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fix analysisCRS to use network layer, fix OD matrix unique ID data types, and update language to match other QGIS functions #33

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fix analysisCRS to use network layer, fix OD matrix unique ID data types, and update language to match other QGIS functions #33

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38d3348
Use network.sourceCrs() for analysis rather than context.project().cr…
kufreu Jun 30, 2020
f94e5be
Allowing the unique point identifier fields in OD Matrix to use the o…
kufreu Jun 30, 2020
dc51e6a
Making origin and destination field names consistent with QGIS Distan…
kufreu Jul 1, 2020
1efb830
Remove start and end ID from shortest path output
kufreu Jul 1, 2020
9c8a2f4
Update language in Iso-Area algorithms for consistency with core QGIS…
Jul 1, 2020
dbfe669
Clarify contour interval units
Jul 1, 2020
db7f78a
Increase default value of topology tolerance to 0.00001
kufreu Jul 6, 2020
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59 changes: 29 additions & 30 deletions algs/IsoAreaAsContoursFromLayer.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -3,10 +3,10 @@
***************************************************************************
IsoAreaAsContourFromLayer.py
---------------------
Partially based on QGIS3 network analysis algorithms.
Copyright 2016 Alexander Bruy

Partially based on QGIS3 network analysis algorithms.
Copyright 2016 Alexander Bruy

Date : February 2018
Copyright : (C) 2018 by Clemens Raffler
Email : clemens dot raffler at gmail dot com
Expand Down Expand Up @@ -88,27 +88,27 @@ def group(self):

def groupId(self):
return 'isoareas'

def name(self):
return 'isoareaascontoursfromlayer'

def displayName(self):
return self.tr('Iso-Area as Contours (from Layer)')

def shortHelpString(self):
return "<b>General:</b><br>"\
"This algorithm implements iso-area contours to return the <b>isochrone areas for a maximum cost level and interval levels </b> on a given <b>network dataset for a layer of points</b>.<br>"\
"It accounts for <b>points outside of the network</b> (eg. <i>non-network-elements</i>) and increments the iso-areas cost regarding to distance/default speed value. Distances are measured accounting for <b>ellipsoids</b>.<br>Please, <b>only use a projected coordinate system (eg. no WGS84)</b> for this kind of analysis.<br><br>"\
"<b>Parameters (required):</b><br>"\
"Following Parameters must be set to run the algorithm:"\
"<ul><li>Network Layer</li><li>Startpoint Layer</li><li>Unique Point ID Field (numerical)</li><li>Maximum cost level for Iso-Area</li><li>Cost Intervals for Iso-Area Bands</li><li>Cellsize in Meters (increase default when analyzing larger networks)</li><li>Cost Strategy</li></ul><br>"\
"<ul><li>Network Layer</li><li>Startpoint Layer</li><li>Unique Point ID Field (numerical)</li><li>Maximum cost level of Iso-Area in distance (meters) or time (seconds)</li><li>Contour Intervals in distance (meters) or time (seconds)</li><li>Cellsize in Meters (increase default when analyzing larger networks)</li><li>Path type to calculate</li></ul><br>"\
"<b>Parameters (optional):</b><br>"\
"There are also a number of <i>optional parameters</i> to implement <b>direction dependent</b> shortest paths and provide information on <b>speeds</b> on the networks edges."\
"<ul><li>Direction Field</li><li>Value for forward direction</li><li>Value for backward direction</li><li>Value for both directions</li><li>Default direction</li><li>Speed Field</li><li>Default Speed (affects entry/exit costs)</li><li>Topology tolerance</li></ul><br>"\
"<b>Output:</b><br>"\
"The output of the algorithm are two layers:"\
"<ul><li>TIN-Interpolation Distance Raster</li><li>Iso-Area Contours with cost levels as attributes</li></ul>"

def msg(self, var):
return "Type:"+str(type(var))+" repr: "+var.__str__()

