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renaming for consistency
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c782b812d5
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@ -177,7 +177,7 @@ class GWR:
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fixed=fixed,
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fixed=fixed,
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kernel=kernel).predict(coords_test, X_test)
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kernel=kernel).predict(coords_test, X_test)
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coefficients = []
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coeffs = []
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stand_errs = []
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stand_errs = []
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t_vals = []
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t_vals = []
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r_squared = model.localR2.flatten()
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r_squared = model.localR2.flatten()
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@ -185,12 +185,12 @@ class GWR:
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m = len(model.predy)
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m = len(model.predy)
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for idx in xrange(m):
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for idx in xrange(m):
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coefficients.append(json.dumps({var: model.params[idx, k]
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coeffs.append(json.dumps({var: model.params[idx, k]
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for k, var in enumerate(ind_vars)}))
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for k, var in enumerate(ind_vars)}))
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stand_errs.append(json.dumps({var: model.bse[idx, k]
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stand_errs.append(json.dumps({var: model.bse[idx, k]
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for k, var in enumerate(ind_vars)}))
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for k, var in enumerate(ind_vars)}))
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t_vals.append(json.dumps({var: model.tvalues[idx, k]
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t_vals.append(json.dumps({var: model.tvalues[idx, k]
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for k, var in enumerate(ind_vars)}))
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for k, var in enumerate(ind_vars)}))
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return zip(coefficients, stand_errs, t_vals,
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return zip(coeffs, stand_errs, t_vals,
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r_squared, predicted, rowid)
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r_squared, predicted, rowid)
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