def GetNeighborhood(self, centralFeature):
centralPnt = centralFeature.geometry().asPoint()
# In a first step get the nearest points inside a rectangle
# to limit the search loop
halfDistance = self.GetCharacteristicDistance() / 1.4
min_X = centralPnt.x() - halfDistance
max_X = centralPnt.x() + halfDistance
min_Y = centralPnt.y() - halfDistance
max_Y = centralPnt.y() + halfDistance
# select features inside a rectangle : to restrict the search loop
self.gstaLayer.select(QgsRectangle(min_X, min_Y, max_X, max_Y), False)
# Return an empty list if no point on the layer
if self.gstaLayer.selectedFeatureCount() == 0:
return []
# Initialisation of the list returned
neighborList = []
# loop over the selected features to construct the neighborhood list
for f in processing.features(self.gstaLayer):
geomF = f.geometry()
if self.GetAnisotropy() == True:
# Construction of the ellipse to take into account anisotropy
ellipse = self.MakeEllipse(centralPnt, self.GetCharacteristicDistance(), self.GetTolerance(), self.GetDirection())
if not ellipse:
return []
if geomF.asPoint() != centralPnt and ellipse.geometry().contains(geomF):
if len(self.GetBarrierLayerList()) > 0:
line = QgsFeature()
line.setGeometry(QgsGeometry.fromPolyline([geomF.asPoint(),centralFeature.geometry().asPoint()])) # construct segment
for layer in self.GetBarrierLayerList():
cross = False
for feature in processing.features(layer):
if line.geometry().crosses(feature.geometry()):
cross = True
if not cross:
neighborList.append(f)
else:
neighborList.append(f)
else:
distance = geomF.distance(centralFeature.geometry())
if distance <= self.GetCharacteristicDistance() and distance > 0.0:
if len(self.GetBarrierLayerList()) > 0:
line = QgsFeature()
line.setGeometry(QgsGeometry.fromPolyline([geomF.asPoint(),centralFeature.geometry().asPoint()])) # construct segment
for layer in self.GetBarrierLayerList():
cross = False
for feature in processing.features(layer):
if line.geometry().crosses(feature.geometry()):
cross = True
if not cross:
neighborList.append(f)
else:
neighborList.append(f)
self.gstaLayer.removeSelection()
return neighborList
def test_SagaVectorAlgorithmWithSelection(self):
layer = processing.getObject(polygons2())
feature = layer.getFeatures().next()
selected = [feature.id()]
layer.setSelectedFeatures(selected)
outputs = processing.runalg('saga:polygoncentroids', polygons2(),
True, None)
layer.setSelectedFeatures([])
output = outputs['CENTROIDS']
layer = dataobjects.getObjectFromUri(output, True)
fields = layer.pendingFields()
expectednames = ['ID', 'POLY_NUM_B', 'POLY_ST_B']
expectedtypes = ['Real', 'Real', 'String']
names = [unicode(f.name()) for f in fields]
types = [unicode(f.typeName()) for f in fields]
self.assertEqual(expectednames, names)
self.assertEqual(expectedtypes, types)
features = processing.features(layer)
self.assertEqual(1, len(features))
feature = features.next()
attrs = feature.attributes()
expectedvalues = ['2', '1', 'string a']
values = [unicode(attr) for attr in attrs]
self.assertEqual(expectedvalues, values)
wkt = 'POINT(270806.69221918 4458924.97720492)'
self.assertEqual(wkt, unicode(feature.geometry().exportToWkt()))
def getVectorLayerFieldValues(self,vectorLayer, fieldName):
"""
purpose:
return all field values for vector layer using qgis processing conveince function
notes:
takes into account feature selection
returns:
tuple of (message, list of values, boolean status)
"""
# convert attribute name to qgis object using processing convience method
inputLayer = processing.getObject(vectorLayer)
# convert attribute name to qgis object using processing convience method
values = []
# get index of polygon id
idx = inputLayer.fieldNameIndex(fieldName)
# get list of features. takes into account spatial selection
iter = processing.features(inputLayer)
# iterate over each feature and get attribute value wanted
for feature in iter:
values.append(feature.attributes()[idx])
# check values present
if len(values) == 0:
return ("no values for vector layer fieldname provided", None, False)
else:
return ("values present", values, True)
def test_SagaVectorAlgorithmWithSelection(self):
layer = processing.getObject(polygons2());
feature = layer.getFeatures().next()
selected = [feature.id()]
layer.setSelectedFeatures(selected)
outputs=processing.runalg("saga:polygoncentroids",polygons2(),True,None)
layer.setSelectedFeatures([])
output=outputs['CENTROIDS']
layer=dataobjects.getObjectFromUri(output, True)
fields=layer.pendingFields()
expectednames=['ID','POLY_NUM_B','POLY_ST_B']
expectedtypes=['Real','Real','String']
names=[str(f.name()) for f in fields]
types=[str(f.typeName()) for f in fields]
self.assertEqual(expectednames, names)
self.assertEqual(expectedtypes, types)
features=processing.features(layer)
self.assertEqual(1, len(features))
feature=features.next()
attrs=feature.attributes()
expectedvalues=["2","1","string a"]
values=[str(attr) for attr in attrs]
self.assertEqual(expectedvalues, values)
wkt='POINT(270806.69221918 4458924.97720492)'
self.assertEqual(wkt, str(feature.geometry().exportToWkt()))
def test_SagaVectorAlgorithWithUnsupportedInputAndOutputFormat(self):
"""This tests both the exporting to shp and then the format
change in the output layer.
"""
layer = processing.getObject(polygonsGeoJson())
feature = layer.getFeatures().next()
selected = [feature.id()]
layer.setSelectedFeatures(selected)
outputs = processing.runalg('saga:polygoncentroids',
polygonsGeoJson(), True,
getTempFilename('geojson'))
layer.setSelectedFeatures([])
output = outputs['CENTROIDS']
layer = dataobjects.getObjectFromUri(output, True)
fields = layer.pendingFields()
expectednames = ['ID', 'POLY_NUM_A', 'POLY_ST_A']
expectedtypes = ['Real', 'Real', 'String']
names = [unicode(f.name()) for f in fields]
types = [unicode(f.typeName()) for f in fields]
self.assertEqual(expectednames, names)
self.assertEqual(expectedtypes, types)
features = processing.features(layer)
self.assertEqual(1, len(features))
feature = features.next()
attrs = feature.attributes()
expectedvalues = ['0', '1.1', 'string a']
values = [unicode(attr) for attr in attrs]
self.assertEqual(expectedvalues, values)
wkt = 'POINT(270787.49991451 4458955.46775295)'
self.assertEqual(wkt, unicode(feature.geometry().exportToWkt()))
def create_lvl_copies(input_shp="DEFAULT",height_attr="height"):
"""
creates zoom level dependent copies of 10 m spaced contour lines
scale factor = {zoom-level : isoline spacing in m}
used on selected layer
"""
scale_factor = {9:500,10:200,11:100,12:50,13:20}
if input_shp == "DEFAULT":
layer = iface.mapCanvas().currentLayer()
height_attr = "height"
features = processing.features(layer)
for level in range(9,14):
export_features_per_lvl = []
for feature in features:
# can be divided by spacing -> must be contained in the dataset
# change back to height
if ((feature[height_attr] % scale_factor[level]) == 0):
export_features_per_lvl.append(feature.id())
print "selecting following ids:",len(export_features_per_lvl)
print "current level is: "+str(level)+"; added feature: "+str(feature.id())+" with height: "+str(feature[height_attr])
# select features that contain the specified criteria
print "selecting following ids:",len(export_features_per_lvl)
layer.setSelectedFeatures(export_features_per_lvl)
# write down selected features
basepath= iface.activeLayer().dataProvider().dataSourceUri()
new_file = basepath[:-4]+"-level"+str(level)+".shp"
# boolean 1 at the end saves only selected features
error = QgsVectorFileWriter.writeAsVectorFormat(layer, new_file, "utf-8", None, "ESRI Shapefile", 1)
if error == QgsVectorFileWriter.NoError:
print "Exported: ",new_file
def calculateFields(listStats, output):
# iterates over input layer features to get attributes as a list of lists
# uses the processing method so as to get only selected features if this option is set in the processing options
iter = processing.features(inputLayer)
attrs = [feature.attributes() for feature in iter]
# get index of dissolve field
provider = inputLayer.dataProvider()
fields = provider.fields()
listFieldNames = [field.name() for field in fields]
indexDissolveField = listFieldNames.index(Dissolve_field)
# get all values of the dissolve field (before processing : with duplicate values)
valuesDissolveField = [feature[indexDissolveField] for feature in attrs]
# get unique values for dissolve field, from output (seems more secure than to get it from valuesDissolveField ?)
outputLayer = QgsVectorLayer(output, "name", "ogr")
provider = dissolveLayer.dataProvider()
fields = provider.fields()
listFieldNames = [field.name() for field in fields]
iter = outputLayer.getFeatures()
uniqueValuesDissolveField = [feature.attributes()[indexDissolveField] for feature in iter]
# initializes list of lists which will contain results (it will have one element per kept field)
listRes = []
# for each kept field
for i in range(len(listFieldNames)):
if listStats[i] != 'no':
# creates list which will contain attribute values for current field, one empty element per unique dissolve field value
listAttrs = [[] for val in range(len(uniqueValuesDissolveField))]
# fill this list with all the current field values corresponding to each dissolve field value
valuesField = [feature[i] for feature in attrs]
for (x,y) in zip(valuesDissolveField, valuesField):
listAttrs[uniqueValuesDissolveField.index(x)].append(y)
# removes any NULL values
listAttrs = [[x for x in l if x] for l in listAttrs]
# for each list in listAttrs, calculates one value according to the chosen stat
# if list is empty (can happen if it contained originally only NULL values), return NULL as a result
if listStats[i] == "mean":
listAttrs = [sum(y) / len(y) if y else NULL for y in listAttrs]
elif listStats[i] == "sum":
listAttrs = [sum(y) if y else NULL for y in listAttrs]
elif listStats[i] == "min":
listAttrs = [min(y) if y else NULL for y in listAttrs]
elif listStats[i] == "max":
listAttrs = [max(y) if y else NULL for y in listAttrs]
elif listStats[i] == "count":
listAttrs = [len(y) if y else NULL for y in listAttrs]
elif listStats[i] == "first":
listAttrs = [y[0] if y else NULL for y in listAttrs]
elif listStats[i] == "last":
listAttrs = [y[-1] if y else NULL for y in listAttrs]
elif listStats[i] == "median":
listAttrs = [self.median(y) if y else NULL for y in listAttrs]
elif listStats[i] == "sd":
listAttrs = [self.standard_dev(y) if y else NULL for y in listAttrs]
elif listStats[i] == "concat":
listAttrs = [", ".join(y) if y else NULL for y in listAttrs]
elif listStats[i] == "unique":
listAttrs = [", ".join(set(y)) if y else NULL for y in listAttrs]
# append each field result to listRes
listRes.append(listAttrs)
return listRes
def test_featuresWithSelection(self):
layer = processing.getObject(points())
feature = layer.getFeatures().next()
selected = [feature.id()]
layer.setSelectedFeatures(selected)
features = processing.features(layer)
self.assertEqual(1, len(features))
layer.setSelectedFeatures([])
def test_featuresWithSelection(self):
layer = processing.getObject(points())
feature = layer.getFeatures().next()
selected = [feature.id()]
layer.setSelectedFeatures(selected)
features = processing.features(layer)
