def generateWeightsUsingShapefile(shapeFilePath,
idVariable=None,
weights=None,
kind="queen",
k=None,
binary=False):
# use weights from shapefile for purely geographic
w = None
if weights == None:
if kind == "queen":
w = pysal.queen_from_shapefile(shapeFilePath,
idVariable=idVariable)
if kind == "rook":
w = pysal.rook_from_shapefile(shapeFilePath, idVariable=idVariable)
if kind == "knn" and type(k) == int:
w = pysal.knnW_from_shapefile(shapefile=shapeFilePath,
k=k,
idVariable=idVariable)
if kind == "band":
threshold = pysal.min_threshold_dist_from_shapefile(
shapeFilePath, idVariable=idVariable)
if binary == True:
w = pysal.weights.DistanceBand.from_shapefile(
shapeFilePath,
threshold=threshold,
binary=True,
idVariable=idVariable)
else:
w = pysal.threshold_continuousW_from_shapefile(
shapefile=shapeFilePath,
threshold=threshold,
idVariable=idVariable)
if kind == "kernel":
w = pysal.adaptive_kernelW_from_shapefile(shapeFilePath,
diagonal=True,
k=5,
idVariable=idVariable)
# else use user defined weights to create "space" instead of "place"
else:
if kind == "rook":
w = pysal.rook_from_shapefile(shapeFilePath, idVariable=idVariable)
if kind == "knn":
w = pysal.knnW_from_shapefile(shapeFilePath,
k=k,
idVariable=idVariable)
else:
w = pysal.queen_from_shapefile(shapeFilePath,
idVariable=idVariable)
neighbors = w.neighbor_offsets
w = pysal.W(neighbors, weights=weights)
# row standardize the matrix. better to do it here and use it somewhere else.
w.transform = 'r'
if binary == True:
w.transform = 'b'
return w
def test_knnW_from_shapefile(self):
wc = pysal.knnW_from_shapefile(pysal.examples.get_path("columbus.shp"))
self.assertAlmostEquals(wc.pct_nonzero, 0.040816326530612242)
wc3 = pysal.knnW_from_shapefile(pysal.examples.get_path(
"columbus.shp"), k=3)
self.assertEquals(wc3.weights[1], [1, 1, 1])
self.assertEquals(set(wc3.neighbors[1]), set([3, 0, 7]))
self.assertEquals(set(wc.neighbors[0]), set([2, 1]))
w = pysal.knnW_from_shapefile(pysal.examples.get_path('juvenile.shp'))
self.assertAlmostEquals(w.pct_nonzero, 0.011904761904761904)
w1 = pysal.knnW_from_shapefile(
pysal.examples.get_path('juvenile.shp'), k=1)
self.assertAlmostEquals(w1.pct_nonzero, 0.0059523809523809521)
def get(self,shpName='',width=0,height=0):
print shpName,width,height
if not shpName in self.SHPS:
return self.index()
shp = pysal.open(self.SHPS[shpName])
W = None
if 'w' in self.request.GET:
wtype = self.request.GET['w']
if wtype.lower() == 'rook':
W = pysal.rook_from_shapefile(self.SHPS[shpName])
elif wtype.lower() == 'queen':
W = pysal.queen_from_shapefile(self.SHPS[shpName])
else:
try:
k = int(wtype)
W = pysal.knnW_from_shapefile(self.SHPS[shpName],k)
except:
print "No valid W"
print shp
if width and height:
width=int(width)
height=int(height)
if W:
return self.write({'len':len(shp), 'polygons':shift_scale_shp(shp,width,height),'width':width,'height':height,'W':W.neighbors})
else:
return self.write({'len':len(shp), 'polygons':shift_scale_shp(shp,width,height),'width':width,'height':height,'W':'null'})
return self.write({'len':len(shp)})
def __init__(self, filepath, outname, namelist, idlist, nb="queen", factor=2):
"""
Initiation of modules
"""
f=Dbf(filepath+".dbf")
#Create mapping of locations to row id
self.locations = dict()
i=0
for row in f:
uid=unicode("".join([row[k] for k in idlist]))
locnames = unicode(", ".join([row[k] for k in namelist]),"ascii","ignore")
self.locations[i] = {outname:locnames,"id":uid}
i+=1
self.__dict__[outname]= self.locations
self.outname = outname