Expand All @@ -121,12 +121,12 @@ def initAlgorithm(self, config=None):
(self.tr('Backward direction'), QgsVectorLayerDirector.DirectionBackward),
(self.tr('Both directions'), QgsVectorLayerDirector.DirectionBoth)])

self.STRATEGIES = [self.tr('Shortest Path (distance optimization)'),
self.tr('Fastest Path (time optimization)')
self.STRATEGIES = [self.tr('Shortest distance'),
self.tr('Fastest time')
]

self.ENTRY_COST_CALCULATION_METHODS = [self.tr('Planar (only use with projected CRS)')]


self.addParameter(QgsProcessingParameterFeatureSource(self.INPUT,
self.tr('Network Layer'),
Expand All @@ -140,7 +140,7 @@ def initAlgorithm(self, config=None):
self.START_POINTS,
optional=False))
self.addParameter(QgsProcessingParameterNumber(self.MAX_DIST,
self.tr('Size of Iso-Area (distance or time value)'),
self.tr('Maximum cost level of Iso-Area'),
QgsProcessingParameterNumber.Double,
2500.0, False, 0, 99999999.99))
self.addParameter(QgsProcessingParameterNumber(self.INTERVAL,
Expand All @@ -152,7 +152,7 @@ def initAlgorithm(self, config=None):
QgsProcessingParameterNumber.Integer,
10, False, 1, 99999999))
self.addParameter(QgsProcessingParameterEnum(self.STRATEGY,
self.tr('Optimization Criterion'),
self.tr('Path type to calculate'),
self.STRATEGIES,
defaultValue=0))

Expand Down Expand Up @@ -191,15 +191,15 @@ def initAlgorithm(self, config=None):
params.append(QgsProcessingParameterNumber(self.TOLERANCE,
self.tr('Topology tolerance'),
QgsProcessingParameterNumber.Double,
0.0, False, 0, 99999999.99))
0.00001, False, 0, 99999999.99))

for p in params:
p.setFlags(p.flags() | QgsProcessingParameterDefinition.FlagAdvanced)
self.addParameter(p)

self.addParameter(QgsProcessingParameterRasterDestination(self.OUTPUT_INTERPOLATION, self.tr('Output Interpolation')))
self.addParameter(QgsProcessingParameterFeatureSink(self.OUTPUT_CONTOURS, self.tr('Output Contours'), QgsProcessing.TypeVectorLine))

def processAlgorithm(self, parameters, context, feedback):
feedback.pushInfo(self.tr("[QNEAT3Algorithm] This is a QNEAT3 Algorithm: '{}'".format(self.displayName())))
network = self.parameterAsSource(parameters, self.INPUT, context) #QgsProcessingFeatureSource
Expand All @@ -221,47 +221,46 @@ def processAlgorithm(self, parameters, context, feedback):
tolerance = self.parameterAsDouble(parameters, self.TOLERANCE, context) #float
output_path = self.parameterAsOutputLayer(parameters, self.OUTPUT_INTERPOLATION, context) #string

analysisCrs = context.project().crs()
input_coordinates = getListOfPoints(startPoints)
analysisCrs = network.sourceCrs()
input_coordinates = getListOfPoints(startPoints)

feedback.pushInfo("[QNEAT3Algorithm] Building Graph...")
feedback.setProgress(10)
net = Qneat3Network(network, input_coordinates, strategy, directionFieldName, forwardValue, backwardValue, bothValue, defaultDirection, analysisCrs, speedFieldName, defaultSpeed, tolerance, feedback)
feedback.setProgress(40)

list_apoints = [Qneat3AnalysisPoint("from", feature, id_field, net, net.list_tiedPoints[i], entry_cost_calc_method, feedback) for i, feature in enumerate(getFeaturesFromQgsIterable(startPoints))]

feedback.pushInfo("[QNEAT3Algorithm] Calculating Iso-Pointcloud...")
iso_pointcloud = net.calcIsoPoints(list_apoints, max_dist+(max_dist*0.1))
feedback.setProgress(50)

uri = "Point?crs={}&field=vertex_id:int(254)&field=cost:double(254,7)&field=origin_point_id:string(254)&index=yes".format(analysisCrs.authid())

iso_pointcloud_layer = QgsVectorLayer(uri, "iso_pointcloud_layer", "memory")
iso_pointcloud_provider = iso_pointcloud_layer.dataProvider()
iso_pointcloud_provider.addFeatures(iso_pointcloud, QgsFeatureSink.FastInsert)

feedback.pushInfo("[QNEAT3Algorithm] Calculating Iso-Interpolation-Raster using QGIS TIN-Interpolator...")
net.calcIsoTinInterpolation(iso_pointcloud_layer, cell_size, output_path)
feedback.setProgress(70)

fields = QgsFields()
fields.append(QgsField('id', QVariant.Int, '', 254, 0))
fields.append(QgsField('cost_level', QVariant.Double, '', 20, 7))