self.assertEqual(1, len(features))
layer.setSelectedFeatures([])
def processAlgorithm(self, progress):
field = self.getParameterValue(self.FIELD)
field = field[0:10] # try to handle Shapefile field length limit
filename = self.getParameterValue(self.INPUT)
layer = dataobjects.getObjectFromUri(filename)
filename = dataobjects.exportVectorLayer(layer)
provider = layer.dataProvider()
fields = provider.fields()
fields.append(QgsField('L_G', QVariant.Double))
fields.append(QgsField('L_G_p', QVariant.Double))
fields.append(QgsField('L_G_S', QVariant.Int))
fields.append(QgsField('L_G_ll_hh', QVariant.Int))
writer = self.getOutputFromName(self.OUTPUT).getVectorWriter(
fields, provider.geometryType(), layer.crs() )
contiguity = self.getParameterValue(self.CONTIGUITY)
if self.CONTIGUITY_OPTIONS[contiguity] == 'queen':
print 'INFO: Local G and G* using queen contiguity'
w = pysal.queen_from_shapefile(filename)
elif self.CONTIGUITY_OPTIONS[contiguity] == 'rook':
print 'INFO: Local G and G* using rook contiguity'
w = pysal.rook_from_shapefile(filename)
significance_level = self.getParameterValue(self.SIGNIFICANCE_LEVEL)
if self.SIGNIFICANCE_OPTIONS[significance_level] == '90%':
max_p = 0.10
elif self.SIGNIFICANCE_OPTIONS[significance_level] == '95%':
max_p = 0.05
elif self.SIGNIFICANCE_OPTIONS[significance_level] == '99%':
max_p = 0.01
print 'INFO: significance level ' + self.SIGNIFICANCE_OPTIONS[significance_level]
f = pysal.open(pysal.examples.get_path(filename.replace('.shp','.dbf')))
y = np.array(f.by_col[str(field)])
lg = pysal.G_Local(y,w,transform = "b", permutations = 999)
sig_g = 1.0 * lg.p_sim <= max_p
ll_hh = 1.0 * (lg.Gs > lg.EGs) + 1
sig_ll_hh = sig_g * ll_hh
outFeat = QgsFeature()
i = 0
for inFeat in processing.features(layer):
inGeom = inFeat.geometry()
outFeat.setGeometry(inGeom)
attrs = inFeat.attributes()
attrs.append(float(lg.Gs[i]))
attrs.append(float(lg.p_sim[i]))
attrs.append(int(sig_g[i]))
attrs.append(int(sig_ll_hh[i]))
outFeat.setAttributes(attrs)
writer.addFeature(outFeat)
i+=1
del writer
def geocode(self):
self.dlg.pushButton.setDisabled( True )
print "Geocode"
layer = self.dlg.mMapLayerComboBox.currentLayer()
layer_field_index = layer.fieldNameIndex(self.dlg.mFieldComboBox.currentField())
# prepare
features = processing.features(layer)
count = 0
total = 0
for f in features:
total +=1
features = processing.features(layer)
for f in features:
count += 1
self.dlg.progressBar.setValue(int(100 * total / count))
print int(100 * count / total)
def test_simplification(self):
outputs = processing.runalg('schematizationprovider:topologypreservingsimplifier', lines(), '2000', None)
output = outputs['OUTPUT']
layer = dataobjects.getObjectFromUri(output, True)
fields = layer.pendingFields()
expectednames = ['ID', 'LINE_NUM_A', 'LINE_ST_A']
names = [str(f.name()) for f in fields]
self.assertEqual(expectednames, names)
features = processing.features(layer)
self.assertEqual(5, len(features))
feature = features.next()
attrs = feature.attributes()
expectedvalues = ['NULL', 'NULL', 'NULL']
values = [str(attr) for attr in attrs]
self.assertEqual(expectedvalues, values)
def test_simplification(self):
outputs = processing.runalg(
'schematizationprovider:topologypreservingsimplifier', lines(),
'2000', None)
output = outputs['OUTPUT']
layer = dataobjects.getObjectFromUri(output, True)
fields = layer.pendingFields()
expectednames = ['ID', 'LINE_NUM_A', 'LINE_ST_A']
names = [str(f.name()) for f in fields]
self.assertEqual(expectednames, names)
features = processing.features(layer)
self.assertEqual(5, len(features))
feature = features.next()
attrs = feature.attributes()
expectedvalues = ['NULL', 'NULL', 'NULL']
values = [str(attr) for attr in attrs]
self.assertEqual(expectedvalues, values)
def test_qgiscountpointsinpolygon(self):
outputs=processing.runalg("qgis:countpointsinpolygon",polygons(),points(),"NUMPOINTS", self.getOutputFile())
output=outputs['OUTPUT']
layer=dataobjects.getObjectFromUri(output, True)
fields=layer.pendingFields()
expectednames=['ID','POLY_NUM_A','POLY_ST_A','NUMPOINTS']
expectedtypes=['Integer','Real','String','Real']
names=[str(f.name()) for f in fields]
types=[str(f.typeName()) for f in fields]
self.assertEqual(expectednames, names)
self.assertEqual(expectedtypes, types)
features=processing.features(layer)
self.assertEqual(2, len(features))
feature=features.next()
attrs=feature.attributes()
expectedvalues=["1","1.1","string a","6"]
values=[str(attr) for attr in attrs]
self.assertEqual(expectedvalues, values)
def test_modeleremptystring(self):
outputs = processing.runalg('modeler:emptystring', union(), None)
output = outputs['OUTPUT_LAYER_ALG0']
layer = dataobjects.getObjectFromUri(output, True)
fields = layer.pendingFields()
expectednames = [
'ID',
'POLY_NUM_A',
'POLY_ST_A',
'ID_2',
'POLY_NUM_B',
'POLY_ST_B',
'NewField',
]
expectedtypes = [
'Integer',
'Real',
'String',
'Integer',
'Real',
'String',
'Integer',
]
names = [unicode(f.name()) for f in fields]
types = [unicode(f.typeName()) for f in fields]
self.assertEqual(expectednames, names)
self.assertEqual(expectedtypes, types)
features = processing.features(layer)
self.assertEqual(8, len(features))
feature = features.next()
attrs = feature.attributes()
expectedvalues = [
'1',
'1.1',
'string a',
'2',
'1',
'string a',
'10',
]
values = [unicode(attr) for attr in attrs]
self.assertEqual(expectedvalues, values)
wkt = 'POLYGON((270807.08580285 4458940.1594565,270798.42294527 4458914.62661676,270780.81854858 4458914.21983449,270763.52289518 4458920.715993,270760.3449542 4458926.6570575,270763.78234766 4458958.22561242,270794.30290024 4458942.16424502,270807.08580285 4458940.1594565))'
self.assertEqual(wkt, unicode(feature.geometry().exportToWkt()))
def test_modeleremptystring(self):
outputs = processing.runalg('modeler:emptystring', union(), None)
output = outputs['OUTPUT_LAYER_ALG0']
layer = dataobjects.getObjectFromUri(output, True)
fields = layer.pendingFields()
expectednames = [
'ID',
'POLY_NUM_A',
'POLY_ST_A',
'ID_2',
'POLY_NUM_B',
'POLY_ST_B',
'NewField',
]
expectedtypes = [
'Integer',
'Real',
'String',
'Integer',
'Real',
'String',
'Integer',
]
names = [unicode(f.name()) for f in fields]
types = [unicode(f.typeName()) for f in fields]
self.assertEqual(expectednames, names)
self.assertEqual(expectedtypes, types)
features = processing.features(layer)
self.assertEqual(8, len(features))
feature = features.next()
attrs = feature.attributes()
expectedvalues = [
'1',
'1.1',
'string a',
'2',
'1',
'string a',
'10',
]
values = [unicode(attr) for attr in attrs]
self.assertEqual(expectedvalues, values)
wkt = 'POLYGON((270807.08580285 4458940.1594565,270798.42294527 4458914.62661676,270780.81854858 4458914.21983449,270763.52289518 4458920.715993,270760.3449542 4458926.6570575,270763.78234766 4458958.22561242,270794.30290024 4458942.16424502,270807.08580285 4458940.1594565))'
self.assertEqual(wkt, unicode(feature.geometry().exportToWkt()))
def test_gdalogrogr2ogrWrongExtension(self):
outputs = processing.runalg('gdalogr:ogr2ogr', union(), 3, '',
getTempFilename('wrongext'))
output = outputs['OUTPUT_LAYER']
layer = dataobjects.getObjectFromUri(output, True)
fields = layer.pendingFields()
expectednames = [
'id',
'poly_num_a',
'poly_st_a',
'id_2',
'poly_num_b',
'poly_st_b',
]
expectedtypes = [
'Integer',
'Real',
'String',
'Integer',
'Real',
'String',
]
names = [str(f.name()) for f in fields]
types = [str(f.typeName()) for f in fields]
self.assertEqual(expectednames, names)
self.assertEqual(expectedtypes, types)
features = processing.features(layer)
self.assertEqual(8, len(features))
feature = features.next()
attrs = feature.attributes()
expectedvalues = [
'1',
'1.1',
'string a',
'2',
'1',
'string a',
]
values = [str(attr) for attr in attrs]
self.assertEqual(expectedvalues, values)
wkt = 'POLYGON((270807.08580285 4458940.1594565,270798.42294527 4458914.62661676,270780.81854858 4458914.21983449,270763.52289518 4458920.715993,270760.3449542 4458926.6570575,270763.78234766 4458958.22561242,270794.30290024 4458942.16424502,270807.08580285 4458940.1594565))'
self.assertEqual(wkt, str(feature.geometry().exportToWkt()))
def test_gdalogrogr2ogrWrongExtension(self):
outputs = processing.runalg('gdalogr:ogr2ogr', union(), 3, '',
getTempFilename('wrongext'))
output = outputs['OUTPUT_LAYER']
layer = dataobjects.getObjectFromUri(output, True)
fields = layer.pendingFields()
expectednames = [
'id',
'poly_num_a',
'poly_st_a',
'id_2',
'poly_num_b',
'poly_st_b',
]
expectedtypes = [
'Integer',
'Real',
'String',
'Integer',
'Real',
'String',
]
names = [unicode(f.name()) for f in fields]
types = [unicode(f.typeName()) for f in fields]
self.assertEqual(expectednames, names)
self.assertEqual(expectedtypes, types)
features = processing.features(layer)
self.assertEqual(8, len(features))
feature = features.next()
attrs = feature.attributes()
expectedvalues = [
'1',
'1.1',
'string a',
'2',
'1',
'string a',
]
values = [unicode(attr) for attr in attrs]
self.assertEqual(expectedvalues, values)
wkt = 'POLYGON((270807.08580285 4458940.1594565,270798.42294527 4458914.62661676,270780.81854858 4458914.21983449,270763.52289518 4458920.715993,270760.3449542 4458926.6570575,270763.78234766 4458958.22561242,270794.30290024 4458942.16424502,270807.08580285 4458940.1594565))'
self.assertEqual(wkt, unicode(feature.geometry().exportToWkt()))
def test_modeleroptionalfield(self):
outputs = processing.runalg('modeler:optionalfield', points(), None)
output = outputs['OUTPUT_ALG0']
layer = dataobjects.getObjectFromUri(output, True)
fields = layer.pendingFields()
expectednames = ['id', 'value', 'area', 'perim']
expectedtypes = ['Integer', 'String', 'Real', 'Real']
names = [unicode(f.name()) for f in fields]
types = [unicode(f.typeName()) for f in fields]
self.assertEqual(expectednames, names)
self.assertEqual(expectedtypes, types)
features = processing.features(layer)
self.assertEqual(1, len(features))
feature = features.next()
attrs = feature.attributes()
expectedvalues = ['0', 'all', '3592.818848', '230.989919']
values = [unicode(attr) for attr in attrs]
self.assertEqual(expectedvalues, values)
wkt = 'POLYGON((270839.46818665 4458921.97813894,270778.60197966 4458935.96883677,270786.54279065 4458980.04784113,270803.15756434 4458983.84880322,270839.65586926 4458983.16267036,270855.74530134 4458940.79948673,270839.46818665 4458921.97813894))'
self.assertEqual(wkt, unicode(feature.geometry().exportToWkt()))
def test_qgiscountpointsinpolygon(self):
outputs = processing.runalg('qgis:countpointsinpolygon', polygons(),
points(), 'NUMPOINTS',
self.getOutputFile())
output = outputs['OUTPUT']
layer = dataobjects.getObjectFromUri(output, True)
fields = layer.pendingFields()
expectednames = ['ID', 'POLY_NUM_A', 'POLY_ST_A', 'NUMPOINTS']
expectedtypes = ['Integer', 'Real', 'String', 'Real']
names = [unicode(f.name()) for f in fields]
types = [unicode(f.typeName()) for f in fields]
self.assertEqual(expectednames, names)
self.assertEqual(expectedtypes, types)
features = processing.features(layer)
self.assertEqual(2, len(features))
feature = features.next()
attrs = feature.attributes()
expectedvalues = ['1', '1.1', 'string a', '6']
