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FlowsAlgorithms.py
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# -*- coding: utf-8 -*-
"""
/***************************************************************************
Thematic
A QGIS plugin
Thematic cartography tools for processing
Generated by Plugin Builder: http://g-sherman.github.io/Qgis-Plugin-Builder/
-------------------
begin : 2018-07-19
copyright : (C) 2018 by Lionel Cacheux
email : [email protected]
***************************************************************************/
/***************************************************************************
* *
* This program is free software; you can redistribute it and/or modify *
* it under the terms of the GNU General Public License as published by *
* the Free Software Foundation; either version 2 of the License, or *
* (at your option) any later version. *
* *
***************************************************************************/
"""
__author__ = 'Lionel Cacheux'
__date__ = '2018-07-19'
__copyright__ = '(C) 2018 by Lionel Cacheux'
# This will get replaced with a git SHA1 when you do a git archive
__revision__ = '$Format:%H$'
from PyQt5.QtCore import QCoreApplication
from qgis.PyQt.QtCore import QVariant
import os, math
from PyQt5.QtGui import (QIcon, QColor)
from qgis.core import (QgsProcessing,
QgsProject,
QgsMessageLog,
QgsFeatureSink,
QgsProcessingAlgorithm,
QgsProcessingParameterFeatureSource,
QgsProcessingParameterVectorLayer,
QgsCoordinateReferenceSystem,
QgsProcessingParameterNumber,
QgsProcessingParameterFeatureSink,
QgsFeatureRequest,
QgsField,
QgsProcessingParameterVectorDestination,
QgsProcessingParameterEnum,
QgsProcessingParameterField,
QgsProcessingParameterDefinition,
QgsFeature,
QgsVectorLayer,
QgsGeometry,
QgsDistanceArea,
QgsSimpleLineSymbolLayer,
QgsProcessingUtils,
QgsArrowSymbolLayer,
QgsSymbol,
QgsPoint,
QgsProcessingParameterBoolean,
QgsExpressionContextUtils,
QgsProcessingParameterString,
QgsProperty,
QgsWkbTypes)
import processing
from qgis.utils import iface
class CreateLinesAlgorithm(QgsProcessingAlgorithm):
"""
This is an example algorithm that takes a vector layer and
creates a new identical one.
It is meant to be used as an example of how to create your own
algorithms and explain methods and variables used to do it. An
algorithm like this will be available in all elements, and there
is not need for additional work.
All Processing algorithms should extend the QgsProcessingAlgorithm
class.
"""
# Constants used to refer to parameters and outputs. They will be
# used when calling the algorithm from another algorithm, or when
# calling from the QGIS console.
OUTPUT_LAYER = 'OUTPUT_LAYER'
INPUT = 'INPUT'
ORIGIN = 'ORIGIN'
DESTINATION = 'DESTINATION'
STOCK = 'STOCK'
INPUT2 = 'INPUT2'
MIN_FLOW = 'MIN_FLOW'
MAX_DIST = 'MAX_DIST'
CODGEO = 'CODGEO'
def initAlgorithm(self, config):
"""
Here we define the inputs and output of the algorithm, along
with some other properties.
"""
# We add the input vector features source. It can have any kind of
# geometry.
self.addParameter(
QgsProcessingParameterFeatureSource(
self.INPUT,
self.tr("Flow table"),
[QgsProcessing.TypeVector]
)
)
self.addParameter(QgsProcessingParameterField(
self.ORIGIN,
self.tr("Origin"),
None,
self.INPUT,
QgsProcessingParameterField.String,
False
)
)
self.addParameter(QgsProcessingParameterField(
self.DESTINATION,
self.tr("Destination"),
None,
self.INPUT,
QgsProcessingParameterField.String,
False
)
)
self.addParameter(QgsProcessingParameterField(
self.STOCK,
self.tr("Flow value"),
None,
self.INPUT,
QgsProcessingParameterField.Numeric,
optional=True
)
)
self.addParameter(
QgsProcessingParameterFeatureSource(
self.INPUT2,
self.tr("Localisation layer"),
[QgsProcessing.TypeVectorPolygon,QgsProcessing.TypeVectorPoint],
optional=False
)
)
self.addParameter(QgsProcessingParameterField(
self.CODGEO,
self.tr("Geographical ID"),
None,
self.INPUT2,
QgsProcessingParameterField.String,
False
)
)