(sink, dest_id) = self.parameterAsSink(parameters, self.OUTPUT_CONTOURS, context, fields, QgsWkbTypes.LineString, network.sourceCrs())

feedback.pushInfo("[QNEAT3Algorithm] Calculating Iso-Contours using numpy and matplotlib...")
contour_featurelist = net.calcIsoContours(max_dist, interval, output_path)
feedback.setProgress(90)

sink.addFeatures(contour_featurelist, QgsFeatureSink.FastInsert)

feedback.pushInfo("[QNEAT3Algorithm] Ending Algorithm")
feedback.setProgress(100)

results = {}
results[self.OUTPUT_INTERPOLATION] = output_path
results[self.OUTPUT_CONTOURS] = dest_id
return results

55 changes: 27 additions & 28 deletions algs/IsoAreaAsContoursFromPoint.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -3,10 +3,10 @@
***************************************************************************
IsoAreaAsContourFromPoint.py
---------------------
Partially based on QGIS3 network analysis algorithms.
Copyright 2016 Alexander Bruy

Partially based on QGIS3 network analysis algorithms.
Copyright 2016 Alexander Bruy

Date : February 2018
Copyright : (C) 2018 by Clemens Raffler
Email : clemens dot raffler at gmail dot com
Expand Down Expand Up @@ -88,7 +88,7 @@ def group(self):

def groupId(self):
return 'isoareas'

def name(self):
return 'isoareaascontoursfrompoint'

Expand All @@ -101,15 +101,15 @@ def shortHelpString(self):
"It accounts for <b>points outside of the network</b> (eg. <i>non-network-elements</i>) and increments the isochrone areas cost regarding to distance/default speed value. Distances are measured accounting for <b>ellipsoids</b>.<br>Please, <b>only use a projected coordinate system (eg. no WGS84)</b> for this kind of analysis.<br><br>"\
"<b>Parameters (required):</b><br>"\
"Following Parameters must be set to run the algorithm:"\
"<ul><li>Network Layer</li><li>Startpoint</li><li>Maximum cost level for Iso-Area</li><li>Cost Intervals for Iso-Area Bands</li><li>Cellsize in Meters (increase default when analyzing larger networks)</li><li>Cost Strategy</li></ul><br>"\
"<ul><li>Network Layer</li><li>Startpoint</li><li>Maximum cost level of Iso-Area in distance (meters) or time (seconds)</li><li>Contour Intervals in distance (meters) or time (seconds)</li><li>Cellsize in Meters (increase default when analyzing larger networks)</li><li>Path type to calculate</li></ul><br>"\
"<b>Parameters (optional):</b><br>"\
"There are also a number of <i>optional parameters</i> to implement <b>direction dependent</b> shortest paths and provide information on <b>speeds</b> on the networks edges."\
"<ul><li>Direction Field</li><li>Value for forward direction</li><li>Value for backward direction</li><li>Value for both directions</li><li>Default direction</li><li>Speed Field</li><li>Default Speed (affects entry/exit costs)</li><li>Topology tolerance</li></ul><br>"\
"<b>Output:</b><br>"\
"The output of the algorithm are two layers:"\
"<ul><li>TIN-Interpolation Distance Raster</li><li>Iso-Area Contours with cost levels as attributes</li></ul>"


def msg(self, var):
return "Type:"+str(type(var))+" repr: "+var.__str__()

Expand All @@ -122,20 +122,20 @@ def initAlgorithm(self, config=None):
(self.tr('Backward direction'), QgsVectorLayerDirector.DirectionBackward),
(self.tr('Both directions'), QgsVectorLayerDirector.DirectionBoth)])

self.STRATEGIES = [self.tr('Shortest Path (distance optimization)'),
self.tr('Fastest Path (time optimization)')
self.STRATEGIES = [self.tr('Shortest distance'),
self.tr('Fastest time')
]

self.ENTRY_COST_CALCULATION_METHODS = [self.tr('Planar (only use with projected CRS)')]


self.addParameter(QgsProcessingParameterFeatureSource(self.INPUT,
self.tr('Network Layer'),
[QgsProcessing.TypeVectorLine]))
self.addParameter(QgsProcessingParameterPoint(self.START_POINT,
self.tr('Start point')))
self.addParameter(QgsProcessingParameterNumber(self.MAX_DIST,
self.tr('Size of Iso-Area (distance or time value)'),
self.tr('Maximum cost level of Iso-Area'),
QgsProcessingParameterNumber.Double,
2500.0, False, 0, 99999999.99))
self.addParameter(QgsProcessingParameterNumber(self.INTERVAL,
Expand All @@ -147,7 +147,7 @@ def initAlgorithm(self, config=None):
QgsProcessingParameterNumber.Integer,
10, False, 1, 99999999))
self.addParameter(QgsProcessingParameterEnum(self.STRATEGY,
self.tr('Optimization Criterion'),
self.tr('Path type to calculate'),
self.STRATEGIES,
defaultValue=0))

