def test_names(self):
w = pysal.queen_from_shapefile(pysal.examples.get_path('columbus.shp'))
gwk = pysal.kernelW_from_shapefile(pysal.examples.get_path('columbus.shp'),k=5,function='triangular', fixed=False)
name_x = ['inc']
name_y = 'crime'
name_yend = ['hoval']
name_q = ['discbd']
name_w = 'queen'
name_gwk = 'k=5'
name_ds = 'columbus'
reg = TSLS(self.y, self.X, self.yd, self.q,
spat_diag=True, w=w, robust='hac', gwk=gwk,
name_x=name_x, name_y=name_y, name_q=name_q, name_w=name_w,
name_yend=name_yend, name_gwk=name_gwk, name_ds=name_ds)
betas = np.array([[ 88.46579584], [ 0.5200379 ], [ -1.58216593]])
np.testing.assert_array_almost_equal(reg.betas, betas, 7)
vm = np.array([[ 225.0795089 , 17.11660041, -12.22448566],
[ 17.67097154, 2.47483461, -1.4183641 ],
[ -12.45093722, -1.40495464, 0.8700441 ]])
np.testing.assert_array_almost_equal(reg.vm, vm, 7)
self.assertListEqual(reg.name_x, ['CONSTANT']+name_x)
self.assertListEqual(reg.name_yend, name_yend)
self.assertListEqual(reg.name_q, name_q)
self.assertEqual(reg.name_y, name_y)
self.assertEqual(reg.name_w, name_w)
self.assertEqual(reg.name_gwk, name_gwk)
self.assertEqual(reg.name_ds, name_ds)
def test_kernelW_from_shapefile(self):
kw = pysal.kernelW_from_shapefile(pysal.examples.get_path(
'columbus.shp'), idVariable='POLYID')
self.assertEquals(kw.weights[1], [0.2052478782400463,
0.0070787731484506233, 1.0,
0.23051223027663237])
np.testing.assert_array_almost_equal(
kw.bandwidth[:3], np.array([[0.75333961], [0.75333961],
[0.75333961]]))
def test_hac(self):
gwk = pysal.kernelW_from_shapefile(pysal.examples.get_path('columbus.shp'),k=15,function='triangular', fixed=False)
reg = BaseTSLS(self.y, self.X, self.yd, self.q, robust='hac', gwk=gwk)
betas = np.array([[ 88.46579584], [ 0.5200379 ], [ -1.58216593]])
np.testing.assert_array_almost_equal(reg.betas, betas, 7)
vm = np.array([[ 231.07254978, 15.42050291, -11.3941033 ],
[ 15.01376346, 1.92422887, -1.11865505],
[ -11.34381641, -1.1279227 , 0.72053806]])
np.testing.assert_array_almost_equal(reg.vm, vm, 7)
def test_names(self):
X = np.array(self.db.by_col("INC"))
X = np.reshape(X, (49, 1))
X = SP.csr_matrix(X)
yd = np.array(self.db.by_col("CRIME"))
yd = np.reshape(yd, (49, 1))
q = np.array(self.db.by_col("DISCBD"))
q = np.reshape(q, (49, 1))
w = pysal.queen_from_shapefile(pysal.examples.get_path("columbus.shp"))
gwk = pysal.kernelW_from_shapefile(
pysal.examples.get_path("columbus.shp"), k=5, function="triangular", fixed=False
)
name_x = ["inc"]
name_y = "crime"
name_yend = ["crime"]
name_q = ["discbd"]
name_w = "queen"
name_gwk = "k=5"
name_ds = "columbus"
reg = GM_Lag(
self.y,
X,
yd,
q,
spat_diag=True,
w=w,
robust="hac",
gwk=gwk,
name_x=name_x,
name_y=name_y,
name_q=name_q,
name_w=name_w,
name_yend=name_yend,
name_gwk=name_gwk,
name_ds=name_ds,
)
betas = np.array([[5.46344924e01], [4.13301682e-01], [-5.92637442e-01], [-7.40490883e-03]])
np.testing.assert_array_almost_equal(reg.betas, betas, 7)
vm = np.array(
[
[5.70817052e02, -1.83655385e01, -8.36602575e00, 2.37538877e-02],
[-1.85224661e01, 6.53311383e-01, 2.84209566e-01, -6.47694160e-03],
[-8.31105622e00, 2.78772694e-01, 1.38144928e-01, -3.98175246e-03],
[2.66662466e-02, -6.23783104e-03, -4.11092891e-03, 1.10936528e-03],
]
)
np.testing.assert_array_almost_equal(reg.vm, vm, 6)