# We add a feature sink in which to store our processed features (this
# usually takes the form of a newly created vector layer when the
# algorithm is run in QGIS).
'''
self.addParameter(
QgsProcessingParameterFeatureSink(
self.OUTPUT,
self.tr('Output layer')
)
)
'''
params = []
params.append(
QgsProcessingParameterNumber(
self.MIN_FLOW,
self.tr("Minimum flow"),
defaultValue=0,
minValue=0,
optional=False
)
)
params.append(
QgsProcessingParameterNumber(
self.MAX_DIST,
self.tr("Maximum distance (in km)"),
defaultValue=0,
minValue=0,
optional=False
)
)
for param in params:
param.setFlags(param.flags() | QgsProcessingParameterDefinition.FlagAdvanced)
self.addParameter(param)
self.addParameter(
QgsProcessingParameterFeatureSink(
self.OUTPUT_LAYER,
self.tr("Oursins"),
type=QgsProcessing.TypeVectorPolygon
)
)
def processAlgorithm(self, parameters, context, feedback):
"""
Here is where the processing itself takes place.
"""
# Retrieve the feature source and sink. The 'dest_id' variable is used
# to uniquely identify the feature sink, and must be included in the
# dictionary returned by the processAlgorithm function.
# INPUT = parameters[self.INPUT]
# print(self.INPUT.extent())
# print(INPUT)
# definition : flowList(self, flowTable, indexOrigin, indexDestination, indexValue, coordinatesDictionnary, minValue, maxDistance)
# self.flowList(inputTable, originIndex, destinationIndex, valueIndex, coordinates, minValue, maxDistanceKM)
inputTable = self.parameterAsSource(parameters, self.INPUT, context).materialize(QgsFeatureRequest())
geographicIdName = self.parameterAsString(parameters, self.CODGEO , context)
geometryLayer = self.parameterAsSource(parameters, self.INPUT2, context).materialize(QgsFeatureRequest())
codgeoIndex = geometryLayer.fields().indexOf(geographicIdName)
crsString = geometryLayer.crs().authid()
# extract coordinates of the centroid of the geometryLayer as a dictionary
coordinatesDictionnary = {}
features = geometryLayer.getFeatures()
for elem in features:
centroid = elem.geometry().centroid().asPoint()
IDvalue = elem.attributes()[codgeoIndex]
coordinatesDictionnary[IDvalue] = centroid
originField = self.parameterAsString(parameters, self.ORIGIN , context)
originFieldIndex = inputTable.fields().indexOf(originField)
feedback.pushInfo("__________________")
feedback.pushInfo(self.tr("Lines"))
feedback.pushInfo(" ")
feedback.pushInfo(" • {0}".format(self.tr("Values")))
feedback.pushInfo(" • {0} : {1}, [{2}]".format(self.tr("Origin"),
originField,originFieldIndex+1))
destinationField = self.parameterAsString(parameters, self.DESTINATION , context)
destinationFieldIndex = inputTable.fields().indexOf(destinationField)
feedback.pushInfo(" • {0} : {1}, [{2}]".format(self.tr("Destination"),
destinationField,destinationFieldIndex+1))
valueField = self.parameterAsString(parameters, self.STOCK , context)
valueFieldIndex = inputTable.fields().indexOf(valueField)
feedback.pushInfo(" • {0} : {1}, [{2}]".format(self.tr("value"),
valueField,valueFieldIndex+1))
minValue = self.parameterAsDouble(parameters, self.MIN_FLOW , context)
feedback.pushInfo(self.tr("Filter"))
feedback.pushInfo(" • {0} : {1}".format(self.tr("Minimum flow"),
minValue))
maxDistanceKM = self.parameterAsDouble(parameters, self.MAX_DIST , context)
feedback.pushInfo(" • {0} : {1} km ({2})".format(self.tr("Maximum distance"),
maxDistanceKM,
self.tr("0 = not defined")))
feedback.pushInfo("__________________")
vl = QgsVectorLayer("LineString?crs="+crsString, "temp", 'memory')
pr = vl.dataProvider()
pr.addAttributes([(QgsField("ORIGINE", QVariant.String)),
(QgsField("DEST", QVariant.String)),
(QgsField("FLUX", QVariant.Double)),
(QgsField("DIST_KM", QVariant.Double))])
vl.updateFields()
notInLayer = 0
maxValue = max([abs(item.attributes()[valueFieldIndex]) for item in inputTable.getFeatures()])
# feedback.pushInfo(" • valeur maximale : {0}".format(maxValue))
for elem in inputTable.getFeatures():
value = float(elem.attributes()[valueFieldIndex])
try:
pointA = coordinatesDictionnary[elem.attributes()[originFieldIndex]]
pointB = coordinatesDictionnary[elem.attributes()[destinationFieldIndex]]
if pointA != pointB and (value >= minValue or minValue ==0):
line = (pointA,pointB)
d = QgsDistanceArea()
distance = d.measureLine(pointA,pointB)/1000
if (maxDistanceKM == 0 or distance <= maxDistanceKM):
f = QgsFeature()
f.setGeometry(QgsGeometry.fromPolylineXY(line))
f.setAttributes([elem.attributes()[originFieldIndex],
elem.attributes()[destinationFieldIndex],
value,
distance])
pr.addFeature(f)
except:
# commune manquante dans le fond de carte
pass
vl.updateExtents()
vl.renderer().symbol().setWidth(3)
# Add features to the sink
(sink, dest_id) = self.parameterAsSink(parameters, self.OUTPUT_LAYER, context,
vl.fields(), QgsWkbTypes.LineString, vl.crs())
# vl.triggerRepaint()
features = vl.getFeatures()
for feature in features:
sink.addFeature(feature, QgsFeatureSink.FastInsert)
