .../crankshaft/regression/gwr_cs.py | 32 ++++++++++--------- 1 file changed, 17 insertions(+), 15 deletions(-) diff --git a/src/py/crankshaft/crankshaft/regression/gwr_cs.py b/src/py/crankshaft/crankshaft/regression/gwr_cs.py index 01042c3..36fbde1 100644 --- a/src/py/crankshaft/crankshaft/regression/gwr_cs.py +++ b/src/py/crankshaft/crankshaft/regression/gwr_cs.py @@ -31,9 +31,9 @@ def gwr(subquery, dep_var, ind_vars, plpy.notice(query) plpy.error('Analysis failed: %s' % err) - #unique ids and variable names list + # unique ids and variable names list rowid = np.array(query_result[0]['rowid'], dtype=np.int) - + # TODO: should x, y be centroids? point on surface? # lat, long coordinates x = np.array(query_result[0]['x']) @@ -51,10 +51,10 @@ def gwr(subquery, dep_var, ind_vars, attr_name = 'attr' + str(attr + 1) X[:, attr] = np.array( query_result[0][attr_name]).flatten() - - #add intercept variable name + + # add intercept variable name ind_vars.insert(0, 'intercept') - + # calculate bandwidth bw = Sel_BW(coords, Y, X, fixed=fixed, kernel=kernel).search() @@ -65,7 +65,7 @@ def gwr(subquery, dep_var, ind_vars, # column called coeffs: # {'pctrural': ..., 'pctpov': ..., ...} # Follow the same structure for other outputs - + coefficients = [] stand_errs = [] t_vals = [] @@ -74,12 +74,14 @@ def gwr(subquery, dep_var, ind_vars, r_squared = model.localR2 for idx in xrange(n): - coefficients.append(json.dumps({var: model.params[idx,k] for k, var in - enumerate(ind_vars)})) - stand_errs.append(json.dumps({var: model.bse[idx,k] for k, var in - enumerate(ind_vars)})) - t_vals.append(json.dumps({var: model.tvalues[idx,k] for k, var in - enumerate(ind_vars)})) - - plpy.notice(str(zip(coefficients, stand_errs, t_vals, predicted, residuals, r_squared, rowid))) - return zip(coefficients, stand_errs, t_vals, predicted, residuals, r_squared, rowid) + coefficients.append(json.dumps({var: model.params[idx, k] + for k, var in enumerate(ind_vars)})) + stand_errs.append(json.dumps({var: model.bse[idx, k] + for k, var in enumerate(ind_vars)})) + t_vals.append(json.dumps({var: model.tvalues[idx, k] + for k, var in enumerate(ind_vars)})) + + plpy.notice(str(zip(coefficients, stand_errs, t_vals, + predicted, residuals, r_squared, rowid))) + return zip(coefficients, stand_errs, t_vals, + predicted, residuals, r_squared, rowid)