values = [unicode(attr) for attr in attrs]
self.assertEqual(expectedvalues, values)
def test_modeleroptionalfield(self):
outputs = processing.runalg("modeler:optionalfield", points(), None)
output = outputs["OUTPUT_ALG0"]
layer = dataobjects.getObjectFromUri(output, True)
fields = layer.pendingFields()
expectednames = ["id", "value", "area", "perim"]
expectedtypes = ["Integer", "String", "Real", "Real"]
names = [str(f.name()) for f in fields]
types = [str(f.typeName()) for f in fields]
self.assertEqual(expectednames, names)
self.assertEqual(expectedtypes, types)
features = processing.features(layer)
self.assertEqual(1, len(features))
feature = features.next()
attrs = feature.attributes()
expectedvalues = ["0", "all", "3592.818848", "230.989919"]
values = [str(attr) for attr in attrs]
self.assertEqual(expectedvalues, values)
wkt = "POLYGON((270839.46818665 4458921.97813894,270778.60197966 4458935.96883677,270786.54279065 4458980.04784113,270803.15756434 4458983.84880322,270839.65586926 4458983.16267036,270855.74530134 4458940.79948673,270839.46818665 4458921.97813894))"
self.assertEqual(wkt, str(feature.geometry().exportToWkt()))
def test_scriptcreatetilingfromvectorlayer(self):
outputs=processing.runalg("script:createtilingfromvectorlayer",union(),10,None)
output=outputs['polygons']
layer=dataobjects.getObjectFromUri(output, True)
fields=layer.pendingFields()
expectednames=['longitude','latitude']
expectedtypes=['Real','Real']
names=[str(f.name()) for f in fields]
types=[str(f.typeName()) for f in fields]
self.assertEqual(expectednames, names)
self.assertEqual(expectedtypes, types)
features=processing.features(layer)
self.assertEqual(10, len(features))
feature=features.next()
attrs=feature.attributes()
expectedvalues=["270761.415396242","4458948.29588823"]
values=[str(attr) for attr in attrs]
self.assertEqual(expectedvalues, values)
wkt='POLYGON((270755.54427424 4458901.23378639,270755.54427424 4458995.35799007,270767.28651824 4458995.35799007,270767.28651824 4458901.23378639,270755.54427424 4458901.23378639))'
self.assertEqual(wkt, str(feature.geometry().exportToWkt()))
def test_scripthexgridfromlayerbounds(self):
outputs=processing.runalg("script:hexgridfromlayerbounds",polygons(),10,None)
output=outputs['grid']
layer=dataobjects.getObjectFromUri(output, True)
fields=layer.pendingFields()
expectednames=['longitude','latitude']
expectedtypes=['Real','Real']
names=[str(f.name()) for f in fields]
types=[str(f.typeName()) for f in fields]
self.assertEqual(expectednames, names)
self.assertEqual(expectedtypes, types)
features=processing.features(layer)
self.assertEqual(117, len(features))
feature=features.next()
attrs=feature.attributes()
expectedvalues=["270765.621834001","4458907.27146471"]
values=[str(attr) for attr in attrs]
self.assertEqual(expectedvalues, values)
wkt='POLYGON((270771.39533669 4458907.27146471,270768.50858535 4458902.27146471,270762.73508265 4458902.27146471,270759.84833131 4458907.27146471,270762.73508265 4458912.27146471,270768.50858535 4458912.27146471,270771.39533669 4458907.27146471))'
self.assertEqual(wkt, str(feature.geometry().exportToWkt()))
def test_modelersagagrass(self):
outputs = processing.runalg('modeler:sagagrass', points(), None)
output = outputs['CENTROIDS_ALG1']
layer = dataobjects.getObjectFromUri(output, True)
fields = layer.pendingFields()
expectednames = ['CAT']
expectedtypes = ['Real']
names = [unicode(f.name()) for f in fields]
types = [unicode(f.typeName()) for f in fields]
self.assertEqual(expectednames, names)
self.assertEqual(expectedtypes, types)
features = processing.features(layer)
self.assertEqual(12, len(features))
feature = features.next()
attrs = feature.attributes()
expectedvalues = ['1']
values = [unicode(attr) for attr in attrs]
self.assertEqual(expectedvalues, values)
wkt = 'POINT(270839.65586926 4458983.16267036)'
self.assertEqual(wkt, unicode(feature.geometry().exportToWkt()))
def test_modeleremptystring(self):
outputs = processing.runalg("modeler:emptystring", union(), None)
output = outputs["OUTPUT_LAYER_ALG0"]
layer = dataobjects.getObjectFromUri(output, True)
fields = layer.pendingFields()
expectednames = ["ID", "POLY_NUM_A", "POLY_ST_A", "ID_2", "POLY_NUM_B", "POLY_ST_B", "NewField"]
expectedtypes = ["Integer", "Real", "String", "Integer", "Real", "String", "Integer"]
names = [str(f.name()) for f in fields]
types = [str(f.typeName()) for f in fields]
self.assertEqual(expectednames, names)
self.assertEqual(expectedtypes, types)
features = processing.features(layer)
self.assertEqual(8, len(features))
feature = features.next()
attrs = feature.attributes()
expectedvalues = ["1", "1.1", "string a", "2", "1", "string a", "10"]
values = [str(attr) for attr in attrs]
self.assertEqual(expectedvalues, values)
wkt = "POLYGON((270807.08580285 4458940.1594565,270798.42294527 4458914.62661676,270780.81854858 4458914.21983449,270763.52289518 4458920.715993,270760.3449542 4458926.6570575,270763.78234766 4458958.22561242,270794.30290024 4458942.16424502,270807.08580285 4458940.1594565))"
self.assertEqual(wkt, str(feature.geometry().exportToWkt()))
def test_modeleroptionalfield(self):
outputs = processing.runalg('modeler:optionalfield', points(), None)
output = outputs['OUTPUT_ALG0']
layer = dataobjects.getObjectFromUri(output, True)
fields = layer.pendingFields()
expectednames = ['id', 'value', 'area', 'perim']
expectedtypes = ['Integer', 'String', 'Real', 'Real']
names = [unicode(f.name()) for f in fields]
types = [unicode(f.typeName()) for f in fields]
self.assertEqual(expectednames, names)
self.assertEqual(expectedtypes, types)
features = processing.features(layer)
self.assertEqual(1, len(features))
feature = features.next()
attrs = feature.attributes()
expectedvalues = ['0', 'all', '3592.818848', '230.989919']
values = [unicode(attr) for attr in attrs]
self.assertEqual(expectedvalues, values)
wkt = 'POLYGON((270839.46818665 4458921.97813894,270778.60197966 4458935.96883677,270786.54279065 4458980.04784113,270803.15756434 4458983.84880322,270839.65586926 4458983.16267036,270855.74530134 4458940.79948673,270839.46818665 4458921.97813894))'
self.assertEqual(wkt, unicode(feature.geometry().exportToWkt()))
def test_modelersagagrass(self):
outputs = processing.runalg("modeler:sagagrass", points(), None)
output = outputs["CENTROIDS_ALG1"]
layer = dataobjects.getObjectFromUri(output, True)
fields = layer.pendingFields()
expectednames = ["CAT"]
expectedtypes = ["Real"]
names = [str(f.name()) for f in fields]
types = [str(f.typeName()) for f in fields]
self.assertEqual(expectednames, names)
self.assertEqual(expectedtypes, types)
features = processing.features(layer)
self.assertEqual(12, len(features))
feature = features.next()
attrs = feature.attributes()
expectedvalues = ["1"]
values = [str(attr) for attr in attrs]
self.assertEqual(expectedvalues, values)
wkt = "POINT(270839.65586926 4458983.16267036)"
self.assertEqual(wkt, str(feature.geometry().exportToWkt()))
def testWrongformat(self):
outputs = processing.runalg('qgis:countpointsinpolygon', polygons(),
points(), 'NUMPOINTS',
getTempFilename('wrongext'))
output = outputs['OUTPUT']
self.assertTrue(output.endswith('shp'))
layer = dataobjects.getObjectFromUri(output, True)
fields = layer.pendingFields()
expectednames = ['ID', 'POLY_NUM_A', 'POLY_ST_A', 'NUMPOINTS']
expectedtypes = ['Integer', 'Real', 'String', 'Real']
names = [unicode(f.name()) for f in fields]
types = [unicode(f.typeName()) for f in fields]
self.assertEqual(expectednames, names)
self.assertEqual(expectedtypes, types)
features = processing.features(layer)
self.assertEqual(2, len(features))
feature = features.next()
attrs = feature.attributes()
expectedvalues = ['1', '1.1', 'string a', '6.0']
values = [unicode(attr) for attr in attrs]
self.assertEqual(expectedvalues, values)
def test_scriptcreatetilingfromvectorlayer(self):
outputs = processing.runalg('script:createtilingfromvectorlayer',
union(), 10, None)
output = outputs['polygons']
layer = dataobjects.getObjectFromUri(output, True)
fields = layer.pendingFields()
expectednames = ['longitude', 'latitude']
expectedtypes = ['Real', 'Real']
names = [str(f.name()) for f in fields]
types = [str(f.typeName()) for f in fields]
self.assertEqual(expectednames, names)
self.assertEqual(expectedtypes, types)
features = processing.features(layer)
self.assertEqual(10, len(features))
feature = features.next()
attrs = feature.attributes()
expectedvalues = ['270761.415396242', '4458948.29588823']
values = [str(attr) for attr in attrs]
self.assertEqual(expectedvalues, values)
wkt = 'POLYGON((270755.54427424 4458901.23378639,270755.54427424 4458995.35799007,270767.28651824 4458995.35799007,270767.28651824 4458901.23378639,270755.54427424 4458901.23378639))'
self.assertEqual(wkt, str(feature.geometry().exportToWkt()))
def test_scripthexgridfromlayerbounds(self):
outputs = processing.runalg('script:hexgridfromlayerbounds',
polygons(), 10, None)
output = outputs['grid']
layer = dataobjects.getObjectFromUri(output, True)
fields = layer.pendingFields()
expectednames = ['longitude', 'latitude']
expectedtypes = ['Real', 'Real']
names = [str(f.name()) for f in fields]
types = [str(f.typeName()) for f in fields]
self.assertEqual(expectednames, names)
self.assertEqual(expectedtypes, types)
features = processing.features(layer)
self.assertEqual(117, len(features))
feature = features.next()
attrs = feature.attributes()
expectedvalues = ['270765.621834001', '4458907.27146471']
values = [str(attr) for attr in attrs]
self.assertEqual(expectedvalues, values)
wkt = 'POLYGON((270771.39533669 4458907.27146471,270768.50858535 4458902.27146471,270762.73508265 4458902.27146471,270759.84833131 4458907.27146471,270762.73508265 4458912.27146471,270768.50858535 4458912.27146471,270771.39533669 4458907.27146471))'
self.assertEqual(wkt, str(feature.geometry().exportToWkt()))
def testWrongformat(self):
outputs = processing.runalg('qgis:countpointsinpolygon', polygons(),
points(), 'NUMPOINTS',
getTempFilename('wrongext'))
output = outputs['OUTPUT']
self.assertTrue(output.endswith('shp'))
layer = dataobjects.getObjectFromUri(output, True)
fields = layer.pendingFields()
expectednames = ['ID', 'POLY_NUM_A', 'POLY_ST_A', 'NUMPOINTS']
expectedtypes = ['Integer', 'Real', 'String', 'Real']
names = [str(f.name()) for f in fields]
types = [str(f.typeName()) for f in fields]
self.assertEqual(expectednames, names)
self.assertEqual(expectedtypes, types)
features = processing.features(layer)
self.assertEqual(2, len(features))
feature = features.next()
attrs = feature.attributes()
expectedvalues = ['1', '1.1', 'string a', '6.0']
values = [str(attr) for attr in attrs]
self.assertEqual(expectedvalues, values)
units = "?"
# Make a list to stage feature IDs, their vertex lists, and output elevations
# Each part within a multipart feature will be considered a separate geometry,
# for the purposes of exporting to Collada)
outputFeatures = []
# Count any errors when getting the feature elevation values
feat_elev_error_counter = 0
# Count the number of features;
# we will use this as part of the feature ID for each geometry instance
feat_counter = 0
progress.setText("Scanning over input features...")