self.dest_id = dest_id
# Return the results of the algorithm. In this case our only result is
# the feature sink which contains the processed features, but some
# algorithms may return multiple feature sinks, calculated numeric
# statistics, etc. These should all be included in the returned
# dictionary, with keys matching the feature corresponding parameter
# or output names.
return {self.OUTPUT_LAYER: dest_id}
def postProcessAlgorithm(self, context, feedback):
# Styling the arrows
output = QgsProcessingUtils.mapLayerFromString(self.dest_id, context)
output.renderer().symbol().symbolLayers()[0].setWidth(0.1)
output.renderer().symbol().symbolLayers()[0].setColor(QColor('Black'))
output.triggerRepaint()
return {self.OUTPUT_LAYER: self.dest_id}
def name(self):
"""
Returns the algorithm name, used for identifying the algorithm. This
string should be fixed for the algorithm, and must not be localised.
The name should be unique within each provider. Names should contain
lowercase alphanumeric characters only and no spaces or other
formatting characters.
"""
return 'automaticflowlines'
def displayName(self):
"""
Returns the translated algorithm name, which should be used for any
user-visible display of the algorithm name.
"""
return self.tr('Oursins')
def group(self):
"""
Returns the name of the group this algorithm belongs to. This string
should be localised.
"""
return self.tr('Flows and movements')
def groupId(self):
"""
Returns the unique ID of the group this algorithm belongs to. This
string should be fixed for the algorithm, and must not be localised.
The group id should be unique within each provider. Group id should
contain lowercase alphanumeric characters only and no spaces or other
formatting characters.
"""
return 'flows'
def tr(self, string):
return QCoreApplication.translate('CreateLinesAlgorithm', string)
def createInstance(self):
return CreateLinesAlgorithm()
def icon(self):
return QIcon(os.path.dirname(__file__) + '/images/oursins.png')
def shortHelpString(self):
"""
Returns a localised short helper string for the algorithm. This string
should provide a basic description about what the algorithm does and the
parameters and outputs associated with it..
"""
return self.tr("<center><img src='{0}/images/helper/oursins_h.png' ></center> \
<p> Génère un fond d’oursins représentant les liens ou les flux entre deux points de la carte sans tenir compte de leur intensité<p>\
<p> La <b>table de flux</b> doit contenir l’<b>origine</b>, la <b>destination</b> et la valeur de chaque <b>flux </b>à représenter</p> \
<p>Le <b>fond de géolocalisation</b> sert à obtenir les coordonnées de l’origine et de la destination de chaque flux à partir de l’<b>identifiant code géographique</b><p>\
<p><b>Les paramètres avancés </b>permettent de filtrer les flux selon leur intensité (<b>flux minimum</b>) et une <b>distance maximale</b> <p>".format(os.path.dirname(__file__)))
class ShortenLinesAlgorithm(QgsProcessingAlgorithm):
"""
This is an example algorithm that takes a vector layer and
creates a new identical one.
It is meant to be used as an example of how to create your own
algorithms and explain methods and variables used to do it. An
algorithm like this will be available in all elements, and there
is not need for additional work.
All Processing algorithms should extend the QgsProcessingAlgorithm
class.
"""
# Constants used to refer to parameters and outputs. They will be
# used when calling the algorithm from another algorithm, or when
# calling from the QGIS console.
OUTPUT_LAYER = 'OUTPUT_LAYER'
INPUT = 'INPUT'
DISTANCE = 'DISTANCE'
TARGET = 'TARGET'
STOCK = 'STOCK'
def initAlgorithm(self, config):
"""
Here we define the inputs and output of the algorithm, along
with some other properties.