#Get Neightbor weights by queen, rook, knn, distance
if nb=="queen":
self.wt = pysal.queen_from_shapefile(filepath+".shp")
elif nb=="rook":
self.wt = pysal.rook_from_shapefile(filepath+".shp")
elif nb=="knn":
self.wt = pysal.knnW_from_shapefile(filepath+".shp", k=factor)
elif nb=="distance":
self.wt = pysal.threshold_binaryW_from_shapefile(filepath+".shp",k)
#Create dictionary of neighbors for each region
self.neighbors ={}
for i,j in enumerate(self.wt):
self.neighbors[self.locations[i]["id"]] = {self.outname:self.locations[i][self.outname]
,"neighbors":dict([[self.locations[k]["id"],self.locations[k][self.outname]] for k in j.keys()])}
def create_weights_from_shp(self, config):
os.chdir(config['data_dir'])
shapefile_name = config['output_shp']+".shp"
w = ps.knnW_from_shapefile(shapefile_name, k=config['number_of_neighbors'], idVariable=config['shapefile_id_name'])
w.transform = 'r'
fo = ps.open(config['output_shp']+".gwt", "w")
fo.write(w)
fo.close()
return config['output_shp']+".gwt"
def test_knnW(self):
x = np.indices((5, 5))
x, y = np.indices((5, 5))
x.shape = (25, 1)
y.shape = (25, 1)
data = np.hstack([x, y])
wnn2 = pysal.knnW(data, k=2)
wnn4 = pysal.knnW(data, k=4)
wnn4.neighbors[0]
self.assertEqual(set(wnn4.neighbors[0]), set([1, 5, 6, 2]))
self.assertEqual(set(wnn2.neighbors[5]), set([0, 6]))
self.assertEqual(wnn2.pct_nonzero, 8.0)
wnn3e = pysal.knnW(data, p=2, k=3)
self.assertEqual(set(wnn3e.neighbors[0]), set([1, 5, 6]))
wc = pysal.knnW_from_shapefile(self.polyShp)
self.assertEqual(wc.pct_nonzero, 4.081632653061225)
self.assertEqual(set(wc.neighbors[0]), set([2, 1]))
wc3 = pysal.knnW_from_shapefile(self.polyShp, k=3)
self.assertEqual(wc3.weights[1], [1, 1, 1])
self.assertEqual(set(wc3.neighbors[1]), set([0, 3, 7]))
def test_knnW(self):
x = np.indices((5, 5))
x, y = np.indices((5, 5))
x.shape = (25, 1)
y.shape = (25, 1)
data = np.hstack([x, y])
wnn2 = pysal.knnW(data, k=2)
wnn4 = pysal.knnW(data, k=4)
wnn4.neighbors[0]
self.assertEqual(wnn4.neighbors[0], [1, 5, 6, 2])
self.assertEqual(wnn2.neighbors[5], [0, 6])
self.assertEqual(wnn2.pct_nonzero, 0.080000000000000002)
wnn3e = pysal.knnW(data, p=2, k=3)
self.assertEqual(wnn3e.neighbors[0], [1, 5, 6])
wc = pysal.knnW_from_shapefile(self.polyShp)
self.assertEqual(wc.pct_nonzero, 0.040816326530612242)
self.assertEqual(wc.neighbors[0], [2, 1])
wc3 = pysal.knnW_from_shapefile(self.polyShp, k=3, idVariable="POLYID")
self.assertEqual(wc3.weights[1], [1, 1, 1])
self.assertEqual(wc3.neighbors[1], [3, 2, 4])
def test_knnW(self):
x = np.indices((5, 5))
x, y = np.indices((5, 5))
x.shape = (25, 1)
y.shape = (25, 1)
data = np.hstack([x, y])
wnn2 = pysal.knnW(data, k=2)
wnn4 = pysal.knnW(data, k=4)
wnn4.neighbors[0]
self.assertEqual(wnn4.neighbors[0], [1, 5, 6, 2])
self.assertEqual(wnn2.neighbors[5], [0, 6])
self.assertEqual(wnn2.pct_nonzero, 0.080000000000000002)
wnn3e = pysal.knnW(data, p=2, k=3)
self.assertEqual(wnn3e.neighbors[0], [1, 5, 6])
wc = pysal.knnW_from_shapefile(self.polyShp)
self.assertEqual(wc.pct_nonzero, 0.040816326530612242)
self.assertEqual(wc.neighbors[0], [2, 1])
wc3 = pysal.knnW_from_shapefile(self.polyShp, k=3, idVariable="POLYID")
self.assertEqual(wc3.weights[1], [1, 1, 1])
self.assertEqual(wc3.neighbors[1], [3, 2, 4])
def _distance(arg_dict):
"""
General handler for distance based weights obtained from shapefiles
"""
input1 = arg_dict['input1']
uri = input1['uri']
weight_type = arg_dict['weight_type']
weight_type = weight_type.lower()
k = 2
id_variable = None
p = 2
radius = None
if 'parameters' in arg_dict:
k = arg_dict['parameters'].get('k', k) # set default to 2
id_variable = arg_dict['parameters'].get('id_variable', id_variable)
p = arg_dict['parameters'].get('p', p)
radius = arg_dict['parameters'].get('radius', radius)
else:
parameters = {}
parameters['k'] = 2
parameters['id_variable'] = None
parameters['radius'] = None
parameters['p'] = 2
arg_dict['parameters'] = parameters
if weight_type == 'knn':
w = ps.knnW_from_shapefile(uri,
k=k,
p=p,
idVariable=id_variable,
radius=radius)
w = WMD(w.neighbors, w.weights)
w.meta_data = {}
w.meta_data["input1"] = {"type": 'shp', 'uri': uri}
w.meta_data["weight_type"] = 'knn'
w.meta_data["transform"] = w.transform
w.meta_data['parameters'] = arg_dict['parameters']
return w
def replace_empty_neighbours_with_KNN(data_countries, w):
shapefile = SHAPEFILE
no_neighbors_idx = w.islands
knn = 10
wknn = pysal.knnW_from_shapefile(shapefile, knn)
knn_countries = get_countries_from_shapefile(shapefile)
neighbors = w.neighbors
for nn_idx in no_neighbors_idx:
country = data_countries[nn_idx]
print country
if country not in knn_countries:
continue
knn_country_idx = knn_countries.index(country)
knn_country_neighbors = [
knn_countries[nn] for nn in wknn.neighbors[knn_country_idx]
]
for knn_nn in knn_country_neighbors:
if len(neighbors[nn_idx]) > 2:
continue
data_country_idx = np.where(data_countries == knn_nn)[0]
if len(data_country_idx) > 0:
neighbors[nn_idx][data_country_idx[0]] = 1.0
w = pysal.weights.W(neighbors, id_order=range(len(data_countries)))
return w
def _distance(arg_dict):
"""
General handler for distance based weights obtained from shapefiles
"""
input1 = arg_dict['input1']
uri = input1['uri']
weight_type = arg_dict['weight_type']
weight_type = weight_type.lower()
k = 2
id_variable = None
p = 2
radius = None
if 'parameters' in arg_dict:
k = arg_dict['parameters'].get('k',k) # set default to 2
id_variable = arg_dict['parameters'].get('id_variable', id_variable)
p = arg_dict['parameters'].get('p',p)
radius = arg_dict['parameters'].get('radius', radius)
else:
parameters = {}
parameters['k'] = 2
parameters['id_variable'] = None
parameters['radius'] = None
parameters['p'] = 2
arg_dict['parameters'] = parameters
if weight_type == 'knn':
w = ps.knnW_from_shapefile(uri,k=k,p=p,idVariable=id_variable,
radius=radius)
w = WMD(w.neighbors, w.weights)
w.meta_data = {}
w.meta_data["input1"] = {"type": 'shp', 'uri':uri}
w.meta_data["weight_type"] = 'knn'
w.meta_data["transform"] = w.transform
w.meta_data['parameters'] = arg_dict['parameters']
return w
print("time elapsed for rook... using bins: " + str(t1 - t0))
from pysal.weights._contW_rtree import ContiguityWeights_rtree
t0 = time.time()
rt = ContiguityWeights_rtree(pysal.open(fname), ROOK)
t1 = time.time()
print("time elapsed for rook... using rtree: " + str(t1 - t0))
print(rt.w == rb.w)
print('QUEEN')
t0 = time.time()
qt = ContiguityWeights_rtree(pysal.open(fname), QUEEN)
t1 = time.time()
print("using " + str(fname))
print("time elapsed for queen... using rtree: " + str(t1 - t0))
print(qb.w == qt.w)
print('knn4')
t0 = time.time()
knn = pysal.knnW_from_shapefile(fname, k=4)
t1 = time.time()
print(t1 - t0)
print('rook from shapefile')
t0 = time.time()
knn = pysal.rook_from_shapefile(fname)
t1 = time.time()
print(t1 - t0)
def run_distance(self, sfile, var):
""" Invoked by main run method. """
if self.model.shapes.type == pysal.cg.Polygon:
self.warn("The selected shapefile contains polygons and distance \
weights can only be computed on points. " +
"The centroids of the specified polygons will be used \
instead.")