for feat in processing.features(linework):
feat_counter += 1
geom_col = feat.geometry().asGeometryCollection()
# The geom_col will be a list containing each "part" of the geometry
# (if the geometry is single-part, then we expect len(geom_col) == 1)
# We want to handle both polyline and polygon geometries
part_counter = 0
for geom_part in geom_col:
part_counter += 1
if len(geom_part.asPolyline()) > 0:
# This part is a polyline
vertexlist = []
geom_vertexlist = geom_part.asPolyline()
edge1.increase_weight(edge2.get_weight())
edge2.increase_weight(edge1.get_weight())
return ids_to_delete
t_start = datetime.now()
print '{0}: Collapsing lines'.format(t_start)
layer = processing.getObject(input_layer)
crs = layer.crs()
provider = layer.dataProvider()
fields = provider.fields()
fields.append(QgsField('SEG_ID',QVariant.Int))
fields.append(QgsField('MERGED_N', QVariant.Double))
writer = processing.VectorWriter(collapsed_lines, None, fields, QGis.WKBLineString, crs)
features = list(processing.features(layer))
weight_index = provider.fieldNameIndex(weight_field)
# get all labels from the input features
labels = []
for feat in features:
labels.append(int(feat[cluster_field]))
# one cluster per label
clusters = []
for l in range(0,max(labels)+1):
clusters.append(list())
# populate clusters
vl = QgsVectorLayer("LineString", "line_segments", "memory")
pr = vl.dataProvider()
def calculateFields(self, listKeep, listStats, output):
# get selected layer
index = self.ui.comboLayerList.currentIndex()
legendInterface = self.iface.legendInterface()
listLayers = [layer for layer in legendInterface.layers() if layer.type() == QgsMapLayer.VectorLayer]
selectedLayer = listLayers[index]
# iterates over layer features to get attributes as a list of lists
# uses the processing method so as to get only selected features if this option is set in the processing options
iter = processing.features(selectedLayer)
attrs = [feature.attributes() for feature in iter]
# get all values of the dissolve field (before processing : with duplicate values)
indexDissolveField = self.ui.comboFieldList.currentIndex()
valuesDissolveField = [feature[indexDissolveField] for feature in attrs]
# get unique values for dissolve field, from output (seems more secure than to get it from valuesDissolveField ?)
outputLayer = QgsVectorLayer(output, "name", "ogr")
provider = outputLayer.dataProvider()
fields = provider.fields()
listFieldNames = [field.name() for field in fields]
iter = outputLayer.getFeatures()
uniqueValuesDissolveField = [feature.attributes()[indexDissolveField] for feature in iter]
# initializes list of lists which will contain results (it will have one element per kept field)
listRes = []
# trick for dissolve field, if kept
if listKeep[indexDissolveField] == 2:
listStats [indexDissolveField] = 'First'
# for each kept field
for i in range(len(listFieldNames)):
if listKeep[i] == 2:
# creates list which will contain attribute values for current field, one empty element per unique dissolve field value
listAttrs = [[] for val in range(len(uniqueValuesDissolveField))]
# fill this list with all the current field values corresponding to each dissolve field value
valuesField = [feature[i] for feature in attrs]
for (x,y) in zip(valuesDissolveField, valuesField):
listAttrs[uniqueValuesDissolveField.index(x)].append(y)
# removes any NULL values
listAttrs = [[x for x in l if x] for l in listAttrs]
# for each list in listAttrs, calculates one value according to the chosen stat
# if list is empty (can happen if it contained originally only NULL values), return NULL as a result
if listStats[i] == "Mean":
listAttrs = [sum(y) / len(y) if y else NULL for y in listAttrs]
elif listStats[i] == "Sum":
listAttrs = [sum(y) if y else NULL for y in listAttrs]
elif listStats[i] == "Min":
listAttrs = [min(y) if y else NULL for y in listAttrs]
elif listStats[i] == "Max":
listAttrs = [max(y) if y else NULL for y in listAttrs]
elif listStats[i] == "Count":
listAttrs = [len(y) if y else NULL for y in listAttrs]
elif listStats[i] == "First":
listAttrs = [y[0] if y else NULL for y in listAttrs]
elif listStats[i] == "Last":
listAttrs = [y[-1] if y else NULL for y in listAttrs]
elif listStats[i] == "Median":
listAttrs = [self.median(y) if y else NULL for y in listAttrs]
elif listStats[i] == "Standard deviation":
listAttrs = [self.standard_dev(y) if y else NULL for y in listAttrs]
elif listStats[i] == "Concatenation":
listAttrs = [", ".join(y) if y else NULL for y in listAttrs]
elif listStats[i] == "Uniquification":
listAttrs = [", ".join(set(y)) if y else NULL for y in listAttrs]
# append each field result to listRes
listRes.append(listAttrs)
return listRes
def run(self):
"""Run method that performs all the real work"""
# show the dialog
self.dlg.show()
# Run the dialog event loop
result = self.dlg.exec_()
# See if OK was pressed
if result:
# CARREGAR VALORES DOS PARAMETROS:
#PARAMETRO 1
ListaVarIndep = []
ListaLayerName = []
NrLinhasTabela = self.dlg.tableWidget.rowCount()
for Linhas in range(NrLinhasTabela):
VarIndepPath = self.dlg.tableWidget.item(Linhas, 0).text()
VarIndepLayerName = self.dlg.tableWidget.item(Linhas, 1).text()
ListaVarIndep.append(VarIndepPath)
ListaLayerName.append(VarIndepLayerName)
#PARAMETRO 2
VarDep = self.dlg.lineEdit_2.text()
VarDepDisplayName = self.dlg.lineEdit_4.text()
#PARAMETRO 3
InputOutputFolder = self.dlg.lineEdit_3.text()
#PARAMETRO 4
RasterValidacao = self.dlg.lineEdit_5.text()
ValidacaoDisplayName = self.dlg.lineEdit_6.text()
# INICIO DOS PROCESSOS:
# CRIAR PASTA OUTPUT
PastaOutput = os.path.join(InputOutputFolder, "Output")
if not os.path.exists(PastaOutput):
os.makedirs(PastaOutput)
else:
for NrPastas in range(1, 10):
sufixo = "_" + str(NrPastas)
PastaOutput = os.path.join(InputOutputFolder,
"Output" + sufixo)
if not os.path.exists(PastaOutput):
os.makedirs(PastaOutput)
break
# CRIAR SUBPASTA TABELAS
PastaTabelas = os.path.join(PastaOutput, "Tabelas")
os.makedirs(PastaTabelas)
# CARREGAR VARIAVEL DEPENDENTE E ADICIONAR LAYER AO QGIS
LoadVarDep = QgsRasterLayer(VarDep, VarDepDisplayName)
ListaVarIndepVI = []
# PROPRIEDADES DOS FICHEIROS DE INPUT
for VarIndep, VarIndepLayerName in zip(ListaVarIndep,
ListaLayerName):
# CARREGAR VARIAVEL INDEPENDENTE E ADICIONAR LAYER AO QGIS
LoadVarIndep = QgsRasterLayer(VarIndep, VarIndepLayerName)
AddVarIndep = QgsMapLayerRegistry.instance().addMapLayer(
LoadVarIndep)
# DEFINIR EXTENSAO
ext = AddVarIndep.extent()
xmin = ext.xMinimum()
xmax = ext.xMaximum()
ymin = ext.yMinimum()
ymax = ext.yMaximum()
Mask = "%f,%f,%f,%f" % (xmin, xmax, ymin, ymax)
# DEFINIR CELL SIZE
PixelSizeX = LoadVarIndep.rasterUnitsPerPixelX()
PixelSizeY = LoadVarIndep.rasterUnitsPerPixelY()
CellSize = PixelSizeX * PixelSizeY
# CRIAR REPORT E CALCULAR VALORES UNICOS
CountUniqueValues = os.path.join(
PastaTabelas, VarIndepLayerName + "_CountUniqueValues.txt")
processing.runalg("grass7:r.report", VarIndep, 5, "*", 255,
True, True, True, True, Mask, None,
CountUniqueValues)
ReportReadLines = open(CountUniqueValues).readlines()
ReportSelectLines = ReportReadLines[4:-4]
UniqueValues = len(ReportSelectLines)
# DEFINIR CAMINHO DO OUTPUT E EXECUTAR R.COIN
RCoinFile = os.path.join(
PastaTabelas, VarIndepLayerName + "_x_" +
VarDepDisplayName + "_Original.txt")
processing.runalg("grass7:r.coin", VarIndep, VarDep, 0, False,
Mask, None, RCoinFile)
# LER RCOINFILE E SELECIONAR AS LINHAS COM INFORMACAO UTIL
ReadLines = open(RCoinFile).readlines()
SelectLines = ReadLines[22:UniqueValues + 22]
# FORMATAR DADOS PARA IMPORTACAO EM CSV
ListaValores = []
for row in SelectLines:
RemoverEspacos = re.sub(' +', ' ', row)
SubstituirEspacos = RemoverEspacos.replace(' ', ';')
SepararPontoVirgula = SubstituirEspacos.split(";")
SelecionarColunas = itemgetter(1, 3, 5,
7)(SepararPontoVirgula)
JuntarColunas = ';'.join(SelecionarColunas)
ListaValores.append(JuntarColunas)
if UniqueValues <= 2:
JuntarLinhas = ';'.join(ListaValores)
SepararValores = JuntarLinhas.split(";")
ConversaoInteiros = map(int, SepararValores)
Linha0 = "V;V0;V1;T\n"
Linha1 = str(ConversaoInteiros[0] + 1) + ";" + str(
ConversaoInteiros[1]) + ";" + str(
ConversaoInteiros[5]) + ";" + str(
ConversaoInteiros[1] +
ConversaoInteiros[5]) + "\n"
Linha2 = str(ConversaoInteiros[4] + 1) + ";" + str(
ConversaoInteiros[2]) + ";" + str(
ConversaoInteiros[6]) + ";" + str(
ConversaoInteiros[2] + ConversaoInteiros[6])
ValoresImportar = [Linha0, Linha1, Linha2]
else:
ListaValores.insert(0, 'V;V0;V1;T')
ValoresImportar = '\n'.join(ListaValores)
# ESCREVER DADOS FORMATADOS NUM NOVO FICHEIRO TXT
RCoinTemp = os.path.join(
PastaTabelas, VarIndepLayerName + "_x_" +
VarDepDisplayName + "_Tratado.txt")
open(RCoinTemp, 'wb').writelines(ValoresImportar)
# IMPORTAR PARA FICHEIRO CSV
TabulateAreaCSV = os.path.join(
PastaTabelas,
VarIndepLayerName + "_x_" + VarDepDisplayName + ".csv")
csv.writer(open(TabulateAreaCSV, 'wb')).writerows(
csv.reader(open(RCoinTemp, 'rb')))
# EXPORTAR PARA DBF
LoadTabulateAreaCSV = QgsVectorLayer(
TabulateAreaCSV,
VarIndepLayerName + "_x_" + VarDepDisplayName, "ogr")
DbfTablePath = os.path.join(
PastaTabelas,
VarIndepLayerName + "_x_" + VarDepDisplayName)
QgsVectorFileWriter.writeAsVectorFormat(
LoadTabulateAreaCSV, DbfTablePath, "System", None,
"ESRI Shapefile")
os.remove(DbfTablePath + ".prj")
os.remove(DbfTablePath + ".qpj")
# CARREGAR TABELA DBF PARA o QGIS
DbfTable = QgsVectorLayer(
DbfTablePath + ".dbf",
VarIndepLayerName + "_x_" + VarDepDisplayName + ".dbf",
"ogr")
AddDbfTable = QgsMapLayerRegistry.instance().addMapLayer(
DbfTable)
# OBTER INDEXs DOS CAMPOS EXISTENTES
IndexCampoV = DbfTable.fieldNameIndex("V")
IndexCampoV0 = DbfTable.fieldNameIndex("V0")
IndexCampoV1 = DbfTable.fieldNameIndex("V1")
IndexCampoT = DbfTable.fieldNameIndex("T")
# CRIAR CAMPOS A CALCULAR
CampoVALUE = DbfTable.dataProvider().addAttributes(
[QgsField("VALUE", QVariant.Int)])
CampoVALUE_0 = DbfTable.dataProvider().addAttributes(
[QgsField("VALUE_0", QVariant.Int)])
CampoVALUE_1 = DbfTable.dataProvider().addAttributes(
[QgsField("VALUE_1", QVariant.Int)])
CampoARCLASSE = DbfTable.dataProvider().addAttributes(