"""
# We add the input vector features source. It can have any kind of
# geometry.
self.addParameter(
QgsProcessingParameterFeatureSource(
self.INPUT,
self.tr('Line layer'),
[QgsProcessing.TypeVectorLine]
)
)
self.targetList = [self.tr('from origin'), self.tr('from destination')]
self.addParameter(QgsProcessingParameterEnum(
self.TARGET,
self.tr('Shorten the lines'),
defaultValue = 0,
options=self.targetList
)
)
self.addParameter(QgsProcessingParameterNumber(
self.DISTANCE,
self.tr('Distance (in km)'),
defaultValue=10,
minValue = 1,
optional=False
)
)
self.addParameter(QgsProcessingParameterField(
self.STOCK,
self.tr('Value'),
None,
self.INPUT,
QgsProcessingParameterField.Numeric,
optional=True
)
)
self.addParameter(
QgsProcessingParameterFeatureSink(
self.OUTPUT_LAYER,
self.tr('Reduced oursins'),
type=QgsProcessing.TypeVectorPolygon
)
)
def processAlgorithm(self, parameters, context, feedback):
"""
Here is where the processing itself takes place.
"""
# Retrieve the feature source and sink. The 'dest_id' variable is used
# to uniquely identify the feature sink, and must be included in the
# dictionary returned by the processAlgorithm function.
# INPUT = parameters[self.INPUT]
# print(self.INPUT.extent())
# print(INPUT)
# definition : flowList(self, flowTable, indexOrigin, indexDestination, indexValue, coordinatesDictionnary, minValue, maxDistance)
# self.flowList(inputTable, originIndex, destinationIndex, valueIndex, coordinates, minValue, maxDistanceKM)
inputLayer = self.parameterAsSource(parameters, self.INPUT, context).materialize(QgsFeatureRequest())
radius = self.parameterAsDouble(parameters, self.DISTANCE , context)
target = self.parameterAsInt( parameters, self.TARGET, context )
if target !=0 :
target = -1
feedback.pushInfo(" • {0} : {1}".format(self.tr('Distance'),radius))
(sink, dest_id) = self.parameterAsSink(parameters, self.OUTPUT_LAYER, context,
inputLayer.fields(), QgsWkbTypes.LineString, inputLayer.crs())
# features = result['OUTPUT'].getFeatures()
stockField = self.parameterAsString(parameters, self.STOCK , context)
for feature in inputLayer.getFeatures():
if stockField != "":
stockFieldIndex = inputLayer.fields().indexOf(stockField)
bufferCenter = QgsGeometry(feature.geometry().get()[target])
bufferPolygon = bufferCenter.buffer(radius*1000, 5)
intersectLine = QgsGeometry.intersection(feature.geometry(), bufferPolygon)
feature.setGeometry(intersectLine)
sink.addFeature(feature, QgsFeatureSink.FastInsert)
return {self.OUTPUT_LAYER: dest_id}
def name(self):
"""
Returns the algorithm name, used for identifying the algorithm. This
string should be fixed for the algorithm, and must not be localised.
The name should be unique within each provider. Names should contain
lowercase alphanumeric characters only and no spaces or other
formatting characters.
"""
return 'shortenlines'
def displayName(self):
"""
Returns the translated algorithm name, which should be used for any
user-visible display of the algorithm name.
"""
return self.tr('Shorten the oursins')
def group(self):
"""
Returns the name of the group this algorithm belongs to. This string
should be localised.
"""
return self.tr('Flows and movements')
def groupId(self):
"""
Returns the unique ID of the group this algorithm belongs to. This
string should be fixed for the algorithm, and must not be localised.
The group id should be unique within each provider. Group id should
contain lowercase alphanumeric characters only and no spaces or other
formatting characters.
"""
return 'flows'
def tr(self, string):
return QCoreApplication.translate('ShortenLinesAlgorithm', string)
def createInstance(self):
return ShortenLinesAlgorithm()
def icon(self):
return QIcon(os.path.dirname(__file__) + '/images/oursins.png')
class CreateArrowsAlgorithm(QgsProcessingAlgorithm):
"""
This is an example algorithm that takes a vector layer and
creates a new identical one.
It is meant to be used as an example of how to create your own
algorithms and explain methods and variables used to do it. An
algorithm like this will be available in all elements, and there
is not need for additional work.
All Processing algorithms should extend the QgsProcessingAlgorithm
class.
"""
# Constants used to refer to parameters and outputs. They will be
# used when calling the algorithm from another algorithm, or when
# calling from the QGIS console.
OUTPUT_LAYER = 'OUTPUT_LAYER'
INPUT = 'INPUT'
ORIGIN = 'ORIGIN'
DESTINATION = 'DESTINATION'
STOCK = 'STOCK'
INPUT2 = 'INPUT2'
MIN_FLOW = 'MIN_FLOW'
MAX_DIST = 'MAX_DIST'
CODGEO = 'CODGEO'
SMART_ARROWS="SMART_ARROWS"
ADD_LEGEND='ADD_LEGEND'
OUTPUT2 = 'OUTPUT2'
def initAlgorithm(self, config):
"""
Here we define the inputs and output of the algorithm, along
with some other properties.