self.assertListEqual(reg.name_x, ["CONSTANT"] + name_x)
name_yend.append("W_crime")
self.assertListEqual(reg.name_yend, name_yend)
name_q.extend(["W_inc", "W_discbd"])
self.assertListEqual(reg.name_q, name_q)
self.assertEqual(reg.name_y, name_y)
self.assertEqual(reg.name_w, name_w)
self.assertEqual(reg.name_gwk, name_gwk)
self.assertEqual(reg.name_ds, name_ds)
def test_hac(self):
gwk = pysal.kernelW_from_shapefile(pysal.examples.get_path('columbus.shp'),k=5,function='triangular', fixed=False)
reg = TSLS(self.y, self.X, self.yd, self.q, robust='hac', gwk=gwk)
betas = np.array([[ 88.46579584], [ 0.5200379 ], [ -1.58216593]])
np.testing.assert_array_almost_equal(reg.betas, betas, 7)
vm = np.array([[ 225.0795089 , 17.11660041, -12.22448566],
[ 17.67097154, 2.47483461, -1.4183641 ],
[ -12.45093722, -1.40495464, 0.8700441 ]])
np.testing.assert_array_almost_equal(reg.vm, vm, 7)
self.assertEqual(reg.robust, 'hac')
def _kernel(arg_dict):
"""
General handler for building kernel based weights from shapefiles
Examples
--------
>>> w = wmd_reader('kernel.wmd')
>>> w.n
49
>>> w.meta_data
{'root': {u'input1': {u'data1': {u'type': u'shp',
u'uri': u'../examples/columbus.shp'}},
u'weight_type': u'kernel', u'transform': u'O',
u'parameters': {u'function': u'triangular',
u'bandwidths': None, u'k': 2}}}
"""
input1 = arg_dict['input1']['data1']
uri = input1['uri']
weight_type = arg_dict['weight_type']
weight_type = weight_type.lower()
k = 2
bandwidths = None
function = 'triangular'
if 'parameters' in arg_dict:
k = arg_dict['parameters'].get('k', k) # set default to 2
bandwidths = arg_dict['parameters'].get('bandwidths', bandwidths)
function = arg_dict['parameters'].get('function', function)
else:
parameters = {}
parameters['k'] = k
parameters['bandwidths'] = bandwidths
parameters['function'] = function
arg_dict['parameters'] = parameters
if weight_type == 'akernel':
# adaptive kernel
w = ps.adaptive_kernelW_from_shapefile(uri, bandwidths = bandwidths,
k=k, function = function)
elif weight_type == 'kernel':
w = ps.kernelW_from_shapefile(uri, k=k, function = function)
else:
print "Unsupported kernel: ",weight_type
return None
w = WMD(w.neighbors, w.weights)
w.meta_data = {}
w.meta_data["input1"] = {"type": 'shp', 'uri':uri}
w.meta_data["transform"] = w.transform
w.meta_data["weight_type"] = weight_type
w.meta_data['parameters'] = arg_dict['parameters']
return w
def test_init_hac_(self):
X = []
X.append(self.db.by_col("INC"))
X.append(self.db.by_col("CRIME"))
self.X = np.array(X).T
gwk = pysal.kernelW_from_shapefile(pysal.examples.get_path('columbus.shp'),k=15,function='triangular', fixed=False)
base_gm_lag = GM_Lag(self.y, self.X, w=self.w, w_lags=2, robust='hac', gwk=gwk)
tbetas = np.array([[ 4.53017056e+01], [ 6.20888617e-01], [ -4.80723451e-01], [ 2.83622122e-02]])
np.testing.assert_array_almost_equal(base_gm_lag.betas, tbetas)
dbetas = D.se_betas(base_gm_lag)
se_betas = np.array([ 19.08513569, 0.51769543, 0.18244862, 0.35460553])
np.testing.assert_array_almost_equal(dbetas, se_betas)
def test_Kernel(self):
kw = pysal.Kernel(self.points)
self.assertEqual(kw.weights[0],
[1.0, 0.50000004999999503, 0.44098306152674649])
kw15 = pysal.Kernel(self.points, bandwidth=15.0)
self.assertEqual(kw15[0], {
0: 1.0,
1: 0.33333333333333337,
3: 0.2546440075000701
})
self.assertEqual(kw15.bandwidth[0], 15.)