elif self.model.shapes.type != pysal.cg.Point:
return self.warn("The selected shapefile does not contain points \
and contiguity weights can only be computed \
on points.")
if self.model.distMethod == 0:
radius = None
elif self.model.distMethod == 1: # 'Arc Distance (miles)'
radius = pysal.cg.RADIUS_EARTH_MILES
elif self.model.distMethod == 2: # 'Arc Distance (kilometers)'
radius = pysal.cg.RADIUS_EARTH_KM
if self.ThresholdRadio.GetValue():
try:
cutoff = float(self.CutoffText.GetValue())
except:
return self.warn("The cut-off point is not valid.")
print "Threshold on %s, ids=%r, cutoff=%f" % (sfile, var, cutoff)
W = pysal.threshold_binaryW_from_shapefile(
sfile, cutoff, idVariable=var, radius=radius)
W.meta = {'shape file': sfile,
'id variable': var,
'method': 'distance',
'method options': ['Threshold', cutoff]}
if radius:
W.meta['Sphere Radius'] = radius
self.SetW(W)
elif self.KnnRadio.GetValue():
k = int(self.NumNeighSpin.GetValue())
print "Knn on %s, ids=%r, k=%d" % (sfile, var, k)
W = pysal.knnW_from_shapefile(
sfile, k=k, idVariable=var, radius=radius)
W.meta = {'shape file': sfile,
'id variable': var,
'method': 'distance',
'method options': ['KNN', k]}
if radius:
W.meta['Sphere Radius'] = radius
self.SetW(W)
elif self.InverseRadio.GetValue():
try:
cutoff = float(self.CutoffText2.GetValue())
except:
return self.warn("The cut-off point is not valid.")
power = int(self.PowerSpin.GetValue())
print "Inverse on %s, ids=%r, cutoff=%f, power=%d" % \
(sfile, var, cutoff, power)
try:
W = pysal.threshold_continuousW_from_shapefile(
sfile, cutoff, alpha=- 1 * power,
idVariable=var, radius=radius)
W.meta = {'shape file': sfile,
'id variable': var,
'method': 'distance',
'method options': ['Inverse', cutoff, power]}
if radius:
W.meta['Sphere Radius'] = radius
self.SetW(W)
except Exception:
et, e, tb = sys.exc_info()
d = wx.MessageDialog(self, "\"%s\"\n"
% str(e), "Error", wx.OK | wx.ICON_ERROR)
d.ShowModal()
ds = ps.open(name_ds, 'r')
print(list(enumerate(ds.header)))
logger.info('Dataset = ' + name_ds)
logger.info('Shapefile = ' + shapefile)
x = np.zeros((len(ds), 1))
for i, c in enumerate(x_columns):
data = ds.by_col(ds.header[c])
data = list(map(float, data))
data = np.array(data).reshape(len(ds), 1)
logger.info('Variable #{} :'.format(i + 1) + ds.header[c])
x = np.hstack((x, data))
x = x[:, 1:]
# Weights, row-standarsized
w = ps.knnW_from_shapefile(shapefile, k=4, idVariable=None)
w.transform = 'r'
name_w = shapefile.split('/')[-1]
# Kernel-weights
kw = ps.adaptive_kernelW_from_shapefile(shapefile, k=12, idVariable=None)
for name_y in names_y:
y = ds.by_col(name_y)
y = list(map(float, y))
y = np.array(y).reshape(len(ds), 1)
logger.info('y = ' + name_y)
## For Spatial Lag Model -- Maximum Likelihood
logger.info('Method = Spatial Lag Model -- Maximum Likelihood')
ml_lag = ps.spreg.ML_Lag(y,
x,
def generate_matrix(self):
if self.dlg.txtOutput.text()=='':
QtGui.QMessageBox.warning(None,"Error","Oops! Generate weight matrix. Try again...")