"""
project = QgsProject.instance()
try:
maxValue = QgsExpressionContextUtils.projectScope(project).variable('thematic_arrowsMaxValue')
maxWidth = QgsExpressionContextUtils.projectScope(project).variable('thematic_arrowsMaxWidth')
except:
maxValue = 0
maxWidth = 0
# We add the input vector features source. It can have any kind of
# geometry.
self.addParameter(
QgsProcessingParameterFeatureSource(
self.INPUT,
self.tr('Flow table'),
[QgsProcessing.TypeVector]
)
)
self.addParameter(QgsProcessingParameterField(
self.ORIGIN,
self.tr('Origin'),
None,
self.INPUT,
QgsProcessingParameterField.String,
False
)
)
self.addParameter(QgsProcessingParameterField(
self.DESTINATION,
self.tr('Destination'),
None,
self.INPUT,
QgsProcessingParameterField.String,
False
)
)
self.addParameter(QgsProcessingParameterField(
self.STOCK,
self.tr('Flows variable'),
None,
self.INPUT,
QgsProcessingParameterField.Numeric,
optional=True
)
)
self.addParameter(
QgsProcessingParameterFeatureSource(
self.INPUT2,
self.tr('Localisation layer'),
[QgsProcessing.TypeVectorPolygon,QgsProcessing.TypeVectorPoint],
optional=False
)
)
self.addParameter(QgsProcessingParameterField(
self.CODGEO,
self.tr('Geographical ID'),
None,
self.INPUT2,
QgsProcessingParameterField.String,
False
)
)
# We add a feature sink in which to store our processed features (this
# usually takes the form of a newly created vector layer when the
# algorithm is run in QGIS).
self.addParameter(
QgsProcessingParameterBoolean(self.SMART_ARROWS,
self.tr('Small arrows => needs a polygon localisation layer'),
defaultValue=False))
params = []
params.append(
QgsProcessingParameterNumber(
self.MIN_FLOW,
self.tr('Minimum flow'),
defaultValue=0,
minValue=0,
optional=False
)
)
params.append(
QgsProcessingParameterNumber(
self.MAX_DIST,
self.tr('Maximum distance (in km)'),
defaultValue=0,
minValue=0,
optional=False
)
)
self.addParameter(
QgsProcessingParameterBoolean(self.ADD_LEGEND,
self.tr('Generate a legend'),
defaultValue=True))
for param in params:
param.setFlags(param.flags() | QgsProcessingParameterDefinition.FlagAdvanced)
self.addParameter(param)
self.addParameter(
QgsProcessingParameterFeatureSink(
self.OUTPUT_LAYER,
self.tr('Arrows output layer'),
type=QgsProcessing.TypeVectorPolygon
)
)
self.addParameter(
QgsProcessingParameterFeatureSink(
self.OUTPUT2,
self.tr('Legend output layer'),
type=QgsProcessing.TypeVectorPolygon
)
)
def processAlgorithm(self, parameters, context, feedback):
"""
Here is where the processing itself takes place.
"""