self.assertEqual(kw15.bandwidth[-1], 15.)
bw = [25.0, 15.0, 25.0, 16.0, 14.5, 25.0]
kwa = pysal.Kernel(self.points, bandwidth=bw)
self.assertEqual(kwa.weights[0], [
1.0, 0.59999999999999998, 0.55278640450004202, 0.10557280900008403
])
self.assertEqual(kwa.neighbors[0], [0, 1, 3, 4])
self.assertEqual(kwa.bandwidth[0], 25.)
self.assertEqual(kwa.bandwidth[1], 15.)
self.assertEqual(kwa.bandwidth[2], 25.)
self.assertEqual(kwa.bandwidth[3], 16.)
self.assertEqual(kwa.bandwidth[4], 14.5)
self.assertEqual(kwa.bandwidth[5], 25.)
kwea = pysal.Kernel(self.points, fixed=False)
self.assertEqual(kwea.weights[0],
[1.0, 0.10557289844279438, 9.9999990066379496e-08])
l = kwea.bandwidth.tolist()
self.assertEqual(
l,
[[11.180341005532938], [11.180341005532938], [20.000002000000002],
[11.180341005532938], [14.142137037944515], [18.027758180095585]])
kweag = pysal.Kernel(self.points, fixed=False, function='gaussian')
self.assertEqual(
kweag.weights[0],
[0.3989422804014327, 0.26741902915776961, 0.24197074871621341])
l = kweag.bandwidth.tolist()
self.assertEqual(
l,
[[11.180341005532938], [11.180341005532938], [20.000002000000002],
[11.180341005532938], [14.142137037944515], [18.027758180095585]])
kw = pysal.kernelW_from_shapefile(self.polyShp, idVariable='POLYID')
self.assertEqual(
set(kw.weights[1]),
set([
0.0070787731484506233, 0.2052478782400463, 0.23051223027663237,
1.0
]))
kwa = pysal.adaptive_kernelW_from_shapefile(self.polyShp)
self.assertEqual(kwa.weights[0],
[1.0, 0.03178906767736345, 9.9999990066379496e-08])
def test_hac(self):
gwk = pysal.kernelW_from_shapefile(
pysal.examples.get_path('columbus.shp'),
k=15,
function='triangular',
fixed=False)
reg = BaseTSLS(self.y, self.X, self.yd, self.q, robust='hac', gwk=gwk)
betas = np.array([[88.46579584], [0.5200379], [-1.58216593]])
np.testing.assert_array_almost_equal(reg.betas, betas, 7)
vm = np.array([[231.07254978, 15.42050291, -11.3941033],
[15.01376346, 1.92422887, -1.11865505],
[-11.34381641, -1.1279227, 0.72053806]])
np.testing.assert_array_almost_equal(reg.vm, vm, 7)
def test_init_hac_(self):
X = []
X.append(self.db.by_col("INC"))
X.append(self.db.by_col("CRIME"))
self.X = np.array(X).T
self.X = SP.csr_matrix(self.X)
gwk = pysal.kernelW_from_shapefile(pysal.examples.get_path('columbus.shp'),k=15,function='triangular', fixed=False)
base_gm_lag = GM_Lag(self.y, self.X, w=self.w, w_lags=2, robust='hac', gwk=gwk)
tbetas = np.array([[ 4.53017056e+01], [ 6.20888617e-01], [ -4.80723451e-01], [ 2.83622122e-02]])
np.testing.assert_array_almost_equal(base_gm_lag.betas, tbetas)
dbetas = D.se_betas(base_gm_lag)
se_betas = np.array([ 19.08513569, 0.51769543, 0.18244862, 0.35460553])
np.testing.assert_array_almost_equal(dbetas, se_betas)
def _kernel(arg_dict):
"""
General handler for building kernel based weights from shapefiles
Examples
--------
>>> w = wmd_reader('kernel.wmd')
>>> w.n
49
>>> w.meta_data