[QgsField("ARCLASSE", QVariant.Int)])
CampoPROBCOND = DbfTable.dataProvider().addAttributes(
[QgsField("PROBCOND", QVariant.Double)])
CampoSUM_VALUE0 = DbfTable.dataProvider().addAttributes(
[QgsField("SUM_VALUE0", QVariant.Int)])
CampoSUM_VALUE1 = DbfTable.dataProvider().addAttributes(
[QgsField("SUM_VALUE1", QVariant.Int)])
CampoAR_TOTAL = DbfTable.dataProvider().addAttributes(
[QgsField("AR_TOTAL", QVariant.Int)])
CampoPRIORI = DbfTable.dataProvider().addAttributes(
[QgsField("PRIORI", QVariant.Double)])
CampoSINI_SN = DbfTable.dataProvider().addAttributes(
[QgsField("SINI_SN", QVariant.Double)])
CampoVI = DbfTable.dataProvider().addAttributes(
[QgsField("VI", QVariant.Double)])
DbfTable.updateFields()
# OBTER INDEXs DOS CAMPOS CRIADOS
IndexCampoVALUE = DbfTable.fieldNameIndex("VALUE")
IndexCampoVALUE_0 = DbfTable.fieldNameIndex("VALUE_0")
IndexCampoVALUE_1 = DbfTable.fieldNameIndex("VALUE_1")
IndexCampoARCLASSE = DbfTable.fieldNameIndex("ARCLASSE")
IndexCampoPROBCOND = DbfTable.fieldNameIndex("PROBCOND")
IndexCampoSUM_VALUE0 = DbfTable.fieldNameIndex("SUM_VALUE0")
IndexCampoSUM_VALUE1 = DbfTable.fieldNameIndex("SUM_VALUE1")
IndexCampoAR_TOTAL = DbfTable.fieldNameIndex("AR_TOTAL")
IndexCampoPRIORI = DbfTable.fieldNameIndex("PRIORI")
IndexCampoSINI_SN = DbfTable.fieldNameIndex("SINI_SN")
IndexCampoVI = DbfTable.fieldNameIndex("VI")
# COPIAR VALORES PARA OS CAMPOS BASE
DbfTable.startEditing()
for Valores in processing.features(DbfTable):
DbfTable.changeAttributeValue(Valores.id(),
IndexCampoVALUE,
Valores[IndexCampoV])
DbfTable.changeAttributeValue(
Valores.id(), IndexCampoVALUE_0,
int(Valores[IndexCampoV0]) * CellSize)
DbfTable.changeAttributeValue(
Valores.id(), IndexCampoVALUE_1,
int(Valores[IndexCampoV1]) * CellSize)
DbfTable.changeAttributeValue(
Valores.id(), IndexCampoARCLASSE,
int(Valores[IndexCampoT]) * CellSize)
DbfTable.commitChanges()
DbfTable.updateFields()
ListaVALUE_0 = []
ListaVALUE_1 = []
DbfTable.startEditing()
for Valores in processing.features(DbfTable):
DbfTable.changeAttributeValue(
Valores.id(), IndexCampoPROBCOND,
float(Valores[IndexCampoVALUE_1]) /
float(Valores[IndexCampoARCLASSE]))
ListaVALUE_0.append(int(Valores[IndexCampoVALUE_0]))
ListaVALUE_1.append(int(Valores[IndexCampoVALUE_1]))
DbfTable.commitChanges()
DbfTable.updateFields()
# CALCULAR CAMPOS 'SUM_VALUE0' e 'SUM_VALUE1'
SomaVALUE_0 = sum(ListaVALUE_0)
SomaVALUE_1 = sum(ListaVALUE_1)
DbfTable.startEditing()
for Valores in processing.features(DbfTable):
DbfTable.changeAttributeValue(Valores.id(),
IndexCampoSUM_VALUE0,
SomaVALUE_0)
DbfTable.changeAttributeValue(Valores.id(),
IndexCampoSUM_VALUE1,
SomaVALUE_1)
DbfTable.commitChanges()
DbfTable.updateFields()
# CALCULAR CAMPO 'AR_TOTAL'
DbfTable.startEditing()
[
DbfTable.changeAttributeValue(
Valores.id(), IndexCampoAR_TOTAL,
float(Valores[IndexCampoSUM_VALUE0]) +
float(Valores[IndexCampoSUM_VALUE1]))
for Valores in processing.features(DbfTable)
]
DbfTable.commitChanges()
DbfTable.updateFields()
# CALCULAR CAMPO 'PRIORI'
DbfTable.startEditing()
[
DbfTable.changeAttributeValue(
Valores.id(), IndexCampoPRIORI,
float(Valores[IndexCampoSUM_VALUE1]) /
float(Valores[IndexCampoAR_TOTAL]))
for Valores in processing.features(DbfTable)
]
DbfTable.commitChanges()
DbfTable.updateFields()
# CALCULAR CAMPO 'SINI_SN'
DbfTable.startEditing()
[
DbfTable.changeAttributeValue(
Valores.id(), IndexCampoSINI_SN,
float(Valores[IndexCampoPROBCOND]) /
float(Valores[IndexCampoPRIORI]))
for Valores in processing.features(DbfTable)
]
DbfTable.commitChanges()
DbfTable.updateFields()
# CALCULAR CAMPO 'VI'
DbfTable.startEditing()
ListaVI_Min = []
for Valores in processing.features(DbfTable):
if float(Valores[IndexCampoSINI_SN]) > 0:
DbfTable.changeAttributeValue(
Valores.id(), IndexCampoVI,
math.log(float(Valores[IndexCampoSINI_SN])))
ListaVI_Min.append(
math.log(float(Valores[IndexCampoSINI_SN])))
ListaVI_Min.sort()
VI_MIN = (ListaVI_Min[0])
for Valores in processing.features(DbfTable):
if float(Valores[IndexCampoSINI_SN]) == 0:
DbfTable.changeAttributeValue(Valores.id(),
IndexCampoVI,
float(VI_MIN))
DbfTable.commitChanges()
DbfTable.updateFields()
# CRIAR EXPRESSAO E FICHEIRO TXT PARA RECLASSIFICACAO COM VALORES DE VI
ListaReclass = []
for Valores in processing.features(DbfTable):
ListaReclass.append(
str(Valores[IndexCampoVALUE]) + "=" +
str(int(round(Valores[IndexCampoVI], 9) * (10**8))))
ExpressaoReclass = '\n'.join(ListaReclass)
ReclassVITxt = os.path.join(
PastaTabelas, VarIndepLayerName + "_ReclassVI.txt")
open(ReclassVITxt, 'wb').writelines(ExpressaoReclass)
# RECLASSIFICACAO DAS VARIAVEIS INDEPENDENTES COM VALORES DE VI
VarIndepVI = os.path.join(PastaOutput,
VarIndepLayerName + "_VI.tif")
processing.runalg("grass7:r.reclass", VarIndep, ReclassVITxt,
Mask, 0, VarIndepVI)
ListaVarIndepVI.append(VarIndepVI)
# APAGAR CAMPOS INICIAIS PROVENIENTES DO CSV
DbfTable.dataProvider().deleteAttributes(
[IndexCampoV, IndexCampoV0, IndexCampoV1, IndexCampoT])
DbfTable.updateFields()
# REMOVER VARIAVEIS INDEPENDENTES DO QGIS
QgsMapLayerRegistry.instance().removeMapLayers(
[AddVarIndep.id()])
# SOMAR RASTERS DAS VARIAVEIS INDEPENDENTES NO RASTER CALCULATOR PARA OBTER O MAPA VI FINAL
EntriesVIRaster = []
ListaVIRasterRef = []
for Index, VarIndepVI, VarIndepLayerName in zip(
range(0, len(ListaVarIndepVI)), ListaVarIndepVI,
ListaLayerName):
LoadVarIndepVI = QgsRasterLayer(VarIndepVI,
VarIndepLayerName + "_VI")
AddVarIndepVI = QgsMapLayerRegistry.instance().addMapLayer(
LoadVarIndepVI)
VIRasterObject = processing.getObject(ListaVarIndepVI[Index])
VIRaster = QgsRasterCalculatorEntry()
VIRaster.raster = VIRasterObject
VIRaster.ref = str(VarIndepLayerName + '_VI@1')
VIRaster.bandNumber = 1
EntriesVIRaster.append(VIRaster)
ListaVIRasterRef.append(VIRaster.ref)
ExpressaoCalculateVI = "(" + " + ".join(ListaVIRasterRef) + ")"
VI = os.path.join(PastaOutput, "VI.tif")
CalculateVI = QgsRasterCalculator(ExpressaoCalculateVI, VI,
'GTiff', VIRasterObject.extent(),
VIRasterObject.width(),
VIRasterObject.height(),
EntriesVIRaster)
CalculateVI.processCalculation()
# ADICIONAR RASTER DO VALOR INFORMATIVO AO QGIS
LoadVI = QgsRasterLayer(VI, "VI")
AddVI = QgsMapLayerRegistry.instance().addMapLayer(LoadVI)
####VALIDACAO:####
# CONVERTER RASTER DO VI PARA VALORES INTEIROS
VIint = os.path.join(PastaOutput, "VIint.tif")
processing.runalg("gdalogr:rastercalculator", VI, "1", None, "1",
None, "1", None, "1", None, "1", None, "1",
"rint(A)", "", 4, "", VIint)
# CRIAR REPORT E CALCULAR VALORES UNICOS DE VI
VI_CountUniqueValues = os.path.join(PastaTabelas,
"VI_CountUniqueValues.txt")
processing.runalg("grass7:r.report", VIint, 5, "*", 255, True,
True, True, True, Mask, None,
VI_CountUniqueValues)
VI_ReportReadLines = open(VI_CountUniqueValues).readlines()
VI_ReportSelectLines = VI_ReportReadLines[4:-4]
VI_UniqueValues = len(VI_ReportSelectLines)
# DEFINIR CAMINHO DO OUTPUT E EXECUTAR R.COIN DE VALIDACAO
VI_RCoin = os.path.join(
PastaTabelas, "VI_x_" + ValidacaoDisplayName + "_Original.txt")
processing.runalg("grass7:r.coin", VIint, RasterValidacao, 0,
False, Mask, None, VI_RCoin)
# LER VI_RCOIN E SELECIONAR AS LINHAS COM INFORMACAO UTIL
ValidacaoReadLines = open(VI_RCoin).readlines()
ValidacaoSelectLines = ValidacaoReadLines[22:VI_UniqueValues + 22]
# FORMATAR DADOS PARA IMPORTACAO EM CSV
ValidacaoListaValores = []
for row in ValidacaoSelectLines:
RemoverEspacos = re.sub(' +', ' ', row)
SubstituirEspacos = RemoverEspacos.replace(' ', ';')
SepararPontoVirgula = SubstituirEspacos.split(";")
SelecionarColunas = itemgetter(1, 5, 7)(SepararPontoVirgula)
ConversaoInteiros = map(int, SelecionarColunas)
ValidacaoListaValores.append(ConversaoInteiros)
ValidacaoListaValores = sorted(ValidacaoListaValores, reverse=True)
ListaOrdenada = []
for row in ValidacaoListaValores:
SubstituirEspacos = str(row).replace(', ', ';')
RemoverParentese1 = SubstituirEspacos.replace('[', '')
RemoverParentese2 = RemoverParentese1.replace(']', '')
ListaOrdenada.append(RemoverParentese2)
ListaOrdenada.insert(0, 'V;V1;T')
ValidacaoValoresImportar = '\n'.join(ListaOrdenada)
# ESCREVER DADOS FORMATADOS NUM NOVO FICHEIRO TXT
VI_RCoinTemp = os.path.join(
PastaTabelas, "VI_x_" + ValidacaoDisplayName + "_Tratado.txt")
open(VI_RCoinTemp, 'wb').writelines(ValidacaoValoresImportar)
# IMPORTAR PARA FICHEIRO CSV
TS_CSV = os.path.join(PastaTabelas,
"VI_x_" + ValidacaoDisplayName + ".csv")
csv.writer(open(TS_CSV, 'wb')).writerows(
csv.reader(open(VI_RCoinTemp, 'rb')))
# EXPORTAR PARA DBF
LoadTSCSV = QgsVectorLayer(TS_CSV, "TS", "ogr")
DbfTSPath = os.path.join(PastaTabelas, "TS")
QgsVectorFileWriter.writeAsVectorFormat(LoadTSCSV, DbfTSPath,
"System", None,
"ESRI Shapefile")
os.remove(DbfTSPath + ".prj")
os.remove(DbfTSPath + ".qpj")
# CARREGAR TABELA DBF PARA o QGIS
DbfTS = QgsVectorLayer(DbfTSPath + ".dbf", "TS.dbf", "ogr")
AddDbfTS = QgsMapLayerRegistry.instance().addMapLayer(DbfTS)
# OBTER INDEXs DOS CAMPOS EXISTENTES
TS_IndexCampoV = DbfTS.fieldNameIndex("V")
TS_IndexCampoV1 = DbfTS.fieldNameIndex("V1")
TS_IndexCampoT = DbfTS.fieldNameIndex("T")
# CRIAR CAMPOS A CALCULAR
TS_CampoVI = DbfTS.dataProvider().addAttributes(
[QgsField("VI", QVariant.Double)])
TS_CampoARESTUDO = DbfTS.dataProvider().addAttributes(
[QgsField("ARESTUDO", QVariant.Int)])
TS_CampoARFENOM = DbfTS.dataProvider().addAttributes(
[QgsField("ARFENOM", QVariant.Int)])
TS_CampoArEstudAc = DbfTS.dataProvider().addAttributes(
[QgsField("ArEstudAc", QVariant.Double)])
TS_CampoArFenomAc = DbfTS.dataProvider().addAttributes(
[QgsField("ArFenomAc", QVariant.Double)])
TS_CampoLsi_Li = DbfTS.dataProvider().addAttributes(
[QgsField("Lsi_Li", QVariant.Double)])
TS_Campoai_b1_2 = DbfTS.dataProvider().addAttributes(
[QgsField("ai_b1_2", QVariant.Double)])
TS_CampoACC = DbfTS.dataProvider().addAttributes(
[QgsField("ACC", QVariant.Double)])
DbfTS.updateFields()
# OBTER INDEXs DOS CAMPOS CRIADOS
TS_IndexCampoVI = DbfTS.fieldNameIndex("VI")
TS_IndexCampoARESTUDO = DbfTS.fieldNameIndex("ARESTUDO")
TS_IndexCampoARFENOM = DbfTS.fieldNameIndex("ARFENOM")
TS_IndexCampoArEstudAc = DbfTS.fieldNameIndex("ArEstudAc")