# Retrieve the feature source and sink. The 'dest_id' variable is used
# to uniquely identify the feature sink, and must be included in the
# dictionary returned by the processAlgorithm function.
# INPUT = parameters[self.INPUT]
# print(self.INPUT.extent())
# print(INPUT)
# definition : flowList(self, flowTable, indexOrigin, indexDestination, indexValue, coordinatesDictionnary, minValue, maxDistance)
# self.flowList(inputTable, originIndex, destinationIndex, valueIndex, coordinates, minValue, maxDistanceKM)
inputTable = self.parameterAsSource(parameters, self.INPUT, context).materialize(QgsFeatureRequest())
geographicIdName = self.parameterAsString(parameters, self.CODGEO , context)
geometryLayer = self.parameterAsSource(parameters, self.INPUT2, context).materialize(QgsFeatureRequest())
codgeoIndex = geometryLayer.fields().indexOf(geographicIdName)
layerExtent = geometryLayer.extent()
maximumExtent = max((layerExtent.xMaximum()-layerExtent.xMinimum()),(layerExtent.yMaximum()-layerExtent.yMinimum()))
addLegend = self.parameterAsBool(parameters,self.ADD_LEGEND,context)
originField = self.parameterAsString(parameters, self.ORIGIN , context)
destinationField = self.parameterAsString(parameters, self.DESTINATION , context)
expressionString = '{0} != {1} AND {0} IS NOT NULL AND {1} IS NOT NULL'.format(originField,destinationField)
extractedFeatures = processing.run("native:extractbyexpression",
{'INPUT':inputTable,
'EXPRESSION': expressionString,
'OUTPUT':'memory:'})
crsString = geometryLayer.crs().authid()
if self.parameterAsBool(parameters,self.SMART_ARROWS,context):
buffer = processing.run("native:buffer",
{'INPUT':geometryLayer,
'DISTANCE':QgsProperty.fromExpression(
'-sqrt(area($geometry)/(10*pi()))'),
'SEGMENTS':5,
'END_CAP_STYLE':0,
'JOIN_STYLE':0,
'MITER_LIMIT':2,
'DISSOLVE':False,
'OUTPUT':'memory:'},
feedback = None)
singleParts = processing.run("native:multiparttosingleparts",
{'INPUT':buffer['OUTPUT'],
'OUTPUT':'memory:'},
feedback = feedback)
feedback.pushInfo(" • singleParts['OUTPUT'] : {0}".format(singleParts))
feedback.pushInfo(" • geographicIdName : {0}".format(geographicIdName))
sql = processing.run("qgis:executesql",
{'INPUT_DATASOURCES':singleParts['OUTPUT'],
'INPUT_QUERY':'select *,max(st_area(geometry)) as area from input1 group by {0}'.format(geographicIdName),
'INPUT_UID_FIELD':'',
'INPUT_GEOMETRY_FIELD':'',
'INPUT_GEOMETRY_TYPE':4,
'INPUT_GEOMETRY_CRS':geometryLayer.crs(),
'OUTPUT':'memory:'},
feedback = None)
codgeoIndex = sql['OUTPUT'].fields().indexOf(geographicIdName)
features = sql['OUTPUT'].getFeatures()
else:
features = geometryLayer.getFeatures()
# extract coordinates of the centroid of the geometryLayer as a dictionary
coordinatesDictionnary = {}
for elem in features:
centroid = elem.geometry().centroid().asPoint()
IDvalue = elem.attributes()[codgeoIndex]
coordinatesDictionnary[IDvalue] = centroid
feedback.pushInfo('____________________')
feedback.pushInfo(self.tr('Arrows with automatic scale'))
feedback.pushInfo(' ')
feedback.pushInfo(" {0}".format(self.tr("Values")))
originFieldIndex = extractedFeatures['OUTPUT'].fields().indexOf(originField)
feedback.pushInfo(" • {0} : {1}, [{2}]".format(self.tr("Origin"),
originField,originFieldIndex+1))
destinationFieldIndex = extractedFeatures['OUTPUT'].fields().indexOf(destinationField)
feedback.pushInfo(" • {0} : {1}, [{2}]".format(self.tr("Destination"),
destinationField,destinationFieldIndex+1))
valueField = self.parameterAsString(parameters, self.STOCK , context)
valueFieldIndex = extractedFeatures['OUTPUT'].fields().indexOf(valueField)
feedback.pushInfo(" • {0} : {1}, [{2}]".format(self.tr("Flow"),valueField,valueFieldIndex+1))
feedback.pushInfo(" {0}".format(self.tr("Filter")))
minValue = self.parameterAsDouble(parameters, self.MIN_FLOW , context)
feedback.pushInfo(" • {0} : {1}".format(self.tr('Minimum value'),minValue))
maxDistanceKM = self.parameterAsDouble(parameters, self.MAX_DIST , context)
feedback.pushInfo(" • {0} (0 = {1}) : {2} km".format(self.tr("Maximum distance"),