{'root': {u'input1': {u'data1': {u'type': u'shp', u'uri': u'../examples/columbus.shp'}}, u'weight_type': u'kernel', u'transform': u'O', u'parameters': {u'function': u'triangular', u'bandwidths': None, u'k': 2}}}
"""
input1 = arg_dict['input1']['data1']
uri = input1['uri']
weight_type = arg_dict['weight_type']
weight_type = weight_type.lower()
k = 2
bandwidths = None
function = 'triangular'
if 'parameters' in arg_dict:
k = arg_dict['parameters'].get('k',k) # set default to 2
bandwidths = arg_dict['parameters'].get('bandwidths',bandwidths)
function = arg_dict['parameters'].get('function', function)
else:
parameters = {}
parameters['k'] = k
parameters['bandwidths'] = bandwidths
parameters['function'] = function
arg_dict['parameters'] = parameters
if weight_type == 'akernel':
# adaptive kernel
w = ps.adaptive_kernelW_from_shapefile(uri, bandwidths = bandwidths,
k=k, function = function)
elif weight_type == 'kernel':
w = ps.kernelW_from_shapefile(uri, k=k, function = function)
else:
print "Unsupported kernel: ",weight_type
return None
w = WMD(w.neighbors, w.weights)
w.meta_data = {}
w.meta_data["input1"] = {"type": 'shp', 'uri':uri}
w.meta_data["transform"] = w.transform
w.meta_data["weight_type"] = weight_type
w.meta_data['parameters'] = arg_dict['parameters']
return w
def test_hac(self):
gwk = pysal.kernelW_from_shapefile(
pysal.examples.get_path('columbus.shp'),
k=5,
function='triangular',
fixed=False)
reg = TSLS(self.y, self.X, self.yd, self.q, robust='hac', gwk=gwk)
betas = np.array([[88.46579584], [0.5200379], [-1.58216593]])
np.testing.assert_array_almost_equal(reg.betas, betas, 7)
vm = np.array([[225.0795089, 17.11660041, -12.22448566],
[17.67097154, 2.47483461, -1.4183641],
[-12.45093722, -1.40495464, 0.8700441]])
np.testing.assert_array_almost_equal(reg.vm, vm, 7)
self.assertEqual(reg.robust, 'hac')
def test_init_hac_(self):
w_lags = 2
X = []
X.append(self.db.by_col("INC"))
X.append(self.db.by_col("CRIME"))
self.X = np.array(X).T
yd2, q2 = pysal.spreg.utils.set_endog(self.y, self.X, self.w, None, None, w_lags, True)
self.X = np.hstack((np.ones(self.y.shape),self.X))
gwk = pysal.kernelW_from_shapefile(pysal.examples.get_path('columbus.shp'),k=15,function='triangular', fixed=False)
base_gm_lag = BaseGM_Lag(self.y, self.X, yend=yd2, q=q2, w=self.w.sparse, w_lags=w_lags, robust='hac', gwk=gwk)
tbetas = np.array([[ 4.53017056e+01], [ 6.20888617e-01], [ -4.80723451e-01], [ 2.83622122e-02]])
np.testing.assert_array_almost_equal(base_gm_lag.betas, tbetas)
dbetas = D.se_betas(base_gm_lag)
se_betas = np.array([ 19.08513569, 0.51769543, 0.18244862, 0.35460553])
np.testing.assert_array_almost_equal(dbetas, se_betas)
def test_Kernel(self):
kw = pysal.Kernel(self.points)
wds = {kw.neighbors[0][i]: v for i, v in enumerate(kw.weights[0])}
self.assertEqual(wds, {0: 1, 1: 0.500000049999995, 3: 0.4409830615267465})
kw15 = pysal.Kernel(self.points, bandwidth=15.0)
self.assertEqual(kw15[0], {0: 1.0, 1: 0.33333333333333337,
3: 0.2546440075000701})
self.assertEqual(kw15.bandwidth[0], 15.)
self.assertEqual(kw15.bandwidth[-1], 15.)