else:
filenamein=self.myfile
filename = self.dlg.txtOutput.text()
self.filename=filename
ext=filename[-3:]
"""matrix"""
if self.dlg.rdButtonContW.isChecked()==True:
if self.dlg.rdButtonContWQ.isChecked()==True:
w = pysal.queen_from_shapefile(filenamein,idVariable=None)
if ext=='gal':
output_file = pysal.open(filename,'w')
output_file.write(w)
else:
output_file = pysal.open(filename,'w','arcgis_dbf')
output_file.write(w, useIdIndex=True)
output_file.close()
if self.dlg.rdButtonContWR.isChecked()==True:
w = pysal.rook_from_shapefile(filenamein,idVariable=None)
if ext=='gal':
output_file = pysal.open(filename,'w')
output_file.write(w)
else:
output_file = pysal.open(filename,'w','arcgis_dbf')
output_file.write(w, useIdIndex=True)
output_file.close()
if self.dlg.rdButtonContWB.isChecked()==True:
wr = pysal.rook_from_shapefile(filenamein,idVariable=None)
wq = pysal.queen_from_shapefile(filenamein,idVariable=None)
wb = pysal.w_difference(wq, wr,constrained = False)
if ext=='gal':
output_file = pysal.open(filename,'w')
output_file.write(wb)
else:
output_file = pysal.open(filename,'w','arcgis_dbf')
output_file.write(wb, useIdIndex=True)
output_file.close()
if self.dlg.rdButtonDisW.isChecked()==True:
w = pysal.threshold_binaryW_from_shapefile(filenamein, float(self.dlg.txtThresh.text()))
if ext=='gal':
output_file = pysal.open(filename,'w')
output_file.write(w)
else:
output_file = pysal.open(filename,'w','arcgis_dbf')
output_file.write(w, useIdIndex=True)
output_file.close()
if self.dlg.rdButtonKNW.isChecked()==True:
w = pysal.knnW_from_shapefile(filenamein, k=self.dlg.spinBox.value())
if ext=='gal':
output_file = pysal.open(filename,'w')
output_file.write(w)
else:
output_file = pysal.open(filename,'w','arcgis_dbf')
output_file.write(w, useIdIndex=True)
output_file.close()
"""end matrix"""
QtGui.QMessageBox.warning(None,"Complete","Weight matrix is generated")
data = list(map(float, data))
data = np.array(data).reshape(len(db), 1)
if log_variables[c]:
data = np.log(data)
print('Variable #{} :'.format(i+1), 'log({})'.format(db.header[c]))
else:
print('Variable #{} :'.format(i+1), db.header[c])
x = np.hstack((x, data))
x = x[:, 1:]
logfile = open('Results.log', 'a')
# Weights, row-standarsized
w = ps.knnW_from_shapefile('Listings shp/Tract_With_Airbnb.shp', k=4, idVariable=None)
w.transform = 'r'
# Kernel-weights
kw = ps.adaptive_kernelW_from_shapefile('Listings shp/Tract_With_Airbnb.shp', k=12, idVariable=None)
## For OLS + White-test + Spatial Diagnostics
ols_spat = ps.spreg.OLS(y, x, w=w, robust=None, gwk=kw, sig2n_k=True, nonspat_diag=False, spat_diag=True, moran=True, white_test=True, vm=False, name_y=None, name_x=None, name_w=None, name_gwk=None, name_ds=None)
#print(ols_spat.summary)
#logfile.write('\n'*2 + ols_spat.summary + '\n'*2)
logfile.close()