TS_IndexCampoArFenomAc = DbfTS.fieldNameIndex("ArFenomAc")
TS_IndexCampoLsi_Li = DbfTS.fieldNameIndex("Lsi_Li")
TS_IndexCampoai_b1_2 = DbfTS.fieldNameIndex("ai_b1_2")
TS_IndexCampoACC = DbfTS.fieldNameIndex("ACC")
# COPIAR VALORES PARA OS CAMPOS BASE
DbfTS.startEditing()
for Valores in processing.features(DbfTS):
DbfTS.changeAttributeValue(
Valores.id(), TS_IndexCampoVI,
float(Valores[TS_IndexCampoV]) / float(10**8))
DbfTS.changeAttributeValue(
Valores.id(), TS_IndexCampoARESTUDO,
int(Valores[TS_IndexCampoT]) * CellSize)
DbfTS.changeAttributeValue(
Valores.id(), TS_IndexCampoARFENOM,
int(Valores[TS_IndexCampoV1]) * CellSize)
DbfTS.commitChanges()
DbfTS.updateFields()
# CPRIAR LISTAS DE VALORES PARA AS SOMAS ACUMULADAS
ListaARESTUDO = []
ListaARFENOM = []
for Valores in processing.features(DbfTS):
ListaARESTUDO.append(int(Valores[TS_IndexCampoARESTUDO]))
ListaARFENOM.append(int(Valores[TS_IndexCampoARFENOM]))
# CALCULAR CAMPOS 'ArEstudAc', 'ArFenomAc'
SomaARESTUDO = sum(ListaARESTUDO)
SomaARFENOM = sum(ListaARFENOM)
DbfTS.startEditing()
for Valores, SomaAcARESTUDO, SomaAcARFENOM in zip(
processing.features(DbfTS), numpy.cumsum(ListaARESTUDO),
numpy.cumsum(ListaARFENOM)):
if Valores.id() == 0:
DbfTS.changeAttributeValue(Valores.id(),
TS_IndexCampoArFenomAc, 0)
DbfTS.changeAttributeValue(Valores.id(),
TS_IndexCampoArEstudAc, 0)
else:
DbfTS.changeAttributeValue(
Valores.id(), TS_IndexCampoArEstudAc,
float(SomaAcARESTUDO) / float(SomaARESTUDO))
DbfTS.changeAttributeValue(
Valores.id(), TS_IndexCampoArFenomAc,
float(SomaAcARFENOM) / float(SomaARFENOM))
DbfTS.commitChanges()
# CALCULAR CAMPOS 'Lsi_Li', 'ai_b1_2'
ListaArEstudAc = []
ListaArFenomAc = []
for Valores in processing.features(DbfTS):
ListaArEstudAc.append(float(Valores[TS_IndexCampoArEstudAc]))
ListaArFenomAc.append(float(Valores[TS_IndexCampoArFenomAc]))
ListaArEstudAc.insert(0, 0)
ListaArFenomAc.insert(0, 0)
DbfTS.startEditing()
for Valores, ValoresArEstudAc, ValoresArFenomAc in zip(
processing.features(DbfTS), ListaArEstudAc,
ListaArFenomAc):
if Valores.id() == 0:
DbfTS.changeAttributeValue(Valores.id(),
TS_IndexCampoLsi_Li, 0)
DbfTS.changeAttributeValue(Valores.id(),
TS_IndexCampoai_b1_2, 0)
else:
DbfTS.changeAttributeValue(
Valores.id(), TS_IndexCampoLsi_Li,
float(Valores[TS_IndexCampoArEstudAc]) -
float(ValoresArEstudAc))
DbfTS.changeAttributeValue(
Valores.id(), TS_IndexCampoai_b1_2,
float(
float(Valores[TS_IndexCampoArFenomAc]) +
float(ValoresArFenomAc)) / float(2))
DbfTS.commitChanges()
# CALCULAR CAMPO 'AAC'
DbfTS.startEditing()
for Valores in processing.features(DbfTS):
DbfTS.changeAttributeValue(
Valores.id(), TS_IndexCampoACC,
float(Valores[TS_IndexCampoai_b1_2]) *
float(Valores[TS_IndexCampoLsi_Li]))
DbfTS.commitChanges()
# SOMAR VALORES DE ACC PARA ESCREVER A MENSAGEM
ListaACC = []
for Valores in DbfTS.getFeatures():
ListaACC.append(Valores[TS_IndexCampoACC])
SomaACC = round(sum(ListaACC), 4)
# APAGAR CAMPOS INICIAIS PROVENIENTES DO CSV
DbfTS.dataProvider().deleteAttributes(
[TS_IndexCampoV, TS_IndexCampoV1, TS_IndexCampoT])
DbfTS.updateFields()
msgBar = self.iface.messageBar()
msgBar.pushWidget(
msgBar.createMessage(
"########### O MODELO FOI VALIDADO COM UMA TAXA DE SUCESSO DE "
+ str(SomaACC) + "! ###########"), QgsMessageBar.INFO
) #"...INFO, 5)" para defenir o tempo da mensagem
hausdorff = max(distances)
return hausdorff
origin_layer = processing.getObject(origin_layer)
target_layer = processing.getObject(target_layer)
target_id_column_index = target_layer.fieldNameIndex(target_id_column_index)
"""
origin_layer = l1
target_layer = l2
target_id_column_index = 0
interval = 1
"""
target_spatial_index = QgsSpatialIndex()
target_features = processing.features(target_layer)
origin_fields = origin_layer.pendingFields().toList()
origin_fields.append(QgsField("BEST_FIT", QVariant.Int))
origin_fields.append(QgsField("HAUSDORFF", QVariant.Double))
origin_fields.append(QgsField("LEN_DIFF", QVariant.Double))
writer = VectorWriter(output, None, origin_fields,
origin_layer.dataProvider().geometryType(),
origin_layer.crs())
outFeat = QgsFeature()
# populate the spatial index
for feat in target_features:
target_spatial_index.insertFeature(feat)
import processing
from PyQt4.QtWebKit import QWebView
layer = iface.activeLayer()
values = []
features = processing.features(layer)
for f in features:
values.append(f['elev_m'])
myWV = QWebView(None)
html='<html><head><script type="text/javascript"'
html+='src="https://www.google.com/jsapi"></script>'
html+='<script type="text/javascript">'
html+='google.load("visualization","1",{packages:["corechart"]});'
html+='google.setOnLoadCallback(drawChart);'
html+='function drawChart() { '
html+='var data = google.visualization.arrayToDataTable(['
html+='["%s"],' % (field_name)
for value in values:
html+='[%f],' % (value)
html+=']);'
html+='var chart = new google.visualization.Histogram('
html+=' document.getElementById("chart_div"));'
html+='chart.draw(data, {title: "Histogram"});}</script></head>'
html+='<body><h1>Layer: %s</h1>' % (layer.name())
html+='<p>Values for %s range from: ' % (field_name)
html+='%d to %d</p>' % (min(values),max(values))
html+='<div id="chart_div"style="width:900px; height:500px;">'
html+='</div></body></html>'
def test_featuresWithoutSelection(self):
layer = processing.getObject(points())
features = processing.features(layer)
self.assertEqual(12, len(features))
def processAlgorithm(self, progress):
field = self.getParameterValue(self.FIELD)
field = field[0:10] # try to handle Shapefile field length limit
filename = self.getParameterValue(self.INPUT)
layer = dataobjects.getObjectFromUri(filename)
filename = dataobjects.exportVectorLayer(layer)
provider = layer.dataProvider()
fields = provider.fields()
fields.append(QgsField('MORANS_P', QVariant.Double))
fields.append(QgsField('MORANS_Z', QVariant.Double))
fields.append(QgsField('MORANS_Q', QVariant.Int))
fields.append(QgsField('MORANS_I', QVariant.Double))
fields.append(QgsField('MORANS_C', QVariant.Double))
writer = self.getOutputFromName(self.OUTPUT).getVectorWriter(
fields, provider.geometryType(), layer.crs() )
contiguity = self.getParameterValue(self.CONTIGUITY)
if contiguity == 'queen':
print 'INFO: Local Moran\'s using queen contiguity'
w=pysal.queen_from_shapefile(filename)
else:
print 'INFO: Local Moran\'s using rook contiguity'
w=pysal.rook_from_shapefile(filename)
f = pysal.open(pysal.examples.get_path(filename.replace('.shp','.dbf')))
y=np.array(f.by_col[str(field)])
lm = pysal.Moran_Local(y,w,transformation = "r", permutations = 999)
# http://pysal.readthedocs.org/en/latest/library/esda/moran.html?highlight=local%20moran#pysal.esda.moran.Moran_Local
# values indicate quadrat location 1 HH, 2 LH, 3 LL, 4 HL
# http://www.biomedware.com/files/documentation/spacestat/Statistics/LM/Results/Interpreting_univariate_Local_Moran_statistics.htm
# category - scatter plot quadrant - autocorrelation - interpretation
# high-high - upper right (red) - positive - Cluster - "I'm high and my neighbors are high."
# high-low - lower right (pink) - negative - Outlier - "I'm a high outlier among low neighbors."
# low-low - lower left (med. blue) - positive - Cluster - "I'm low and my neighbors are low."
# low-high - upper left (light blue) - negative - Outlier - "I'm a low outlier among high neighbors."
# http://help.arcgis.com/en/arcgisdesktop/10.0/help/index.html#/What_is_a_z_score_What_is_a_p_value/005p00000006000000/
# z-score (Standard Deviations) | p-value (Probability) | Confidence level
# < -1.65 or > +1.65 | < 0.10 | 90%
# < -1.96 or > +1.96 | < 0.05 | 95%
# < -2.58 or > +2.58 | < 0.01 | 99%
self.setOutputValue(self.P_SIM, str(lm.p_sim))
sig_q = lm.q * (lm.p_sim <= 0.01) # could make significance level an option
outFeat = QgsFeature()
i = 0
for inFeat in processing.features(layer):
inGeom = inFeat.geometry()
outFeat.setGeometry(inGeom)
attrs = inFeat.attributes()
attrs.append(float(lm.p_sim[i]))
attrs.append(float(lm.z_sim[i]))
attrs.append(int(lm.q[i]))
attrs.append(float(lm.Is[i]))
attrs.append(int(sig_q[i]))
outFeat.setAttributes(attrs)
writer.addFeature(outFeat)
i+=1
del writer
def processAlgorithm(self, progress):
field = self.getParameterValue(self.FIELD)
field = field[0:10] # try to handle Shapefile field length limit
filename = self.getParameterValue(self.INPUT)
layer = dataobjects.getObjectFromUri(filename)
filename = dataobjects.exportVectorLayer(layer)
provider = layer.dataProvider()
fields = provider.fields()
fields.append(QgsField('MORANS_P', QVariant.Double))
fields.append(QgsField('MORANS_Z', QVariant.Double))
fields.append(QgsField('MORANS_Q', QVariant.Int)) # quadrant
fields.append(QgsField('MORANS_Q_S',
QVariant.Int)) # significant quadrant
fields.append(QgsField('MORANS_I', QVariant.Double))
writer = self.getOutputFromName(self.OUTPUT).getVectorWriter(
fields, provider.geometryType(), layer.crs())
contiguity = self.getParameterValue(self.CONTIGUITY)
if self.CONTIGUITY_OPTIONS[contiguity] == 'queen':
print 'INFO: Local Moran\'s using queen contiguity'
w = pysal.queen_from_shapefile(filename)
elif self.CONTIGUITY_OPTIONS[contiguity] == 'rook':
print 'INFO: Local Moran\'s using rook contiguity'
w = pysal.rook_from_shapefile(filename)
significance_level = self.getParameterValue(self.SIGNIFICANCE_LEVEL)
if self.SIGNIFICANCE_OPTIONS[significance_level] == '90%':
max_p = 0.10
elif self.SIGNIFICANCE_OPTIONS[significance_level] == '95%':
max_p = 0.05
elif self.SIGNIFICANCE_OPTIONS[significance_level] == '99%':
max_p = 0.01
print 'INFO: significance level ' + self.SIGNIFICANCE_OPTIONS[
significance_level]
f = pysal.open(
pysal.examples.get_path(filename.replace('.shp', '.dbf')))
y = np.array(f.by_col[str(field)])
lm = pysal.Moran_Local(y, w, transformation="r", permutations=999)
# http://pysal.readthedocs.org/en/latest/library/esda/moran.html?highlight=local%20moran#pysal.esda.moran.Moran_Local
# values indicate quadrat location 1 HH, 2 LH, 3 LL, 4 HL
# http://www.biomedware.com/files/documentation/spacestat/Statistics/LM/Results/Interpreting_univariate_Local_Moran_statistics.htm