bw = [25.0, 15.0, 25.0, 16.0, 14.5, 25.0]
kwa = pysal.Kernel(self.points, bandwidth=bw)
wds = {kwa.neighbors[0][i]: v for i, v in enumerate(kwa.weights[0])}
self.assertEqual(wds, {0: 1.0, 1: 0.59999999999999998,
3: 0.55278640450004202, 4: 0.10557280900008403})
self.assertEqual(kwa.bandwidth[0], 25.)
self.assertEqual(kwa.bandwidth[1], 15.)
self.assertEqual(kwa.bandwidth[2], 25.)
self.assertEqual(kwa.bandwidth[3], 16.)
self.assertEqual(kwa.bandwidth[4], 14.5)
self.assertEqual(kwa.bandwidth[5], 25.)
kwea = pysal.Kernel(self.points, fixed=False)
wds = {kwea.neighbors[0][i]: v for i, v in enumerate(kw.weights[0])}
self.assertEqual(kwea.weights[0], [1.0, 0.10557289844279438,
9.9999990066379496e-08])
l = kwea.bandwidth.tolist()
np.allclose(l, [[11.180341005532938], [11.180341005532938],
[20.000002000000002], [11.180341005532938],
[14.142137037944515], [18.027758180095585]])
kweag = pysal.Kernel(self.points, fixed=False, function='gaussian')
wds = {kweag.neighbors[0][i]: v for i, v in enumerate(kweag.weights[0])}
self.assertEqual(wds, {0: 0.3989422804014327,
1: 0.26741902915776961,
3: 0.24197074871621341})
l = kweag.bandwidth.tolist()
np.allclose(l, [[11.180341005532938], [11.180341005532938],
[20.000002000000002], [11.180341005532938],
[14.142137037944515], [18.027758180095585]])
kw = pysal.kernelW_from_shapefile(self.polyShp, idVariable='POLYID')
wds = {kw.neighbors[1][i]: v for i, v in enumerate(kw.weights[1])}
self.assertEqual(wds, {4: 0.0070787731484506233,
2: 0.2052478782400463,
3: 0.23051223027663237,
1: 1.0})
kwa = pysal.adaptive_kernelW_from_shapefile(self.polyShp)
wds = {kwa.neighbors[0][i]: v for i, v in enumerate(kwa.weights[0])}
self.assertEqual(wds, {0: 1.0, 2: 0.03178906767736345,
1: 9.9999990066379496e-08})
def test_names(self):
w = pysal.queen_from_shapefile(pysal.examples.get_path("columbus.shp"))
gwk = pysal.kernelW_from_shapefile(
pysal.examples.get_path("columbus.shp"), k=5, function="triangular", fixed=False
)
name_x = ["inc"]
name_y = "crime"
name_yend = ["hoval"]
name_q = ["discbd"]
name_w = "queen"
name_gwk = "k=5"
name_ds = "columbus"
reg = TSLS(
self.y,
self.X,
self.yd,
self.q,
spat_diag=True,
w=w,
robust="hac",
gwk=gwk,
name_x=name_x,
name_y=name_y,
name_q=name_q,
name_w=name_w,
name_yend=name_yend,
name_gwk=name_gwk,
name_ds=name_ds,
)
betas = np.array([[88.46579584], [0.5200379], [-1.58216593]])
np.testing.assert_array_almost_equal(reg.betas, betas, 7)
vm = np.array(
[
[225.0795089, 17.11660041, -12.22448566],
[17.67097154, 2.47483461, -1.4183641],
[-12.45093722, -1.40495464, 0.8700441],
]
)
np.testing.assert_array_almost_equal(reg.vm, vm, 7)
self.assertListEqual(reg.name_x, ["CONSTANT"] + name_x)
self.assertListEqual(reg.name_yend, name_yend)
self.assertListEqual(reg.name_q, name_q)
self.assertEqual(reg.name_y, name_y)
self.assertEqual(reg.name_w, name_w)
self.assertEqual(reg.name_gwk, name_gwk)
self.assertEqual(reg.name_ds, name_ds)
def test_names(self):
w = pysal.queen_from_shapefile(pysal.examples.get_path('columbus.shp'))