## Langrange Multiplier error and lag values.
vw = ps.spreg.diagnostics_sp.LMtests(ols_spat, w)
print(vw)
def run(self):
"""Run method that performs all the real work""" # show the dialog
self.clear_ui()
layers, layers_shp = self.loadLayerList()
if len(layers) == 0:
return
self.dlg.show()
self.load_comboBox()
# Run the dialog event loop
result = self.dlg.exec_()
# See if OK was pressed and fields are not empty
if result and (self.validator() == 1):
selectedLayerIndex = self.dlg.comboBox.currentIndex()
if selectedLayerIndex < 0 or selectedLayerIndex > len(layers):
return
selectedLayer = layers_shp[selectedLayerIndex]
layerName = selectedLayer.dataProvider().dataSourceUri()
C = selectedLayer.fieldNameIndex(self.dlg.comboBox_C.currentText())
C2 = selectedLayer.fieldNameIndex(
self.dlg.comboBox_C_2.currentText())
filename = self.dlg.lineEdit.text()
(path, layer_id) = layerName.split('|')
inDriver = ogr.GetDriverByName("ESRI Shapefile")
inDataSource = inDriver.Open(path, 0)
inLayer = inDataSource.GetLayer()
type = inLayer.GetLayerDefn().GetGeomType()
u = []
for i in range(0, inLayer.GetFeatureCount()):
geometry = inLayer.GetFeature(i)
u.append(geometry.GetField(C))
y = numpy.array(u) # attributes vector
if self.dlg.checkBox_moranBi.isChecked() == 1:
v = []
for i in range(0, inLayer.GetFeatureCount()):
geometry = inLayer.GetFeature(i)
v.append(geometry.GetField(C2))
x = numpy.array(v)
if type == 1: # point
t = ()
for feature in inLayer:
geometry = feature.GetGeometryRef()
xy = (geometry.GetX(), geometry.GetY())
t = t + (xy, )
# t = get_points_array_from_shapefile(layerName.split("|")[0])
if self.dlg.lineEditThreshold.text(
) and self.dlg.lineEditThreshold.text(
) != "": # if threshold is given
threshold1 = int(self.dlg.lineEditThreshold.text())
elif self.dlg.checkBox_knn.isChecked(
) == 0: # if user needs to optimize threshold (no knn)
mx_moran = -1000.0
mx_i = -1000.0
minT = int(self.dlg.lineEdit_minT.text())
maxT = int(self.dlg.lineEdit_maxT.text())
dist = int(self.dlg.lineEdit_dist.text())
for i in range(minT, maxT + dist, dist):
w = DistanceBand(t, threshold=i, p=2, binary=False)
moran = pysal.Moran(y, w)
# print moran.z_norm
if moran.z_norm > mx_moran:
mx_i = i
mx_moran = moran.z_norm
threshold1 = int(mx_i)
if self.dlg.checkBox_knn.isChecked() == 1:
weightValue = int(self.dlg.knn_number.text())
w = pysal.knnW_from_shapefile(layerName.split("|")[0],
k=weightValue,
p=1)
threshold1 = "None/KNN used " + self.dlg.knn_number.text()
else:
w = DistanceBand(t, threshold1, p=2, binary=False)
else: # polygon
w = pysal.queen_from_shapefile(layerName.split("|")[0])
threshold1 = "None/Queen's Case used"
if self.dlg.checkBox_rowStandard.isChecked() == 1:
type_w = "R"
else:
type_w = "B"
if self.dlg.checkBox_randomPerm.isChecked() == 1:
permutationsValue = int(self.dlg.lineEdit_random.text())
else:
permutationsValue = 999
numpy.random.seed(12345)
if self.dlg.checkBox_gi.isChecked() == 1:
statistics = G_Local(y,
w,
star=True,
transform=type_w,
permutations=permutationsValue)
elif self.dlg.checkBox_moran.isChecked() == 1:
statistics = Moran_Local(y,
w,
transformation=type_w,
permutations=permutationsValue)
else:
statistics = Moran_Local_BV(y,
x,
w,
transformation=type_w,
permutations=permutationsValue)
self.write_file(filename, statistics, layerName, inLayer,
inDataSource, y, threshold1)
# assign the style to the output layer on QGIS
if self.dlg.checkBox_gi.isChecked() == 1:
if type == 1: # point
stylePath = "/layer_style/hotspots_class.qml"
else:
stylePath = "/layer_style/hotspots_class_poly.qml"