# category - scatter plot quadrant - autocorrelation - interpretation
# high-high - upper right (red) - positive - Cluster - "I'm high and my neighbors are high."
# high-low - lower right (pink) - negative - Outlier - "I'm a high outlier among low neighbors."
# low-low - lower left (med. blue) - positive - Cluster - "I'm low and my neighbors are low."
# low-high - upper left (light blue) - negative - Outlier - "I'm a low outlier among high neighbors."
# http://help.arcgis.com/en/arcgisdesktop/10.0/help/index.html#/What_is_a_z_score_What_is_a_p_value/005p00000006000000/
# z-score (Standard Deviations) | p-value (Probability) | Confidence level
# < -1.65 or > +1.65 | < 0.10 | 90%
# < -1.96 or > +1.96 | < 0.05 | 95%
# < -2.58 or > +2.58 | < 0.01 | 99%
self.setOutputValue(self.P_SIM, str(lm.p_sim))
sig_q = lm.q * (lm.p_sim <= max_p)
outFeat = QgsFeature()
i = 0
for inFeat in processing.features(layer):
inGeom = inFeat.geometry()
outFeat.setGeometry(inGeom)
attrs = inFeat.attributes()
attrs.append(float(lm.p_sim[i]))
attrs.append(float(lm.z_sim[i]))
attrs.append(int(lm.q[i]))
attrs.append(int(sig_q[i]))
attrs.append(float(lm.Is[i]))
outFeat.setAttributes(attrs)
writer.addFeature(outFeat)
i += 1
del writer
def Probabilidade(InputAA, InputLayerNameAA, InputLimite, CellSize, TempFolder, Extent):
# CRIAR SHAPEFILE "Limite" TEMPORARIO
LimiteOriginal = QgsVectorLayer(InputLimite, "LimiteOriginal", "ogr")
LimiteCopy = os.path.join(TempFolder, "LimiteCopy.shp")
processing.runalg("qgis:dissolve",LimiteOriginal,True,None,LimiteCopy)
Limite = QgsVectorLayer(LimiteCopy, "Limite", "ogr")
# CRIAR CAMPO "Limite"
CampoLimite = Limite.dataProvider().addAttributes([QgsField("Limite", QVariant.Int)])
Limite.updateFields()
Limite.startEditing()
[Limite.changeAttributeValue(Valores.id(), Limite.fieldNameIndex("Limite"), int(0)) for Valores in processing.features(Limite)]
Limite.commitChanges()
Limite.updateFields()
# APAGAR CAMPOS DESNECESSARIOS
for field in range(len(Limite.dataProvider().attributeIndexes())-1):
Limite.dataProvider().deleteAttributes([0])
Limite.updateFields()
AA = []
inc = 0
for AreasArdidas, LayerName in zip(InputAA,InputLayerNameAA):
# CLIP POR "Limite"
ClipOutput = os.path.join(TempFolder, LayerName + "_Clip.shp")
processing.runalg("qgis:clip",AreasArdidas,Limite,ClipOutput)
LoadAA = QgsVectorLayer(ClipOutput, LayerName, "ogr")
FeatureList = []
for f in LoadAA.getFeatures():
FeatureList.append(f)
if len(FeatureList) == 0:
LimiteGeometryList = []
for feature in Limite.getFeatures():
LimiteGeometryList.append(feature)
LoadAA.startEditing()
DataProvider = LoadAA.dataProvider()
DataProvider.addFeatures(LimiteGeometryList)
LoadAA.commitChanges()
# CRIAR CAMPOS "ANO"
inc +=1
CampoName = "A_" + str(inc)
CampoAno = LoadAA.dataProvider().addAttributes([QgsField(CampoName, QVariant.Int)])
LoadAA.updateFields()
CampoAnoIndex = LoadAA.fieldNameIndex(CampoName)
LoadAA.startEditing()
if len(FeatureList) == 0:
[LoadAA.changeAttributeValue(Valores.id(), CampoAnoIndex, int(0)) for Valores in processing.features(LoadAA)]
else:
[LoadAA.changeAttributeValue(Valores.id(), CampoAnoIndex, int(1)) for Valores in processing.features(LoadAA)]
LoadAA.commitChanges()
LoadAA.updateFields()
# APAGAR CAMPOS DESNECESSARIOS
for field in range(len(LoadAA.dataProvider().attributeIndexes())-1):
LoadAA.dataProvider().deleteAttributes([0])
LoadAA.updateFields()
AA.append(LoadAA)
# EXECUTAR UNION
UnionAnos = []
for incremento in range(0, len(AA)-1):
if incremento == 0:
processing.runalg("saga:union",AA[0],AA[1],True, os.path.join(TempFolder, "Union_" + str(incremento)+ ".shp"))
else:
UnionAnos = os.path.join(TempFolder, "Union_" + str(incremento)+ ".shp")
processing.runalg("saga:union",os.path.join(TempFolder, "Union_" + str(incremento-1)+ ".shp"),AA[incremento + 1],True, UnionAnos)
OutputUnion = os.path.join(TempFolder, "Probabilidade.shp")
processing.runalg("saga:union",UnionAnos,Limite,True, OutputUnion)
### CALCULAR PROBABILIDADE
Probabilidade = QgsVectorLayer(OutputUnion, "Probabilidade", "ogr")
ExpressaoAppend = []
for field in Probabilidade.dataProvider().attributeIndexes():
ExpressaoAppend.append("float(Valores["+str(field) + "]) ")
ExpressaoProb = '+ '.join(ExpressaoAppend)
NrCampos = int(len(ExpressaoAppend)-1)
CampoProb = Probabilidade.dataProvider().addAttributes([QgsField("PROB", QVariant.Double)])
Probabilidade.updateFields()
CampoProbIndex = Probabilidade.fieldNameIndex("PROB")
Probabilidade.startEditing()
for Valores in processing.features(Probabilidade):
Probabilidade.changeAttributeValue(Valores.id(), CampoProbIndex, eval(ExpressaoProb)/float(NrCampos)*100)
Probabilidade.commitChanges()
Probabilidade.updateFields()
Probabilidade.startEditing()
for Valores in processing.features(Probabilidade):
if (Valores[CampoProbIndex] == 0) or (Valores[CampoProbIndex] <= ((1.0/float(NrCampos)*100)+0.000000000005)):
Probabilidade.changeAttributeValue(Valores.id(), CampoProbIndex, float(1))
Probabilidade.commitChanges()
Probabilidade.updateFields()
processing.runalg("grass7:v.to.rast.attribute",Probabilidade,0,"PROB",Extent,CellSize,-1,0.0001, os.path.join(OutputFolder, "probabilidade.tif"))
def run(self):
layer=self.iface.activeLayer()
if layer and layer.dataProvider().capabilities() & QgsVectorDataProvider.ChangeGeometries:
parts_before_total = 0
parts_after_total = 0
parts_included_total = 0
done_anything=False
for feature in processing.features(layer):
geom = feature.geometry()
if geom.type() == QGis.Line and geom.isMultipart():
parts = geom.asMultiPolyline()
lineparts = []
for px in range(0, len(parts)):
if len(parts[px]) > 1:
lp = Linepart(px, parts[px])
lineparts.append(lp)
for px in range(0, len(lineparts)):
for px2 in range(px + 1, len(lineparts)):
lineparts[px].maybe_connect_with(lineparts[px2])
seen = {}
included = {}
new_parts = []
for pa in lineparts:
if pa in seen:
continue
if pa.disabled():
continue
seen[pa]=True
points = []
abort_part=False
pa_last=pa
pa_curr=pa.at_start()
while pa_curr:
if pa_curr == pa:
# multi-part loop detected. multi-part loops are ambiguous since
# where should the start/endpoint be?
#
# all parts in the loop are now marked
# as seen since we are back were we
# started and we will just abort.
abort_part=True
break
seen[pa_curr]=True
shpt1, p, shpt2, pa_next =pa_curr.traverse_from(pa_last)
p.reverse()
points[0:0] = p + [shpt1]
included[pa_curr]=True
pa_last=pa_curr
pa_curr=pa_next
if abort_part:
continue
points.extend(pa.points_start_to_end())
included[pa]=True
pa_last=pa
pa_curr=pa.at_end()
while pa_curr:
seen[pa_curr]=True
shpt1, p, shpt2, pa_next=pa_curr.traverse_from(pa_last)
points.extend([shpt1] + p)
included[pa_curr]=True
pa_last=pa_curr
pa_curr=pa_next
new_parts.append(points)
# print "feature", feature, "(",feature.id(),")-----"
# print "parts before:", len(parts)
# print "parts after:", len(new_parts)
# np=0
# for p in parts:
# np+=len(p)
# print "number of points before:", np
# np=0
# for p in new_parts:
# np+=len(p)
# print "number of points after:", np
# print "-----"
if len(parts) != len(new_parts):
if not done_anything:
done_anything=True
layer.beginEditCommand("Multiline Join")
g = QgsGeometry.fromMultiPolyline(new_parts)
layer.changeGeometry(feature.id(), g)
# layer.addFeatures([f])
parts_before_total += len(parts)
parts_after_total += len(new_parts)
parts_included_total += len(included)
if done_anything:
# print "actually did modify something"
layer.endEditCommand()
layer.triggerRepaint()
self.iface.messageBar().pushMessage("Multiline Join",
str(parts_included_total) + "/" + str(parts_before_total) + \
" parts -> " + str(parts_after_total) + " parts", level=QgsMessageBar.INFO)
def test_featuresWithoutSelection(self):
layer = processing.getObject(points())
features = processing.features(layer)
self.assertEqual(12, len(features))
def calculateFields(self, listKeep, listStats, output):
# get selected layer
index = self.ui.comboLayerList.currentIndex()
legendInterface = self.iface.legendInterface()
listLayers = [
layer for layer in legendInterface.layers()
if layer.type() == QgsMapLayer.VectorLayer
]
selectedLayer = listLayers[index]
# iterates over layer features to get attributes as a list of lists
# uses the processing method so as to get only selected features if this option is set in the processing options
iter = processing.features(selectedLayer)
attrs = [feature.attributes() for feature in iter]
# get all values of the dissolve field (before processing : with duplicate values)
indexDissolveField = self.ui.comboFieldList.currentIndex()
valuesDissolveField = [
feature[indexDissolveField] for feature in attrs
]
