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28.1.19. Vector analysis

28.1.19.1. Basic statistics for fields

Generates basic statistics for a field of the attribute table of a vector layer.

Numeric, date, time and string fields are supported.

The statistics returned will depend on the field type.

Statistics are generated as an HTML file and are available in the Processing ► Results viewer.

Default menu: Vector ► Analysis Tools

Parâmetros

Label	Nome	Type	Descrição
Input vector	INPUT_LAYER	[vector: any]	Vector layer to calculate the statistics on
Field to calculate statistics on	FIELD_NAME	[tablefield: any]	Any supported table field to calculate the statistics
Statistics Opcional	OUTPUT_HTML_FILE	[html] Default: [Save to temporary file]	Specification of the file for the calculated statistics. One of: Skip Output Save to a Temporary File Save to File…

Resultados

Label	Nome	Type	Descrição
Statistics	OUTPUT_HTML_FILE	[html]	HTML file with the calculated statistics
Count	COUNT	[number]
Number of unique values	UNIQUE	[number]
Number of empty (null) values	EMPTY	[number]
Number of non-empty values	FILLED	[number]
Minimum value	MIN	[same as input]
Maximum value	MAX	[same as input]
Minimum length	MIN_LENGTH	[number]
Maximum length	MAX_LENGTH	[number]
Mean length	MEAN_LENGTH	[number]
Coefficient of Variation	CV	[number]
Sum	SUM	[number]
Mean value	MEAN	[number]
Standard deviation	STD_DEV	[number]
Range	RANGE	[number]
Median	MEDIAN	[number]
Minority (rarest occurring value)	MINORITY	[same as input]
Majority (most frequently occurring value)	MAJORITY	[same as input]
First quartile	FIRSTQUARTILE	[number]
Third quartile	THIRDQUARTILE	[number]
Interquartile Range (IQR)	IQR	[number]

Python code

Algorithm ID: qgis:basicstatisticsforfields

import processing
processing.run("algorithm_id", {parameter_dictionary})

The algorithm id is displayed when you hover over the algorithm in the Processing Toolbox. The parameter dictionary provides the parameter NAMEs and values. See Usando os algoritmos do processamento a partir da consola for details on how to run processing algorithms from the Python console.

28.1.19.2. Climb along line

Calculates the total climb and descent along line geometries. The input layer must have Z values present. If Z values are not available, the Drape (set Z value from raster) algorithm may be used to add Z values from a DEM layer.

The output layer is a copy of the input layer with additional fields that contain the total climb (climb), total descent (descent), the minimum elevation (minelev) and the maximum elevation (maxelev) for each line geometry. If the input layer contains fields with the same names as these added fields, they will be renamed (field names will be altered to «name_2», «name_3», etc, finding the first non-duplicate name).

Parâmetros

Label	Nome	Type	Descrição
Line layer	INPUT	[vector: line]	Line layer to calculate the climb for. Must have Z values
Climb layer	OUTPUT	[vector: line] Default: [Create temporary layer]	Specification of the output (line) layer. One of: Create Temporary Layer (TEMPORARY_OUTPUT) Save to File… Save to Geopackage… Save to Database Table… The file encoding can also be changed here.

Resultados

Label	Nome	Type	Descrição
Climb layer	OUTPUT	[vector: line]	Line layer containing new attributes with the results from climb calculations.
Total climb	TOTALCLIMB	[number]	The sum of the climb for all the line geometries in the input layer
Total descent	TOTALDESCENT	[number]	The sum of the descent for all the line geometries in the input layer
Minimum elevation	MINELEVATION	[number]	The minimum elevation for the geometries in the layer
Maximum elevation	MAXELEVATION	[number]	The maximum elevation for the geometries in the layer

Python code

Algorithm ID: qgis:climbalongline

import processing
processing.run("algorithm_id", {parameter_dictionary})

The algorithm id is displayed when you hover over the algorithm in the Processing Toolbox. The parameter dictionary provides the parameter NAMEs and values. See Usando os algoritmos do processamento a partir da consola for details on how to run processing algorithms from the Python console.

28.1.19.3. Count points in polygon

Takes a point and a polygon layer and counts the number of points from the point layer in each of the polygons of the polygon layer.

