How to use pysal - 10 common examples

>>> w = np.array([0.5, 0.1, 0.3, 0.8])

    We specify the number of groups for which the weighted mean is computed.

    >>> n = 2

    Applying sum_by_n function

    >>> sum_by_n(d, w, n)
    array([ 5.9, 30. ])

    """
    t = len(d)
    h = t // n #must be floor!
    d = d * w
    return np.array([sum(d[i: i + h]) for i in range(0, t, h)])

def internal_or_external(polys,filament, vertices):
    #Modification of Serge's code to find poly in poly for line in poly
    #pl = ps.cg.PolygonLocator(polys) #Trying to use this for polyline in polygon
    
    #Spatial Index of Filaments and minimal cycles (polygons)
    polyline = ps.cg.Chain([ps.cg.Point(vertices[pnt]) for pnt in filament])
    polyline_mbr =  polyline.bounding_box
    pl = ps.cg.PolygonLocator(polys)
    overlaps = pl.overlapping(polyline_mbr)
    
    #For the overlapping MBRs check to see if the polyline is internal or external to the min cycle
    for k in range(len(overlaps)):
        s = sum(overlaps[k].contains_point(v) for v in polyline.vertices)
        if s == len(polyline.vertices):
            #Internal
            return True
        else:
            return False

def setUp(self):
        db = pysal.open(pysal.examples.get_path('columbus.dbf'),'r')
        y = np.array(db.by_col("HOVAL"))
        y = np.reshape(y, (49,1))
        self.y = np.round(y).astype(int)
        X = []
        X.append(db.by_col("INC"))
        X.append(db.by_col("CRIME"))
        self.X = np.array(X).T

def _test():
    import doctest
    start_suppress = np.get_printoptions()['suppress']
    np.set_printoptions(suppress=True)
    doctest.testmod()
    np.set_printoptions(suppress=start_suppress)


if __name__ == '__main__':
    _test()

    import numpy as np
    import pysal
    db = pysal.open(pysal.examples.get_path("columbus.dbf"), 'r')
    y_var = 'CRIME'
    y = np.array([db.by_col(y_var)]).reshape(49, 1)
    x_var = ['INC']
    x = np.array([db.by_col(name) for name in x_var]).T
    yd_var = ['HOVAL']
    yd = np.array([db.by_col(name) for name in yd_var]).T
    q_var = ['DISCBD']
    q = np.array([db.by_col(name) for name in q_var]).T
    w = pysal.rook_from_shapefile(pysal.examples.get_path("columbus.shp"))
    w.transform = 'r'
    model = GM_Lag(
        y, x, yd, q, w=w, spat_diag=True, name_y=y_var, name_x=x_var,
        name_yend=yd_var, name_q=q_var, name_ds='columbus', name_w='columbus.gal')
    print model.summary

def _test():
    import doctest
    doctest.testmod()

                     
if __name__ == '__main__':
    _test()    
    import numpy as np
    import pysal
    db=pysal.open("examples/columbus.dbf","r")
    y = np.array(db.by_col("CRIME"))
    y = np.reshape(y, (49,1))
    X = []
    X.append(db.by_col("INC"))
    X = np.array(X).T
    yd = []
    yd.append(db.by_col("HOVAL"))
    yd = np.array(yd).T
    # instrument for HOVAL with DISCBD
    q = []
    q.append(db.by_col("DISCBD"))
    q = np.array(q).T
    reg = BaseTSLS(y, X, yd, q=q, robust='white')
    print reg.betas
    print reg.vm

model.w = w_r
    return model


def _test():
    import doctest
    start_suppress = np.get_printoptions()['suppress']
    np.set_printoptions(suppress=True)
    doctest.testmod()
    np.set_printoptions(suppress=start_suppress)

if __name__ == '__main__':
    _test()
    import numpy as np
    import pysal
    db = pysal.open(pysal.examples.get_path('columbus.dbf'), 'r')
    y_var = 'CRIME'
    y = np.array([db.by_col(y_var)]).reshape(49, 1)
    x_var = ['INC', 'HOVAL']
    x = np.array([db.by_col(name) for name in x_var]).T
    r_var = 'NSA'
    regimes = db.by_col(r_var)
    w = pysal.rook_from_shapefile(pysal.examples.get_path("columbus.shp"))
    w.transform = 'r'
    olsr = OLS_Regimes(y, x, regimes, w=w, constant_regi='many', nonspat_diag=False, spat_diag=False, name_y=y_var, name_x=['INC', 'HOVAL'],
                       name_ds='columbus', name_regimes=r_var, name_w='columbus.gal', regime_err_sep=True, cols2regi=[True, True], sig2n_k=True, robust='white')
    print olsr.summary