self.iface.activeLayer().loadNamedStyle(
os.path.dirname(__file__) + stylePath)
else:
if type == 1: # point
stylePath = "/layer_style/moran_class.qml"
else:
stylePath = "/layer_style/moran_class_poly.qml"
self.iface.activeLayer().loadNamedStyle(
os.path.dirname(__file__) + stylePath)
elif result and (self.validator() == 0):
self.error_msg()
else:
self.clear_ui()
pass
rcParams['figure.figsize'] = 8, 6
pd.set_option('display.max_rows', 500)
get_ipython().magic(u'matplotlib inline')
# In[ ]:
data = pd.read_csv('food_geo3.csv')
data.head()
# In[ ]:
#setting the weight matrix for spatial autocorrelation
#using k-nearest neighbors-3,5,and9
w_knn3 = ps.knnW_from_shapefile(('newer_polys.shp'), k=3, idVariable='CAMIS')
w_knn5 = ps.knnW_from_shapefile(('newer_polys.shp'), k=5, idVariable='CAMIS')
w_knn9 = ps.knnW_from_shapefile(('newer_polys.shp'), k=9, idVariable='CAMIS')
# In[ ]:
#normalize the dependent variable
Y = data.SCORE.values
Y = (Y-Y.mean())/Y.std()
print Y.shape
# In[ ]:
# Now we would like to standardize all the weights. This can be
def run(self):
"""Run method that performs all the real work""" # show the dialog
self.clear_ui()
layers, layers_shp = self.loadLayerList()
if len(layers) == 0:
return
self.dlg.show()
self.load_comboBox()
# Run the dialog event loop
result = self.dlg.exec_()
# See if OK was pressed and fields are not empty
if result and (self.validator() == 1):
selectedLayerIndex = self.dlg.comboBox.currentIndex()
if selectedLayerIndex < 0 or selectedLayerIndex > len(layers):
return
selectedLayer = layers_shp[selectedLayerIndex]
layerName = selectedLayer.dataProvider().dataSourceUri()
C = selectedLayer.fieldNameIndex(self.dlg.comboBox_C.currentText())
C2 = selectedLayer.fieldNameIndex(self.dlg.comboBox_C_2.currentText())
filename = self.dlg.lineEdit.text()
(path, layer_id) = layerName.split('|')
inDriver = ogr.GetDriverByName("ESRI Shapefile")
inDataSource = inDriver.Open(path, 0)
inLayer = inDataSource.GetLayer()
type = inLayer.GetLayerDefn().GetGeomType()
u = []
for i in range(0, inLayer.GetFeatureCount()):
geometry = inLayer.GetFeature(i)
u.append(geometry.GetField(C))
y = numpy.array(u) # attributes vector
if self.dlg.checkBox_moranBi.isChecked() == 1:
v = []
for i in range(0, inLayer.GetFeatureCount()):
geometry = inLayer.GetFeature(i)
v.append(geometry.GetField(C2))
x = numpy.array(v)
if type == 1: # point
t = ()
for feature in inLayer:
geometry = feature.GetGeometryRef()
xy = (geometry.GetX(), geometry.GetY())
t = t + (xy,)
# t = get_points_array_from_shapefile(layerName.split("|")[0])
if self.dlg.lineEditThreshold.text() and self.dlg.lineEditThreshold.text() != "": # if threshold is given
threshold1 = int(self.dlg.lineEditThreshold.text())
elif self.dlg.checkBox_knn.isChecked() == 0: # if user needs to optimize threshold (no knn)
mx_moran = -1000.0
mx_i = -1000.0
minT = int(self.dlg.lineEdit_minT.text())
maxT = int(self.dlg.lineEdit_maxT.text())
dist = int(self.dlg.lineEdit_dist.text())
for i in range(minT, maxT + dist, dist):
w = DistanceBand(t, threshold=i, p=2, binary=False)
moran = pysal.Moran(y, w)
# print moran.z_norm
if moran.z_norm > mx_moran:
mx_i = i
mx_moran = moran.z_norm
threshold1 = int(mx_i)
if self.dlg.checkBox_knn.isChecked() == 1:
weightValue = int(self.dlg.knn_number.text())
w = pysal.knnW_from_shapefile(layerName.split("|")[0], k=weightValue, p=1)
threshold1 = "None/KNN used " + self.dlg.knn_number.text()
else:
w = DistanceBand(t, threshold1, p=2, binary=False)
else: # polygon
w = pysal.queen_from_shapefile(layerName.split("|")[0])