A new polygon layer is generated, with the exact same content as the input polygon layer, but containing an additional field with the points count corresponding to each polygon.

Fig. 28.40 The labels in the polygons show the point count

An optional weight field can be used to assign weights to each point. Alternatively, a unique class field can be specified. If both options are used, the weight field will take precedence and the unique class field will be ignored.

Allows features in-place modification of polygon features

Default menu: Vector ► Analysis Tools

Parâmetros

Label	Nome	Type	Descrição
Polygons	POLYGONS	[vector: polygon]	Polygon layer whose features are associated with the count of points they contain
Points	POINTS	[vector: point]	Point layer with features to count
Weight field Opcional	WEIGHT	[tablefield: any]	A field from the point layer. The count generated will be the sum of the weight field of the points contained by the polygon. If the weight field is not numeric, the count will be 0.
Class field Opcional	CLASSFIELD	[tablefield: any]	Points are classified based on the selected attribute and if several points with the same attribute value are within the polygon, only one of them is counted. The final count of the points in a polygon is, therefore, the count of different classes that are found in it.
Count field name	FIELD	[string] Default: “NUMPOINTS”	The name of the field to store the count of points
Count	OUTPUT	[vector: polygon] Default: [Create temporary layer]	Specification of the output layer. One of: Create Temporary Layer (TEMPORARY_OUTPUT) Save to File… Save to Geopackage… Save to Database Table… Append to Layer… The file encoding can also be changed here.

Resultados

Label	Nome	Type	Descrição
Count	OUTPUT	[vector: polygon]	Resulting layer with the attribute table containing the new column with the points count

Python code

Algorithm ID: native:countpointsinpolygon

import processing
processing.run("algorithm_id", {parameter_dictionary})

The algorithm id is displayed when you hover over the algorithm in the Processing Toolbox. The parameter dictionary provides the parameter NAMEs and values. See Usando os algoritmos do processamento a partir da consola for details on how to run processing algorithms from the Python console.

28.1.19.4. DBSCAN clustering

Clusters point features based on a 2D implementation of Density-based spatial clustering of applications with noise (DBSCAN) algorithm.

The algorithm requires two parameters, a minimum cluster size, and the maximum distance allowed between clustered points.

Veja também

ST-DBSCAN clustering, K-means clustering

Parâmetros

Basic parameters

Label	Nome	Type	Descrição
Input layer	INPUT	[vector: point]	Layer to analyze
Minimum cluster size	MIN_SIZE	[number] Default: 5	Minimum number of features to generate a cluster
Maximum distance between clustered points	EPS	[number] Default: 1.0	Distance beyond which two features can not belong to the same cluster (eps)
Clusters	OUTPUT	[vector: point] Default: [Create temporary layer]	Specify the vector layer for the result of the clustering. One of: Create Temporary Layer (TEMPORARY_OUTPUT) Save to File… Save to Geopackage… Save to Database Table… The file encoding can also be changed here.

Advanced parameters

Label	Nome	Type	Descrição
Treat border points as noise (DBSCAN*) Opcional	DBSCAN*	[boolean] Default: False	If checked, points on the border of a cluster are themselves treated as unclustered points, and only points in the interior of a cluster are tagged as clustered.
Cluster field name	FIELD_NAME	[string] Default: “CLUSTER_ID”	Name of the field where the associated cluster number shall be stored
Cluster size field name	SIZE_FIELD_NAME	[string] Default: “CLUSTER_SIZE”	Name of the field with the count of features in the same cluster

Resultados

Label	Nome	Type	Descrição
Clusters	OUTPUT	[vector: point]	Vector layer containing the original features with a field setting the cluster they belong to
Number of clusters	NUM_CLUSTERS	[number]	The number of clusters discovered

Python code

Algorithm ID: native:dbscanclustering

import processing
processing.run("algorithm_id", {parameter_dictionary})

The algorithm id is displayed when you hover over the algorithm in the Processing Toolbox. The parameter dictionary provides the parameter NAMEs and values. See Usando os algoritmos do processamento a partir da consola for details on how to run processing algorithms from the Python console.

28.1.19.5. Distance matrix

Calculates for point features distances to their nearest features in the same layer or in another layer.