Expand Down Expand Up @@ -186,15 +186,15 @@ def initAlgorithm(self, config=None):
params.append(QgsProcessingParameterNumber(self.TOLERANCE,
self.tr('Topology tolerance'),
QgsProcessingParameterNumber.Double,
0.0, False, 0, 99999999.99))
0.00001, False, 0, 99999999.99))

for p in params:
p.setFlags(p.flags() | QgsProcessingParameterDefinition.FlagAdvanced)
self.addParameter(p)

self.addParameter(QgsProcessingParameterRasterDestination(self.OUTPUT_INTERPOLATION, self.tr('Output Interpolation')))
self.addParameter(QgsProcessingParameterFeatureSink(self.OUTPUT_CONTOURS, self.tr('Output Contours'), QgsProcessing.TypeVectorLine))

def processAlgorithm(self, parameters, context, feedback):
feedback.pushInfo(self.tr("[QNEAT3Algorithm] This is a QNEAT3 Algorithm: '{}'".format(self.displayName())))
network = self.parameterAsSource(parameters, self.INPUT, context) #QgsProcessingFeatureSource
Expand All @@ -218,44 +218,43 @@ def processAlgorithm(self, parameters, context, feedback):
analysisCrs = network.sourceCrs()
input_coordinates = [startPoint]
input_point = getFeatureFromPointParameter(startPoint)

feedback.pushInfo("[QNEAT3Algorithm] Building Graph...")
feedback.setProgress(10)
feedback.setProgress(10)
net = Qneat3Network(network, input_coordinates, strategy, directionFieldName, forwardValue, backwardValue, bothValue, defaultDirection, analysisCrs, speedFieldName, defaultSpeed, tolerance, feedback)
feedback.setProgress(40)

analysis_point = Qneat3AnalysisPoint("point", input_point, "point_id", net, net.list_tiedPoints[0], entry_cost_calc_method, feedback)

feedback.pushInfo("[QNEAT3Algorithm] Calculating Iso-Pointcloud...")
iso_pointcloud = net.calcIsoPoints([analysis_point], (max_dist+(max_dist*0.1)))
feedback.setProgress(50)

uri = "Point?crs={}&field=vertex_id:int(254)&field=cost:double(254,7)&field=origin_point_id:string(254)&index=yes".format(analysisCrs.authid())

iso_pointcloud_layer = QgsVectorLayer(uri, "iso_pointcloud_layer", "memory")
iso_pointcloud_provider = iso_pointcloud_layer.dataProvider()
iso_pointcloud_provider.addFeatures(iso_pointcloud, QgsFeatureSink.FastInsert)

feedback.pushInfo("[QNEAT3Algorithm] Calculating Iso-Interpolation-Raster using QGIS TIN-Interpolator...")
net.calcIsoTinInterpolation(iso_pointcloud_layer, cell_size, output_path)
feedback.setProgress(70)

fields = QgsFields()
fields.append(QgsField('id', QVariant.Int, '', 254, 0))
fields.append(QgsField('cost_level', QVariant.Double, '', 20, 7))

(sink, dest_id) = self.parameterAsSink(parameters, self.OUTPUT_CONTOURS, context, fields, QgsWkbTypes.LineString, network.sourceCrs())

feedback.pushInfo("[QNEAT3Algorithm] Calculating Iso-Contours using numpy and matplotlib...")
contour_featurelist = net.calcIsoContours(max_dist, interval, output_path)
feedback.setProgress(90)

sink.addFeatures(contour_featurelist, QgsFeatureSink.FastInsert)
feedback.pushInfo("[QNEAT3Algorithm] Ending Algorithm")
feedback.setProgress(100)

results = {}
results[self.OUTPUT_INTERPOLATION] = output_path
results[self.OUTPUT_CONTOURS] = dest_id
return results

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