gwk = pysal.kernelW_from_shapefile(
pysal.examples.get_path('columbus.shp'),
k=5,
function='triangular',
fixed=False)
name_x = ['inc']
name_y = 'crime'
name_yend = ['hoval']
name_q = ['discbd']
name_w = 'queen'
name_gwk = 'k=5'
name_ds = 'columbus'
reg = TSLS(self.y,
self.X,
self.yd,
self.q,
spat_diag=True,
w=w,
robust='hac',
gwk=gwk,
name_x=name_x,
name_y=name_y,
name_q=name_q,
name_w=name_w,
name_yend=name_yend,
name_gwk=name_gwk,
name_ds=name_ds)
betas = np.array([[88.46579584], [0.5200379], [-1.58216593]])
np.testing.assert_array_almost_equal(reg.betas, betas, 7)
vm = np.array([[225.0795089, 17.11660041, -12.22448566],
[17.67097154, 2.47483461, -1.4183641],
[-12.45093722, -1.40495464, 0.8700441]])
np.testing.assert_array_almost_equal(reg.vm, vm, 7)
self.assertListEqual(reg.name_x, ['CONSTANT'] + name_x)
self.assertListEqual(reg.name_yend, name_yend)
self.assertListEqual(reg.name_q, name_q)
self.assertEqual(reg.name_y, name_y)
self.assertEqual(reg.name_w, name_w)
self.assertEqual(reg.name_gwk, name_gwk)
self.assertEqual(reg.name_ds, name_ds)
def test_names(self):
w = pysal.queen_from_shapefile(pysal.examples.get_path('columbus.shp'))
gwk = pysal.kernelW_from_shapefile(pysal.examples.get_path('columbus.shp'),k=5,function='triangular', fixed=False)
name_x = ['inc']
name_y = 'crime'
name_yend = ['hoval']
name_q = ['discbd']
name_w = 'queen'
name_gwk = 'k=5'
name_ds = 'columbus'
name_regimes= 'nsa'
reg = TSLS_Regimes(self.y, self.x, self.yd, self.q, self.regimes, regime_err_sep=False,
spat_diag=True, w=w, robust='hac', gwk=gwk, name_regimes=name_regimes,
name_x=name_x, name_y=name_y, name_q=name_q, name_w=name_w,
name_yend=name_yend, name_gwk=name_gwk, name_ds=name_ds)
betas = np.array([[ 80.23408166],[ 5.48218125],[ 82.98396737],[ 0.49775429],[ -3.72663211],[ -1.27451485]])
np.testing.assert_array_almost_equal(reg.betas, betas, 7)
vm = np.array([[ 522.75813101, 120.64940697, -15.60303241, -0.976389 ,\
-67.15556574, 0.64553579],\
[ 122.83491674, 122.62303068, -5.52270916, 0.05023488,\
-57.89404902, 0.15750428],\
[ 0.1983661 , -0.03539147, 335.24731378, 17.40764168,\
-0.26447114, -14.3375455 ],\
[ -0.13612426, -0.43622084, 18.46644989, 2.70320508,\
0.20398876, -1.31821991],\
[ -68.0704928 , -58.03685405, 2.66225388, 0.00323082,\
27.68512974, -0.08124602],\
[ -0.08001296, 0.13575504, -14.6998294 , -1.28225201,\
-0.05193056, 0.79845124]])
np.testing.assert_array_almost_equal(reg.vm, vm, 7)
self.assertEqual(reg.name_x, ['0_CONSTANT', '0_inc', '1_CONSTANT', '1_inc'])
self.assertEqual(reg.name_yend, ['0_hoval', '1_hoval'])
self.assertEqual(reg.name_q, ['0_discbd', '1_discbd'])
self.assertEqual(reg.name_y, name_y)
self.assertEqual(reg.name_w, name_w)
self.assertEqual(reg.name_gwk, name_gwk)
self.assertEqual(reg.name_ds, name_ds)
self.assertEqual(reg.name_regimes, name_regimes)
def test_names(self):
X = np.array(self.db.by_col("INC"))
X = np.reshape(X, (49,1))
X = SP.csr_matrix(X)
yd = np.array(self.db.by_col("CRIME"))
yd = np.reshape(yd, (49,1))
q = np.array(self.db.by_col("DISCBD"))