Default menu: Vector ► Analysis Tools

Veja também

Join attributes by nearest

Parâmetros

Label	Nome	Type	Descrição
Input point layer	INPUT	[vector: point]	Point layer for which the distance matrix is calculated (from points)
Input unique ID field	INPUT_FIELD	[tablefield: any]	Field to use to uniquely identify features of the input layer. Used in the output attribute table.
Target point layer	TARGET	[vector: point]	Point layer containing the nearest point(s) to search (to points)
Target unique ID field	TARGET_FIELD	[tablefield: any]	Field to use to uniquely identify features of the target layer. Used in the output attribute table.
Output matrix type	MATRIX_TYPE	[enumeration] Default: 0	Different types of calculation are available: 0 — Linear (N * k x 3) distance matrix: for each input point, reports the distance to each of the k nearest target points. The output matrix consists of up to k rows per input point, and each row has three columns: InputID, TargetID and Distance. 1 — Standard (N x T) distance matrix 2 — Summary distance matrix (mean, std. dev., min, max): for each input point, reports statistics on the distances to its target points.
Use only the nearest (k) target points	NEAREST_POINTS	[number] Default: 0	You can choose to calculate the distance to all the points in the target layer (0) or limit to a number (k) of closest features.
Distance matrix	OUTPUT	[vector: point] Default: [Create temporary layer]	Specification of the output vector layer. One of: Create Temporary Layer (TEMPORARY_OUTPUT) Save to File… Save to Geopackage… Save to Database Table… The file encoding can also be changed here.

Resultados

Label	Nome	Type	Descrição
Distance matrix	OUTPUT	[vector: point]	Point (or MultiPoint for the «Linear (N * k x 3)» case) vector layer containing the distance calculation for each input feature. Its features and attribute table depend on the selected output matrix type.

Python code

Algorithm ID: qgis:distancematrix

import processing
processing.run("algorithm_id", {parameter_dictionary})

The algorithm id is displayed when you hover over the algorithm in the Processing Toolbox. The parameter dictionary provides the parameter NAMEs and values. See Usando os algoritmos do processamento a partir da consola for details on how to run processing algorithms from the Python console.

28.1.19.6. Distance to nearest hub (line to hub)

Creates lines that join each feature of an input vector to the nearest feature in a destination layer. Distances are calculated based on the center of each feature.

Fig. 28.41 Display the nearest hub for the red input features

Veja também

Distance to nearest hub (points), Join attributes by nearest

Parâmetros

Label	Nome	Type	Descrição
Source points layer	INPUT	[vector: any]	Vector layer for which the nearest feature is searched
Destination hubs layer	HUBS	[vector: any]	Vector layer containing the features to search for
Hub layer name attribute	FIELD	[tablefield: any]	Field to use to uniquely identify features of the destination layer. Used in the output attribute table
Measurement unit	UNIT	[enumeration] Default: 0	Units in which to report the distance to the closest feature: 0 — Meters 1 — Feet 2 — Miles 3 — Kilometers 4 — Layer units
Hub distance	OUTPUT	[vector: line] Default: [Create temporary layer]	Specify the output line vector layer connecting the matching points. One of: Create Temporary Layer (TEMPORARY_OUTPUT) Save to File… Save to Geopackage… Save to Database Table… The file encoding can also be changed here.

Resultados

Label	Nome	Type	Descrição
Hub distance	OUTPUT	[vector: line]	Line vector layer with the attributes of the input features, the identifier of their closest feature and the calculated distance.

Python code

Algorithm ID: qgis:distancetonearesthublinetohub

import processing
processing.run("algorithm_id", {parameter_dictionary})

The algorithm id is displayed when you hover over the algorithm in the Processing Toolbox. The parameter dictionary provides the parameter NAMEs and values. See Usando os algoritmos do processamento a partir da consola for details on how to run processing algorithms from the Python console.

28.1.19.7. Distance to nearest hub (points)

Creates a point layer representing the center of the input features with the addition of two fields containing the identifier of the nearest feature (based on its center point) and the distance between the points.