self.tr("not defined"),
maxDistanceKM))
vl = QgsVectorLayer("LineString?crs="+crsString, "temp", 'memory')
pr = vl.dataProvider()
pr.addAttributes([(QgsField("ORIGINE", QVariant.String)),
(QgsField("DEST", QVariant.String)),
(QgsField("FLUX", QVariant.Double)),
(QgsField("WIDTH", QVariant.Double)),
(QgsField("DIST_KM", QVariant.Double))])
vl.updateFields()
notInLayer = 0
maxValue = max([abs(item.attributes()[valueFieldIndex]) for item in extractedFeatures['OUTPUT'].getFeatures()])
self.maxValue = maxValue
self.maxWidth = (maximumExtent)/30
project = QgsProject.instance()
QgsExpressionContextUtils.setProjectVariable(project,'thematic_arrowsMaxValue',self.maxValue)
QgsExpressionContextUtils.setProjectVariable(project,'thematic_arrowsMaxWidth',self.maxWidth)
feedback.pushInfo(" {0} :".format(self.tr('Scale')))
# feedback.pushInfo(" • {0} : {1}".format(self.tr('Maximum value')),self.maxValue)
# feedback.pushInfo(" • {0} : {1} m".format(self.tr('Maximum width')),self.maxWidth)
for elem in extractedFeatures['OUTPUT'].getFeatures():
value = float(elem.attributes()[valueFieldIndex])
try:
pointA = coordinatesDictionnary[elem.attributes()[originFieldIndex]]
pointB = coordinatesDictionnary[elem.attributes()[destinationFieldIndex]]
if pointA != pointB and (value >= minValue or minValue ==0):
line = (pointA,pointB)
d = QgsDistanceArea()
distance = d.measureLine(pointA,pointB)/1000
if (maxDistanceKM == 0 or distance <= maxDistanceKM):
f = QgsFeature()
f.setGeometry(QgsGeometry.fromPolylineXY(line))
f.setAttributes([elem.attributes()[originFieldIndex],
elem.attributes()[destinationFieldIndex],
value,
abs(value)*self.maxWidth/self.maxValue,
distance])
pr.addFeature(f)
except:
# commune non présente dans le fond de carte
pass
# 'coalesce(scale_linear(abs( "FLUX" ), 0, {0}, 0,{1}), 0)'.format(self.maxValue, self.maxWidth)
vl.updateExtents()
vl.renderer().symbol().setWidth(3)
# Add features to the sink
# (sink, dest_id) = self.parameterAsSink(parameters, self.OUTPUT_LAYER, context,
# vl.fields(), QgsWkbTypes.LineString, vl.crs())
if self.parameterAsBool(parameters,self.SMART_ARROWS,context):
lineOrigin = processing.run("qgis:executesql",
{'INPUT_DATASOURCES':[vl,sql['OUTPUT']],
'INPUT_QUERY':'select a.ORIGINE, a.DEST, a.FLUX, a.WIDTH, a.DIST_KM , st_difference(a.geometry, b.geometry) as geometry from input1 as a left join input2 as b on a.origine = b.{0}'.format(geographicIdName),
'INPUT_UID_FIELD':'',
'INPUT_GEOMETRY_FIELD':'',
'INPUT_GEOMETRY_TYPE':4,
'INPUT_GEOMETRY_CRS':geometryLayer.crs(),
'OUTPUT':'memory:'},
feedback = None)
lineDestination = processing.run("qgis:executesql",
{'INPUT_DATASOURCES':[lineOrigin['OUTPUT'],sql['OUTPUT']],
'INPUT_QUERY':'select a.ORIGINE, a.DEST, a.FLUX, a.WIDTH, a.DIST_KM , st_difference(a.geometry, b.geometry) as geometry from input1 as a left join input2 as b on a.dest = b.{0}'.format(geographicIdName),
'INPUT_UID_FIELD':'',
'INPUT_GEOMETRY_FIELD':'',
'INPUT_GEOMETRY_TYPE':4,
'INPUT_GEOMETRY_CRS':geometryLayer.crs(),
'OUTPUT':'memory:'},
feedback = None)
singleParts = processing.run("native:multiparttosingleparts",
{'INPUT':lineDestination['OUTPUT'],
'OUTPUT':'memory:'})
arrow = processing.run("qgis:executesql",
{'INPUT_DATASOURCES':[geometryLayer,singleParts['OUTPUT']],
'INPUT_QUERY':'select input2.* from input2 where st_intersects(input2.geometry,(select input1.geometry from input1 where input2.origine = input1.{0})) and st_intersects(input2.geometry,(select input1.geometry from input1 where input2.dest = input1.{0}))'.format(geographicIdName),
'INPUT_UID_FIELD':'',
'INPUT_GEOMETRY_FIELD':'geometry',
'INPUT_GEOMETRY_TYPE':0,
'INPUT_GEOMETRY_CRS':None,
'OUTPUT':'memory:'},
feedback = None)
(sink, dest_id) = self.parameterAsSink(parameters, self.OUTPUT_LAYER, context,
arrow['OUTPUT'].fields(), QgsWkbTypes.LineString, arrow['OUTPUT'].crs())
features = arrow['OUTPUT'].getFeatures()
else:
(sink, dest_id) = self.parameterAsSink(parameters, self.OUTPUT_LAYER, context,
vl.fields(), QgsWkbTypes.LineString, vl.crs())