threshold1 = "None/Queen's Case used"
if self.dlg.checkBox_rowStandard.isChecked() == 1:
type_w = "R"
else:
type_w = "B"
if self.dlg.checkBox_randomPerm.isChecked() == 1:
permutationsValue = int(self.dlg.lineEdit_random.text())
else:
permutationsValue = 999
numpy.random.seed(12345)
if self.dlg.checkBox_gi.isChecked() == 1:
statistics = G_Local(y, w, star=True, transform=type_w, permutations=permutationsValue)
elif self.dlg.checkBox_moran.isChecked() == 1:
statistics = Moran_Local(y, w, transformation=type_w, permutations=permutationsValue)
else:
statistics = Moran_Local_BV(y, x, w, transformation=type_w, permutations=permutationsValue)
self.write_file(filename, statistics, layerName, inLayer,
inDataSource,
y, threshold1)
# assign the style to the output layer on QGIS
if self.dlg.checkBox_gi.isChecked() == 1:
if type == 1: # point
stylePath = "/layer_style/hotspots_class.qml"
else:
stylePath = "/layer_style/hotspots_class_poly.qml"
self.iface.activeLayer().loadNamedStyle(os.path.dirname(__file__) + stylePath)
else:
if type == 1: # point
stylePath = "/layer_style/moran_class.qml"
else:
stylePath = "/layer_style/moran_class_poly.qml"
self.iface.activeLayer().loadNamedStyle(os.path.dirname(__file__) + stylePath)
elif result and (self.validator() == 0):
self.error_msg()
else:
self.clear_ui()
pass
def run_distance(self, sfile, var):
""" Invoked by main run method. """
if self.model.shapes.type == pysal.cg.Polygon:
self.warn("The selected shapefile contains polygons and distance \
weights can only be computed on points. " +
"The centroids of the specified polygons will be used \
instead.")
elif self.model.shapes.type != pysal.cg.Point:
return self.warn("The selected shapefile does not contain points \
and contiguity weights can only be computed \
on points.")
if self.model.distMethod == 0:
radius = None
elif self.model.distMethod == 1: # 'Arc Distance (miles)'
radius = pysal.cg.RADIUS_EARTH_MILES
elif self.model.distMethod == 2: # 'Arc Distance (kilometers)'
radius = pysal.cg.RADIUS_EARTH_KM
if self.ThresholdRadio.GetValue():
try:
cutoff = float(self.CutoffText.GetValue())
except:
return self.warn("The cut-off point is not valid.")
print "Threshold on %s, ids=%r, cutoff=%f" % (sfile, var, cutoff)
W = pysal.threshold_binaryW_from_shapefile(sfile,
cutoff,
idVariable=var,
radius=radius)
W.meta = {
'shape file': sfile,
'id variable': var,
'method': 'distance',
'method options': ['Threshold', cutoff]
}
if radius:
W.meta['Sphere Radius'] = radius
self.SetW(W)
elif self.KnnRadio.GetValue():
k = int(self.NumNeighSpin.GetValue())
print "Knn on %s, ids=%r, k=%d" % (sfile, var, k)
W = pysal.knnW_from_shapefile(sfile,
k=k,
idVariable=var,
radius=radius)
W.meta = {
'shape file': sfile,
'id variable': var,
'method': 'distance',
'method options': ['KNN', k]
}
if radius:
W.meta['Sphere Radius'] = radius
self.SetW(W)
elif self.InverseRadio.GetValue():
try:
cutoff = float(self.CutoffText2.GetValue())
except:
return self.warn("The cut-off point is not valid.")
power = int(self.PowerSpin.GetValue())
print "Inverse on %s, ids=%r, cutoff=%f, power=%d" % \
(sfile, var, cutoff, power)
try:
W = pysal.threshold_continuousW_from_shapefile(sfile,
cutoff,
alpha=-1 *
power,
idVariable=var,
radius=radius)
W.meta = {
'shape file': sfile,
'id variable': var,
'method': 'distance',
'method options': ['Inverse', cutoff, power]
}
if radius:
W.meta['Sphere Radius'] = radius
self.SetW(W)
except Exception:
et, e, tb = sys.exc_info()
d = wx.MessageDialog(self, "\"%s\"\n" % str(e), "Error",
wx.OK | wx.ICON_ERROR)
d.ShowModal()