q = np.reshape(q, (49,1))
w = pysal.queen_from_shapefile(pysal.examples.get_path('columbus.shp'))
gwk = pysal.kernelW_from_shapefile(pysal.examples.get_path('columbus.shp'),k=5,function='triangular', fixed=False)
name_x = ['inc']
name_y = 'crime'
name_yend = ['crime']
name_q = ['discbd']
name_w = 'queen'
name_gwk = 'k=5'
name_ds = 'columbus'
reg = GM_Lag(self.y, X, yend=yd, q=q,
spat_diag=True, w=w, robust='hac', gwk=gwk,
name_x=name_x, name_y=name_y, name_q=name_q, name_w=name_w,
name_yend=name_yend, name_gwk=name_gwk, name_ds=name_ds)
betas = np.array([[ 5.46344924e+01], [ 4.13301682e-01], [ -5.92637442e-01], [ -7.40490883e-03]])
np.testing.assert_array_almost_equal(reg.betas, betas, 7)
vm = np.array( [[ 5.70817052e+02, -1.83655385e+01, -8.36602575e+00, 2.37538877e-02],
[ -1.85224661e+01, 6.53311383e-01, 2.84209566e-01, -6.47694160e-03],
[ -8.31105622e+00, 2.78772694e-01, 1.38144928e-01, -3.98175246e-03],
[ 2.66662466e-02, -6.23783104e-03, -4.11092891e-03, 1.10936528e-03]])
np.testing.assert_array_almost_equal(reg.vm, vm, 6)
self.assertListEqual(reg.name_x, ['CONSTANT']+name_x)
name_yend.append('W_crime')
self.assertListEqual(reg.name_yend, name_yend)
name_q.extend(['W_inc', 'W_discbd'])
self.assertListEqual(reg.name_q, name_q)
self.assertEqual(reg.name_y, name_y)
self.assertEqual(reg.name_w, name_w)
self.assertEqual(reg.name_gwk, name_gwk)
self.assertEqual(reg.name_ds, name_ds)
def test_names(self):
X = np.array(self.db.by_col("INC"))
X = np.reshape(X, (49,1))
X = SP.csr_matrix(X)
yd = np.array(self.db.by_col("CRIME"))
yd = np.reshape(yd, (49,1))
q = np.array(self.db.by_col("DISCBD"))
q = np.reshape(q, (49,1))
w = pysal.queen_from_shapefile(pysal.examples.get_path('columbus.shp'))
gwk = pysal.kernelW_from_shapefile(pysal.examples.get_path('columbus.shp'),k=5,function='triangular', fixed=False)
name_x = ['inc']
name_y = 'crime'
name_yend = ['crime']
name_q = ['discbd']
name_w = 'queen'
name_gwk = 'k=5'
name_ds = 'columbus'
reg = GM_Lag(self.y, X, yd, q,
spat_diag=True, w=w, robust='hac', gwk=gwk,
name_x=name_x, name_y=name_y, name_q=name_q, name_w=name_w,
name_yend=name_yend, name_gwk=name_gwk, name_ds=name_ds)
betas = np.array([[ 5.46344924e+01], [ 4.13301682e-01], [ -5.92637442e-01], [ -7.40490883e-03]])
np.testing.assert_array_almost_equal(reg.betas, betas, 7)
vm = np.array( [[ 5.70817052e+02, -1.83655385e+01, -8.36602575e+00, 2.37538877e-02],
[ -1.85224661e+01, 6.53311383e-01, 2.84209566e-01, -6.47694160e-03],
[ -8.31105622e+00, 2.78772694e-01, 1.38144928e-01, -3.98175246e-03],
[ 2.66662466e-02, -6.23783104e-03, -4.11092891e-03, 1.10936528e-03]])
np.testing.assert_array_almost_equal(reg.vm, vm, 6)
self.assertListEqual(reg.name_x, ['CONSTANT']+name_x)
name_yend.append('W_crime')
self.assertListEqual(reg.name_yend, name_yend)
name_q.extend(['W_inc', 'W_discbd'])
self.assertListEqual(reg.name_q, name_q)
self.assertEqual(reg.name_y, name_y)
self.assertEqual(reg.name_w, name_w)
self.assertEqual(reg.name_gwk, name_gwk)
self.assertEqual(reg.name_ds, name_ds)