# get unique values for dissolve field, from output (seems more secure than to get it from valuesDissolveField ?)
outputLayer = QgsVectorLayer(output, "name", "ogr")
provider = outputLayer.dataProvider()
fields = provider.fields()
listFieldNames = [field.name() for field in fields]
iter = outputLayer.getFeatures()
uniqueValuesDissolveField = [
feature.attributes()[indexDissolveField] for feature in iter
]
# initializes list of lists which will contain results (it will have one element per kept field)
listRes = []
# trick for dissolve field, if kept
if listKeep[indexDissolveField] == 2:
listStats[indexDissolveField] = 'First'
# for each kept field
for i in range(len(listFieldNames)):
if listKeep[i] == 2:
# creates list which will contain attribute values for current field, one empty element per unique dissolve field value
listAttrs = [[]
for val in range(len(uniqueValuesDissolveField))]
# fill this list with all the current field values corresponding to each dissolve field value
valuesField = [feature[i] for feature in attrs]
for (x, y) in zip(valuesDissolveField, valuesField):
listAttrs[uniqueValuesDissolveField.index(x)].append(y)
# removes any NULL values
listAttrs = [[x for x in l if x] for l in listAttrs]
# for each list in listAttrs, calculates one value according to the chosen stat
# if list is empty (can happen if it contained originally only NULL values), return NULL as a result
if listStats[i] == "Mean":
listAttrs = [
sum(y) / len(y) if y else NULL for y in listAttrs
]
elif listStats[i] == "Sum":
listAttrs = [sum(y) if y else NULL for y in listAttrs]
elif listStats[i] == "Min":
listAttrs = [min(y) if y else NULL for y in listAttrs]
elif listStats[i] == "Max":
listAttrs = [max(y) if y else NULL for y in listAttrs]
elif listStats[i] == "Count":
listAttrs = [len(y) if y else NULL for y in listAttrs]
elif listStats[i] == "First":
listAttrs = [y[0] if y else NULL for y in listAttrs]
elif listStats[i] == "Last":
listAttrs = [y[-1] if y else NULL for y in listAttrs]
elif listStats[i] == "Median":
listAttrs = [
self.median(y) if y else NULL for y in listAttrs
]
elif listStats[i] == "Standard deviation":
listAttrs = [
self.standard_dev(y) if y else NULL for y in listAttrs
]
elif listStats[i] == "Concatenation":
listAttrs = [
", ".join(y) if y else NULL for y in listAttrs
]
elif listStats[i] == "Uniquification":
listAttrs = [
", ".join(set(y)) if y else NULL for y in listAttrs
]
# append each field result to listRes
listRes.append(listAttrs)
return listRes
def processAlgorithm(self, progress):
progress.setPercentage(0)
# Retrieve the values of the parameters entered by the user
roadsLayer = dataobjects.getObjectFromUri(
self.getParameterValue(self.ROADS_LAYER))
gridLayer = dataobjects.getObjectFromUri(
self.getParameterValue(self.GRID_LAYER))
vertIdField = self.getParameterValue(self.VERT_ID_FIELD)
stress = self.getParameterValue(self.STRESS)
# build the output layer
outFields = QgsFields()
outFields.append(QgsField('grid_id', QVariant.Int))
outFields.append(QgsField('status',QVariant.String))
outFields.append(QgsField('free_cost', QVariant.Int))
outFields.append(QgsField('cnst_cost', QVariant.Int))
outFields.append(QgsField('cost_ratio', QVariant.Double))
writer = self.getOutputFromName(self.OUTPUT_LAYER).getVectorWriter(
outFields, QGis.WKBPolygon, roadsLayer.crs())
progress.setPercentage(2)
# establish db connection
progress.setInfo('Getting DB connection')
self.setDbFromRoadsLayer(roadsLayer)
self.setLayersFromDb()
# get network
progress.setInfo('Building network')
nu = NXUtils(self.vertsLayer,self.linksLayer)
nu.buildNetwork()
DG = nu.getNetwork()
SG = nu.getStressNetwork(stress)
progress.setPercentage(10)
graphCosts = nx.get_edge_attributes(DG,'weight')
#get grid feature and vert id
progress.setText('Reading selected feature(s)')
selectedGridFeatures = processing.features(gridLayer)
if not len(selectedGridFeatures) == 1:
raise GeoAlgorithmExecutionException('You must select one and only one feature in the grid layer')
gridFeature = QgsFeature()
for i, f in enumerate(selectedGridFeatures):
gridFeature = f
sourceVertId = gridFeature.attribute(vertIdField)
#test for source feature not having any low stress connections
if not SG.has_node(sourceVertId):
raise GeoAlgorithmExecutionException('The selected grid cell has no low stress connections')
#iterate grid features and compile scores
progress.setText('Generating grid scores')
#helper function to sum costs from graph
def sumCosts(nodes,graphWeights):
cost = 0
del nodes[1] #remove the source and target nodes from consideration
del nodes[-1]
for j, node in enumerate(nodes):
try:
cost = cost + graphCosts[(node,nodes[j+1])]
except:
pass
return cost
#gridProvider = grid.dataProvider()
gridFeatures = gridLayer.getFeatures()
for i, gf in enumerate(gridFeatures):
targetVertId = gf.attribute(vertIdField)
progress.setInfo('from: ' + str(sourceVertId) + ' to: ' + str(targetVertId))
#write new feature
progress.setText('Writing grid feature')
newFeat = QgsFeature()
newGeom = QgsGeometry(gf.geometry())
newFeat.setGeometry(newGeom)
newFeat.initAttributes(5)
newFeat.setAttribute(0,gf.attribute(vertIdField))
if targetVertId == sourceVertId:
newFeat.setAttribute(1,'Source cell')
elif not SG.has_node(targetVertId):
newFeat.setAttribute(1,'Unreachable')
elif not nx.has_path(SG,source=sourceVertId,target=targetVertId):
newFeat.setAttribute(1,'Unreachable')
else:
#get shortest path without stress
pathNoStress = nx.shortest_path(DG,source=sourceVertId,target=targetVertId,weight='weight')
#get shortest path with stress
pathStress = nx.shortest_path(SG,source=sourceVertId,target=targetVertId,weight='weight')
#get cost values
costNoStress = sumCosts(pathNoStress,graphCosts)
costStress = sumCosts(pathStress,graphCosts)
#add attributes
newFeat.setAttribute(1,'Target cell')
newFeat.setAttribute(2,costNoStress)
newFeat.setAttribute(3,costStress)
if costNoStress == 0:
pass
else:
newFeat.setAttribute(4,float(costStress)/float(costNoStress))
writer.addFeature(newFeat)
del writer
from math import sqrt
t_start = datetime.now()
print '{0}: Clustering using KMeans'.format(t_start)
layer = processing.getObject(input)
provider = layer.dataProvider()
fields = provider.fields()
fields.append(QgsField('CLUSTER', QVariant.Int))
fields.append(QgsField('CLUSTER_N', QVariant.Int))
writer = VectorWriter(kmeans_output, None,fields, provider.geometryType(), layer.crs() )
# Perform clustering
X = []
for edge in processing.features(layer):
geom = edge.geometry()
azimuth = geom.vertexAt(0).azimuth(geom.vertexAt(1))/4
X.append([geom.vertexAt(0).x(),geom.vertexAt(0).y()])
X.append([geom.vertexAt(1).x(),geom.vertexAt(1).y()])
db = KMeans(n_clusters=edge_point_clusters).fit(X)
pt_labels = list(db.labels_)
# labels[0] = cluster of line0 start
# labels[1] = cluster of line0 end
# labels[2] = cluster of line1 start
# labels[3] = cluster of line1 end
# ...
import processing
layer = iface.legendInterface().layers()[0] #if only one layer or find better way to do this
features = processing.features(layer)
#OR
count = 0
depths = []
for feature in layer.getFeatures(): #getFeatures() returns an interator of the layer's features
depths.append([count, feature.attributes()[-2]])
count +=1
#To get field by name rather than index:
idx = layer.fieldNameIndex('name')
for feature in layer.getFeatures():
depths.append(feature.attributes()[idx])
#add field to shp with ogr: (can be done while shp is open in qgis)
from osgeo import ogr
def calculateFields(listStats, output):
# iterates over input layer features to get attributes as a list of lists
# uses the processing method so as to get only selected features if this option is set in the processing options
iter = processing.features(inputLayer)
attrs = [feature.attributes() for feature in iter]
# get index of dissolve field
provider = inputLayer.dataProvider()
fields = provider.fields()
listFieldNames = [field.name() for field in fields]
indexDissolveField = listFieldNames.index(Dissolve_field)
# get all values of the dissolve field (before processing : with duplicate values)
valuesDissolveField = [feature[indexDissolveField] for feature in attrs]
# get unique values for dissolve field, from output (seems more secure than to get it from valuesDissolveField ?)
outputLayer = QgsVectorLayer(output, "name", "ogr")
provider = dissolveLayer.dataProvider()
fields = provider.fields()
listFieldNames = [field.name() for field in fields]
iter = outputLayer.getFeatures()
uniqueValuesDissolveField = [
feature.attributes()[indexDissolveField] for feature in iter
]
# initializes list of lists which will contain results (it will have one element per kept field)
listRes = []
# for each kept field
for i in range(len(listFieldNames)):
if listStats[i] != 'no':
# creates list which will contain attribute values for current field, one empty element per unique dissolve field value
listAttrs = [[] for val in range(len(uniqueValuesDissolveField))]
# fill this list with all the current field values corresponding to each dissolve field value
valuesField = [feature[i] for feature in attrs]
for (x, y) in zip(valuesDissolveField, valuesField):
listAttrs[uniqueValuesDissolveField.index(x)].append(y)
# removes any NULL values
listAttrs = [[x for x in l if x] for l in listAttrs]
# for each list in listAttrs, calculates one value according to the chosen stat
# if list is empty (can happen if it contained originally only NULL values), return NULL as a result
if listStats[i] == "mean":
listAttrs = [sum(y) / len(y) if y else NULL for y in listAttrs]
elif listStats[i] == "sum":
listAttrs = [sum(y) if y else NULL for y in listAttrs]
elif listStats[i] == "min":
listAttrs = [min(y) if y else NULL for y in listAttrs]
elif listStats[i] == "max":
listAttrs = [max(y) if y else NULL for y in listAttrs]
elif listStats[i] == "count":
listAttrs = [len(y) if y else NULL for y in listAttrs]
elif listStats[i] == "first":
listAttrs = [y[0] if y else NULL for y in listAttrs]
elif listStats[i] == "last":
listAttrs = [y[-1] if y else NULL for y in listAttrs]
elif listStats[i] == "median":
listAttrs = [self.median(y) if y else NULL for y in listAttrs]
elif listStats[i] == "sd":
listAttrs = [
self.standard_dev(y) if y else NULL for y in listAttrs
]
elif listStats[i] == "concat":
listAttrs = [", ".join(y) if y else NULL for y in listAttrs]
elif listStats[i] == "unique":
listAttrs = [
", ".join(set(y)) if y else NULL for y in listAttrs
]
# append each field result to listRes
listRes.append(listAttrs)
return listRes
hausdorff = max(distances)
return hausdorff
origin_layer = processing.getObject(origin_layer)
target_layer = processing.getObject(target_layer)
target_id_column_index = target_layer.fieldNameIndex(target_id_column_index)
"""
origin_layer = l1
target_layer = l2
target_id_column_index = 0
interval = 1
"""
target_spatial_index = QgsSpatialIndex()
target_features = processing.features(target_layer)
origin_fields = origin_layer.pendingFields().toList()
origin_fields.append( QgsField("BEST_FIT", QVariant.Int ))
origin_fields.append( QgsField("HAUSDORFF", QVariant.Double ))
origin_fields.append( QgsField("LEN_DIFF", QVariant.Double ))
writer = VectorWriter(output, None, origin_fields, origin_layer.dataProvider().geometryType(), origin_layer.crs() )
outFeat = QgsFeature()
# populate the spatial index
for feat in target_features:
target_spatial_index.insertFeature(feat)
origin_features = processing.features(origin_layer)
for origin_feature in origin_features:
import qgis.gui
VonSchacht = 0
BisSchacht = 0
bis_schacht = 1
sTime = time.time()
haltungen = []
selected_FeatureCount = 0
VonBisSchacht = []
logging.basicConfig(level=logging.DEBUG)
layer_haltungen = QgsMapLayerRegistry.instance().mapLayersByName("Haltungen 20180308")[0]
layer_haltungen.isValid()
layer_schacht = QgsMapLayerRegistry.instance().mapLayersByName("Normschacht 20180308")[0]
# layer_selectedHaltungen = QgsMapLayerRegistry.instance().mapLayersByName("Haltungen 20180308 copy")[0]
features_selectedHaltungen = processing.features(layer_haltungen)
# print("Haltungen-For:")
for feature in features_selectedHaltungen:
try:
# print("Start des Haltungs-For-Loop")
layer_haltungen.setSelectedFeatures([])
iface.mapCanvas().setSelectionColor( QColor("yellow"))
fid = int(feature.id())
layer_haltungen.setSelectedFeatures([fid])
# print "Feature ID %d: " % feature.id()
processing.runalg("preconfigured:normschacht")
features_schacht = processing.features(layer_schacht)
# for f in features_schacht:
# if f['Funktion'] == 6:
# logging.DEBUG("Break")
def option1_2():
peso = 0
features = processing.features(layer)
for feature in features:
peso += feature['peso']
print("peso", peso)
# category - scatter plot quadrant - autocorrelation - interpretation
# high-high - upper right (red) - positive - Cluster - "I'm high and my neighbors are high."
# high-low - lower right (pink) - negative - Outlier - "I'm a high outlier among low neighbors."
# low-low - lower left (med. blue) - positive - Cluster - "I'm low and my neighbors are low."
# low-high - upper left (light blue) - negative - Outlier - "I'm a low outlier among high neighbors."
# http://help.arcgis.com/en/arcgisdesktop/10.0/help/index.html#/What_is_a_z_score_What_is_a_p_value/005p00000006000000/
# z-score (Standard Deviations) | p-value (Probability) | Confidence level
# < -1.65 or > +1.65 | < 0.10 | 90%
# < -1.96 or > +1.96 | < 0.05 | 95%
# < -2.58 or > +2.58 | < 0.01 | 99%
sig_q = lm.q * (lm.p_sim <= 0.01) # could make significance level an option
outFeat = QgsFeature()
i = 0
for inFeat in processing.features(layer):
inGeom = inFeat.geometry()
outFeat.setGeometry(inGeom)
attrs = inFeat.attributes()
attrs.append(float(lm.p_sim[i]))
attrs.append(float(lm.z_sim[i]))
attrs.append(int(lm.q[i]))
attrs.append(float(lm.Is[i]))
attrs.append(int(sig_q[i]))
outFeat.setAttributes(attrs)
writer.addFeature(outFeat)
i+=1
del writer
def test_SagaVectorAlgorithWithUnsupportedInputAndOutputFormat(self):
'''this tests both the exporting to shp and then the format change in the output layer'''
layer = processing.getObject(polygonsGeoJson());
feature = layer.getFeatures().next()
selected = [feature.id()]
layer.setSelectedFeatures(selected)
outputs=processing.runalg("saga:polygoncentroids",polygonsGeoJson(),True, getTempFilename("geojson"))
layer.setSelectedFeatures([])
output=outputs['CENTROIDS']
layer=dataobjects.getObjectFromUri(output, True)
fields=layer.pendingFields()
expectednames=['ID','POLY_NUM_A','POLY_ST_A']
expectedtypes=['Real','Real','String']
names=[str(f.name()) for f in fields]
types=[str(f.typeName()) for f in fields]
self.assertEqual(expectednames, names)
self.assertEqual(expectedtypes, types)
features=processing.features(layer)
self.assertEqual(1, len(features))
feature=features.next()
attrs=feature.attributes()
expectedvalues=["0","1.1","string a"]
values=[str(attr) for attr in attrs]
self.assertEqual(expectedvalues, values)
wkt='POINT(270787.49991451 4458955.46775295)'
self.assertEqual(wkt, str(feature.geometry().exportToWkt()))