def _test():
    import doctest
    start_suppress = np.get_printoptions()['suppress']
    np.set_printoptions(suppress=True)
    doctest.testmod()
    np.set_printoptions(suppress=start_suppress)

if __name__ == '__main__':
    _test()
    import numpy as np
    import pysal
    dbf = pysal.open(pysal.examples.get_path('columbus.dbf'), 'r')
    y = np.array([dbf.by_col('CRIME')]).T
    var_x = ['INC', 'HOVAL']
    x = np.array([dbf.by_col(name) for name in var_x]).T
    w = pysal.open(pysal.examples.get_path("columbus.gal"), 'r').read()
    w.transform = 'r'
    probit1 = Probit(
        (y > 40).astype(float), x, w=w, name_x=var_x, name_y="CRIME",
        name_ds="Columbus", name_w="columbus.dbf")
    print probit1.summary

model.schwarz = DIAG.schwarz(reg=model)
    return model


def _test():
    import doctest
    start_suppress = np.get_printoptions()['suppress']
    np.set_printoptions(suppress=True)
    doctest.testmod()
    np.set_printoptions(suppress=start_suppress)

if __name__ == "__main__":
    _test()
    import numpy as np
    import pysal as ps
    db = ps.open(ps.examples.get_path("baltim.dbf"), 'r')
    ds_name = "baltim.dbf"
    y_name = "PRICE"
    y = np.array(db.by_col(y_name)).T
    y.shape = (len(y), 1)
    x_names = ["NROOM", "NBATH", "PATIO", "FIREPL",
               "AC", "GAR", "AGE", "LOTSZ", "SQFT"]
    x = np.array([db.by_col(var) for var in x_names]).T
    ww = ps.open(ps.examples.get_path("baltim_q.gal"))
    w = ww.read()
    ww.close()
    w_name = "baltim_q.gal"
    w.transform = 'r'
    regimes = db.by_col("CITCOU")

    mllag = ML_Lag_Regimes(y, x, regimes, w=w, method='full', name_y=y_name, name_x=x_names,
                           name_w=w_name, name_ds=ds_name, regime_lag_sep=True, constant_regi='many',

np.set_printoptions(suppress=start_suppress)

if __name__ == "__main__":
    _test()
    import numpy as np
    import pysal as ps

    db = ps.open(ps.examples.get_path("baltim.dbf"), 'r')
    ds_name = "baltim.dbf"
    y_name = "PRICE"
    y = np.array(db.by_col(y_name)).T
    y.shape = (len(y), 1)
    x_names = ["NROOM", "NBATH", "PATIO", "FIREPL",
               "AC", "GAR", "AGE", "LOTSZ", "SQFT"]
    x = np.array([db.by_col(var) for var in x_names]).T
    ww = ps.open(ps.examples.get_path("baltim_q.gal"))
    w = ww.read()
    ww.close()
    w_name = "baltim_q.gal"
    w.transform = 'r'

    regimes = []
    y_coord = np.array(db.by_col("Y"))
    for i in y_coord:
        if i > 544.5:
            regimes.append("North")
        else:
            regimes.append("South")

    mlerror = ML_Error_Regimes(y, x, regimes, w=w, method='full', name_y=y_name,
                               name_x=x_names, name_w=w_name, name_ds=ds_name, regime_err_sep=False,
                               name_regimes="North")

start_suppress = np.get_printoptions()['suppress']
    np.set_printoptions(suppress=True)
    doctest.testmod()
    np.set_printoptions(suppress=start_suppress)

if __name__ == '__main__':
    _test()

    import numpy as np
    import pysal
    db = pysal.open(pysal.examples.get_path("columbus.dbf"), 'r')
    y_var = 'CRIME'
    y = np.array([db.by_col(y_var)]).reshape(49, 1)
    x_var = ['INC', 'HOVAL']
    x = np.array([db.by_col(name) for name in x_var]).T
    w = pysal.rook_from_shapefile(pysal.examples.get_path("columbus.shp"))
    w.transform = 'r'
    ols = OLS(
        y, x, w=w, nonspat_diag=True, spat_diag=True, name_y=y_var, name_x=x_var,
        name_ds='columbus', name_w='columbus.gal', robust='white', sig2n_k=True, moran=True)
    print ols.summary