Veja também

Distance to nearest hub (line to hub), Join attributes by nearest

Parâmetros

Label	Nome	Type	Descrição
Source points layer	INPUT	[vector: any]	Vector layer for which the nearest feature is searched
Destination hubs layer	HUBS	[vector: any]	Vector layer containing the features to search for
Hub layer name attribute	FIELD	[tablefield: any]	Field to use to uniquely identify features of the destination layer. Used in the output attribute table
Measurement unit	UNIT	[enumeration] Default: 0	Units in which to report the distance to the closest feature: 0 — Meters 1 — Feet 2 — Miles 3 — Kilometers 4 — Layer units
Hub distance	OUTPUT	[vector: point] Default: [Create temporary layer]	Specify the output point vector layer with the nearest hub. One of: Create Temporary Layer (TEMPORARY_OUTPUT) Save to File… Save to Geopackage… Save to Database Table… The file encoding can also be changed here.

Resultados

Label	Nome	Type	Descrição
Hub distance	OUTPUT	[vector: point]	Point vector layer representing the center of the source features with their attributes, the identifier of their closest feature and the calculated distance.

Python code

Algorithm ID: qgis:distancetonearesthubpoints

import processing
processing.run("algorithm_id", {parameter_dictionary})

The algorithm id is displayed when you hover over the algorithm in the Processing Toolbox. The parameter dictionary provides the parameter NAMEs and values. See Usando os algoritmos do processamento a partir da consola for details on how to run processing algorithms from the Python console.

28.1.19.8. Join by lines (hub lines)

Creates hub and spoke diagrams by connecting lines from points on the Spoke layer to matching points in the Hub layer.

Determination of which hub goes with each point is based on a match between the Hub ID field on the hub points and the Spoke ID field on the spoke points.

If input layers are not point layers, a point on the surface of the geometries will be taken as the connecting location.

Optionally, geodesic lines can be created, which represent the shortest path on the surface of an ellipsoid. When geodesic mode is used, it is possible to split the created lines at the antimeridian (±180 degrees longitude), which can improve rendering of the lines. Additionally, the distance between vertices can be specified. A smaller distance results in a denser, more accurate line.

Fig. 28.42 Join points based on a common field / attribute

Parâmetros

Basic parameters

Label	Nome	Type	Descrição
Hub layer	HUBS	[vector: any]	Input layer
Hub ID field	HUB_FIELD	[tablefield: any]	Field of the hub layer with ID to join
Hub layer fields to copy (leave empty to copy all fields) Opcional	HUB_FIELDS	[tablefield: any] [list]	The field(s) of the hub layer to be copied. If no field(s) are chosen all fields are taken.
Spoke layer	SPOKES	[vector: any]	Additional spoke point layer
Spoke ID field	SPOKE_FIELD	[tablefield: any]	Field of the spoke layer with ID to join
Spoke layer fields to copy (leave empty to copy all fields) Opcional	SPOKE_FIELDS	[tablefield: any] [list]	Field(s) of the spoke layer to be copied. If no fields are chosen all fields are taken.
Create geodesic lines	GEODESIC	[boolean] Default: False	Create geodesic lines (the shortest path on the surface of an ellipsoid)
Hub lines	OUTPUT	[vector: line] Default: [Create temporary layer]	Specify the output hub line vector layer. One of: Create Temporary Layer (TEMPORARY_OUTPUT) Save to File… Save to Geopackage… Save to Database Table… The file encoding can also be changed here.

Advanced parameters

Label	Nome	Type	Descrição
Distance between vertices (geodesic lines only)	GEODESIC_DISTANCE	[number] Default: 1000.0 (kilometers)	Distance between consecutive vertices (in kilometers). A smaller distance results in a denser, more accurate line
Split lines at antimeridian (±180 degrees longitude)	ANTIMERIDIAN_SPLIT	[boolean] Default: False	Split lines at ±180 degrees longitude (to improve rendering of the lines)

Resultados

Label	Nome	Type	Descrição
Hub lines	OUTPUT	[vector: line]	The resulting line layer connecting matching points in input layers

Python code

Algorithm ID: native:hublines

import processing
processing.run("algorithm_id", {parameter_dictionary})

The algorithm id is displayed when you hover over the algorithm in the Processing Toolbox. The parameter dictionary provides the parameter NAMEs and values. See Usando os algoritmos do processamento a partir da consola for details on how to run processing algorithms from the Python console.