features = vl.getFeatures()
for feature in features:
sink.addFeature(feature, QgsFeatureSink.FastInsert)
self.dest_id = dest_id
if addLegend:
xLegend = vl.sourceExtent().xMaximum()
yLegend = (vl.sourceExtent().yMinimum()+vl.sourceExtent().yMaximum())/2
legendCoords = str(xLegend)+','+str(yLegend)
result2 = processing.run("thematic:arrowslegend",
{'MAX_VALUE':maxValue,
'MAX_WIDTH':self.maxWidth,
'VALUES_LIST':'',
'XY_LEGEND':legendCoords,
'OUTPUT':'memory:'},
feedback = None)
# processing.run("thematic:arrowslegend", {'MAX_VALUE':8800,'MAX_WIDTH':45288,'VALUES_LIST':'','OUTPUT':'memory:'})
feedback.pushInfo(" {0} :".format(self.tr('Values in the legend')))
feedback.pushInfo(" • {0} : {1}".format(self.tr("Value 1"),maxValue))
feedback.pushInfo(" • {0} : {1}".format(self.tr("Value 2"),maxValue/2))
feedback.pushInfo(' {0}'.format(self.tr("Legend coordinates :")))
feedback.pushInfo(" • {0} : {1}".format(self.tr("X"),xLegend))
feedback.pushInfo(" • {0} : {1}".format(self.tr("Y"),yLegend))
feedback.pushInfo('____________________')
feedback.pushInfo('')
(sink2, dest_id2) = self.parameterAsSink(parameters, self.OUTPUT2, context,
result2['OUTPUT'].fields(), QgsWkbTypes.LineString, result2['OUTPUT'].crs())
features = result2['OUTPUT'].getFeatures()
for feature in features:
sink2.addFeature(feature, QgsFeatureSink.FastInsert)
# to get hold of the layer in post processing for styling the legend
self.dest_id2=dest_id2
return {self.OUTPUT_LAYER: 'dest_id', self.OUTPUT2: 'dest_id2'}
# Return the results of the algorithm. In this case our only result is
# the feature sink which contains the processed features, but some
# algorithms may return multiple feature sinks, calculated numeric
# statistics, etc. These should all be included in the returned
# dictionary, with keys matching the feature corresponding parameter
# or output names.
else:
feedback.pushInfo(" {0}".format(self.tr('No legend requested')))
feedback.pushInfo('____________________')
feedback.pushInfo('')
self.dest_id2 = None
return {self.OUTPUT_LAYER: dest_id}
def postProcessAlgorithm(self, context, feedback):
# Styling the arrows
output = QgsProcessingUtils.mapLayerFromString(self.dest_id, context)
path = os.path.dirname(__file__) + '/styles/simple_arrows.qml'
output.loadNamedStyle(path)
layerProperties = output.renderer().symbol().symbolLayers()[0].dataDefinedProperties()
expressionString = '"WIDTH"'
# expressionString = 'coalesce(scale_linear(abs( "FLUX" ), 0, {0}, 0,{1}), 0)'.format(self.maxValue, self.maxWidth)
# PropertyArrowWidth -> 44
layerProperties.property(44).setExpressionString(expressionString)
# PropertyArrowStartWidth -> 45
layerProperties.property(45).setExpressionString(expressionString)
# expressionString = '"WIDTH"*0.8'.format(self.maxValue, self.maxWidth)
# expressionString = 'coalesce(scale_linear(abs( "FLUX" ), 0, {0}, 0,{1}), 0)*0.8'.format(self.maxValue, self.maxWidth)
# PropertyArrowHeadLength -> 46
layerProperties.property(46).setExpressionString(expressionString)
# layerProperties.property(46).setExpressionString('if($length/2 < maximum("WIDTH"), $length/2, maximum("WIDTH"))')
# PropertyArrowHeadThickness -> 47
layerProperties.property(47).setExpressionString('0.5*"WIDTH"+.1*maximum("WIDTH")')
expressionString = '"WIDTH"'.format(self.maxValue, self.maxWidth)
# PropertyOffset -> 7
layerProperties.property(7).setExpressionString('0.5*"WIDTH"+.1*maximum("WIDTH")')
output.triggerRepaint()
if self.dest_id2 is not None:
# Styling the legend
output = QgsProcessingUtils.mapLayerFromString(self.dest_id2, context)
path = os.path.dirname(__file__) + '/styles/arrows_legend.qml'
output.loadNamedStyle(path)
output.triggerRepaint()
return {self.OUTPUT_LAYER: self.dest_id, self.OUTPUT2: self.dest_id2}
else :
return {self.OUTPUT_LAYER: self.dest_id}
def name(self):
"""
Returns the algorithm name, used for identifying the algorithm. This
string should be fixed for the algorithm, and must not be localised.
The name should be unique within each provider. Names should contain