adds psql connector
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@ -1,35 +1,59 @@
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import numpy as np
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from base.gwr import GWR
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from base.sel_bw import Sel_BW
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from gwr.base.gwr import GWR
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from gwr.base.sel_bw import Sel_BW
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def gwr(subquery, dep_var, ind_vars, fixed=False, kernel='bisquare'):
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def gwr(subquery, dep_var, ind_vars,
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fixed=False, kernel='bisquare'):
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"""
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subquery: 'select * from interesting_table'
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subquery: 'select * from demographics'
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dep_var: 'pctbachelor'
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ind_vars: ['intercept', 'pctpov', 'pctrural', 'pctblack']
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fixed: False (kNN) or True ('distance')
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kernel: 'bisquare' (default), or 'exponential', 'gaussian'
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"""
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query_result = subquery
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rowid = np.array(query_result[0]['rowid'])
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# query_result = subquery
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# rowid = np.array(query_result[0]['rowid'])
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params = {'geom_col': 'the_geom',
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'id_col': 'cartodb_id',
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'subquery': subquery,
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'dep_var': dep_var,
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'ind_vars': ind_vars}
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try:
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query_result = plpy.execute(pu.gwr_query(params))
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except plpy.SPIError, err:
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plpy.error('Analysis failed: %s' % err)
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# TODO: should x, y be centroids? point on surface?
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# lat, long coordinates
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x = np.array(query_result[0]['x'])
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y = np.array(query_result[0]['y'])
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coords = zip(x, y)
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Y = query_result[0]['dep'].reshape((-1, 1))
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# extract dependent variable
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Y = query_result[0]['dep_var'].reshape((-1, 1))
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n = Y.shape[0]
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k = len(ind_vars)
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X = np.zeros((n, k))
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for attr in range(0, k):
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attr_name = 'attr' + str(attr+1)
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X[:, attr] = np.array(query_result[0][attr_name]).flatten()
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attr_name = 'attr' + str(attr + 1)
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X[:, attr] = np.array(
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query_result[0][attr_name]).flatten()
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bw = Sel_BW(coords, Y, X, fixed=fixed, kernel=kernel).search()
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model = GWR(coords, Y, X, bw, fixed=fixed, kernel=kernel).fit()
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# calculate bandwidth
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bw = Sel_BW(coords, Y, X,
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fixed=fixed, kernel=kernel).search()
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model = GWR(coords, Y, X, bw,
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fixed=fixed, kernel=kernel).fit()
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# TODO: iterate from 0, n-1 and fill objects like this, for a
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# column called coeffs:
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# {'pctrural': ..., 'pctpov': ..., ...}
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# Follow the same structure for other outputs
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coefficients = model.params.reshape((-1,))
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t_vals = model.tvalues.reshape((-1,))
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stand_errs = model.bse.reshape((-1))
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@ -39,4 +63,5 @@ def gwr(subquery, dep_var, ind_vars, fixed=False, kernel='bisquare'):
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rowid = np.tile(rowid, k+1).reshape((-1,))
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var_name = np.tile(ind_vars, k+1).reshape((-1,))
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return zip(coefficients, stand_errs, t_vals, predicted, residuals, r_squared, rowid, var_name)
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return zip(coefficients, stand_errs, t_vals, predicted,
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residuals, r_squared, rowid)
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