28.1.19.9. K-means clustering

Calculates the 2D distance based k-means cluster number for each input feature.

K-means clustering aims to partition the features into k clusters in which each feature belongs to the cluster with the nearest mean. The mean point is represented by the barycenter of the clustered features.

If input geometries are lines or polygons, the clustering is based on the centroid of the feature.

Fig. 28.43 A five class point clusters

Veja também

DBSCAN clustering, ST-DBSCAN clustering

Parâmetros

Label	Nome	Type	Descrição
Input layer	INPUT	[vector: any]	Layer to analyze
Number of clusters	CLUSTERS	[number] Default: 5	Number of clusters to create with the features
Clusters	OUTPUT	[vector: any] Default:[Create temporary layer]	Specify the output vector layer for generated the clusters. One of: Create Temporary Layer (TEMPORARY_OUTPUT) Save to File… Save to Geopackage… Save to Database Table… The file encoding can also be changed here.

Advanced parameters

Label	Nome	Type	Descrição
Cluster field name	FIELD_NAME	[string] Default: “CLUSTER_ID”	Name of the field where the associated cluster number shall be stored
Cluster size field name	SIZE_FIELD_NAME	[string] Default: “CLUSTER_SIZE”	Name of the field with the count of features in the same cluster

Resultados

Label	Nome	Type	Descrição
Clusters	OUTPUT	[vector: any]	Vector layer containing the original features with fields specifying the cluster they belong to and their number in it

Python code

Algorithm ID: native:kmeansclustering

import processing
processing.run("algorithm_id", {parameter_dictionary})

The algorithm id is displayed when you hover over the algorithm in the Processing Toolbox. The parameter dictionary provides the parameter NAMEs and values. See Usando os algoritmos do processamento a partir da consola for details on how to run processing algorithms from the Python console.

28.1.19.10. List unique values

Lists unique values of an attribute table field and counts their number.

Default menu: Vector ► Analysis Tools

Parâmetros

Label	Nome	Type	Descrição
Input layer	INPUT	[vector: any]	Layer to analyze
Target field(s)	FIELDS	[tablefield: any]	Field to analyze
Unique values Opcional	OUTPUT	[table] Default:[Create temporary layer]	Specify the summary table layer with unique values. One of: Skip Output Create Temporary Layer (TEMPORARY_OUTPUT) Save to File… Save to Geopackage… Save to Database Table… The file encoding can also be changed here.
HTML report Opcional	OUTPUT_HTML_FILE	[html] Default:[Save to temporary file]	HTML report of unique values in the Processing ► Results viewer. One of: Skip Output Save to a Temporary File Save to File…

Resultados

Label	Nome	Type	Descrição
Unique values	OUTPUT	[table]	Summary table layer with unique values
HTML report	OUTPUT_HTML_FILE	[html]	HTML report of unique values. Can be opened from the Processing ► Results viewer
Total unique values	TOTAL_VALUES	[number]	The number of unique values in the input field
Unique values concatenated	UNIQUE_VALUES	[string]	A string with the comma separated list of unique values found in the input field

Python code

Algorithm ID: qgis:listuniquevalues

import processing
processing.run("algorithm_id", {parameter_dictionary})

The algorithm id is displayed when you hover over the algorithm in the Processing Toolbox. The parameter dictionary provides the parameter NAMEs and values. See Usando os algoritmos do processamento a partir da consola for details on how to run processing algorithms from the Python console.

28.1.19.11. Mean coordinate(s)

Computes a point layer with the center of mass of geometries in an input layer.

An attribute can be specified as containing weights to be applied to each feature when computing the center of mass.

If an attribute is selected in the parameter, features will be grouped according to values in this field. Instead of a single point with the center of mass of the whole layer, the output layer will contain a center of mass for the features in each category.

Default menu: Vector ► Analysis Tools

Parâmetros

Label	Nome	Type	Descrição
Input layer	INPUT	[vector: any]	Input vector layer
Weight field Opcional	WEIGHT	[tablefield: numeric]	Field to use if you want to perform a weighted mean
Unique ID field	UID	[tablefield: numeric]	Unique field on which the calculation of the mean will be made
Mean coordinates	OUTPUT	[vector: point] Default:[Create temporary layer]	Specify the (point vector) layer for the result. One of: Create Temporary Layer (TEMPORARY_OUTPUT) Save to File… Save to Geopackage… Save to Database Table… The file encoding can also be changed here.

Resultados

Label	Nome	Type	Descrição
Mean coordinates	OUTPUT	[vector: point]	Resulting point(s) layer

Python code

Algorithm ID: native:meancoordinates

import processing
processing.run("algorithm_id", {parameter_dictionary})

The algorithm id is displayed when you hover over the algorithm in the Processing Toolbox. The parameter dictionary provides the parameter NAMEs and values. See Usando os algoritmos do processamento a partir da consola for details on how to run processing algorithms from the Python console.

28.1.19.12. Nearest neighbour analysis

Performs nearest neighbor analysis for a point layer. The output tells you how your data are distributed (clustered, randomly or distributed).

Output is generated as an HTML file with the computed statistical values:

• Observed mean distance

• Expected mean distance

• Nearest neighbour index

• Number of points

• Z-Score: Comparing the Z-Score with the normal distribution tells you how your data are distributed. A low Z-Score means that the data are unlikely to be the result of a spatially random process, while a high Z-Score means that your data are likely to be a result of a spatially random process.

  

Default menu: Vector ► Analysis Tools

Veja também

Join attributes by nearest

Parâmetros

Label	Nome	Type	Descrição
Input layer	INPUT	[vector: point]	Point vector layer to calculate the statistics on
Nearest neighbour Opcional	OUTPUT_HTML_FILE	[html] Default:[Save to temporary file]	Specification of the HTML file for the computed statistics. One of: Skip Output Save to a Temporary File Save to File…

Resultados

Label	Nome	Type	Descrição
Nearest neighbour	OUTPUT_HTML_FILE	[html]	HTML file with the computed statistics
Observed mean distance	OBSERVED_MD	[number]	Observed mean distance
Expected mean distance	EXPECTED_MD	[number]	Expected mean distance
Nearest neighbour index	NN_INDEX	[number]	Nearest neighbour index
Number of points	POINT_COUNT	[number]	Number of points
Z-Score	Z_SCORE	[number]	Z-Score

Python code

Algorithm ID: native:nearestneighbouranalysis

import processing
processing.run("algorithm_id", {parameter_dictionary})

The algorithm id is displayed when you hover over the algorithm in the Processing Toolbox. The parameter dictionary provides the parameter NAMEs and values. See Usando os algoritmos do processamento a partir da consola for details on how to run processing algorithms from the Python console.

28.1.19.13. Overlap analysis

Calculates the area and percentage cover by which features from an input layer are overlapped by features from a selection of overlay layers.

New attributes are added to the output layer reporting the total area of overlap and percentage of the input feature overlapped by each of the selected overlay layers.

Parâmetros

Basic parameters

Label	Nome	Type	Descrição
Input layer	INPUT	[vector: any]	The input layer.
Overlap layers	LAYERS	[vector: any] [list]	The overlay layers.
Overlap	OUTPUT	[same as input] Default: [Create temporary layer]	Specify the output vector layer. One of: Create Temporary Layer (TEMPORARY_OUTPUT) Save to File… Save to Geopackage… Save to Database Table… The file encoding can also be changed here.

Advanced parameters

Label	Nome	Type	Descrição
Grid size Opcional	GRID_SIZE	[number] Default: Not set	If provided, the input geometries are snapped to a grid of the given size, and the result vertices are computed on that same grid. Requires GEOS 3.9.0 or higher.

Resultados

Label	Nome	Type	Descrição
Overlap	OUTPUT	[same as input]	The output layer with additional fields reporting the overlap (in map units and percentage) of the input feature overlapped by each of the selected layers.

Python code

Algorithm ID: native:calculatevectoroverlaps

import processing
processing.run("algorithm_id", {parameter_dictionary})

The algorithm id is displayed when you hover over the algorithm in the Processing Toolbox. The parameter dictionary provides the parameter NAMEs and values. See Usando os algoritmos do processamento a partir da consola for details on how to run processing algorithms from the Python console.

28.1.19.14. Shortest line between features

Creates a line layer as the shortest line between the source and the destination layer. By default only the first nearest feature of the destination layer is taken into account. The n-nearest neighboring features number can be specified. If a maximum distance is specified, then only features which are closer than this distance will be considered.

The output features will contain all the source layer attributes, all the attributes from the n-nearest feature and the additional field of the distance.

Importante

This algorithm uses purely Cartesian calculations for distance, and does not consider geodetic or ellipsoid properties when determining feature proximity. The measurement and output coordinate system is based on the coordinate system of the source layer.

Fig. 28.44 Shortest line from point features to lines

Parâmetros

Label	Nome	Type	Descrição
Source layer	SOURCE	[vector: any]	Origin layer for which to search for nearest neighbors
Destination layer	DESTINATION	[vector: any]	Target Layer in which to search for nearest neighbors
Method	METHOD	[enumeration] Default: 0	Shortest distance calculation method Possible values are: 0 — Distance to nearest point on feature 1 — Distance to feature centroid
Maximum number of neighbors	NEIGHBORS	[number] Default: 1	Maximum number of neighbors to look for
Maximum distance Opcional	DISTANCE	[number]	Only destination features which are closer than this distance will be considered.
Shortest lines	OUTPUT	[vector: line] Default: [Create temporary layer]	Specify the output vector layer. One of: Create Temporary Layer (TEMPORARY_OUTPUT) Save to File… Save to Geopackage… Save to Database Table… The file encoding can also be changed here.

Resultados

Label	Nome	Type	Descrição
Output layer	OUTPUT	[vector: line]	Line vector layer joining source features to their nearest neighbor(s) in the destination layer. Contains all attributes for both source and destination features, and the computed distance.

Python code

Algorithm ID: native:shortestline

import processing
processing.run("algorithm_id", {parameter_dictionary})

The algorithm id is displayed when you hover over the algorithm in the Processing Toolbox. The parameter dictionary provides the parameter NAMEs and values. See Usando os algoritmos do processamento a partir da consola for details on how to run processing algorithms from the Python console.

28.1.19.15. ST-DBSCAN clustering

Clusters point features based on a 2D implementation of spatiotemporal Density-based clustering of applications with noise (ST-DBSCAN) algorithm.

Veja também

DBSCAN clustering, K-means clustering

Parâmetros

Basic parameters

Label	Nome	Type	Descrição
Input layer	INPUT	[vector: point]	Layer to analyze
Date/time field	DATETIME_FIELD	[tablefield: date]	Field containing the temporal information
Minimum cluster size	MIN_SIZE	[number] Default: 5	Minimum number of features to generate a cluster
Maximum distance between clustered points	EPS	[number] Default: 1.0	Distance beyond which two features can not belong to the same cluster (eps)
Maximum time duration between clustered points	EPS2	[number] Default: 0.0 (days)	Time duration beyond which two features can not belong to the same cluster (eps2). Available time units are milliseconds, seconds, minutes, hours, days and weeks.
Clusters	OUTPUT	[vector: point] Default: [Create temporary layer]	Specify the vector layer for the result of the clustering. One of: Create Temporary Layer (TEMPORARY_OUTPUT) Save to File… Save to Geopackage… Save to Database Table… The file encoding can also be changed here.

Advanced parameters

Label	Nome	Type	Descrição
Treat border points as noise (DBSCAN*) Opcional	DBSCAN*	[boolean] Default: False	If checked, points on the border of a cluster are themselves treated as unclustered points, and only points in the interior of a cluster are tagged as clustered.
Cluster field name	FIELD_NAME	[string] Default: “CLUSTER_ID”	Name of the field where the associated cluster number shall be stored
Cluster size field name	SIZE_FIELD_NAME	[string] Default: “CLUSTER_SIZE”	Name of the field with the count of features in the same cluster

Resultados

Label	Nome	Type	Descrição
Clusters	OUTPUT	[vector: point]	Vector layer containing the original features with a field setting the cluster they belong to
Number of clusters	NUM_CLUSTERS	[number]	The number of clusters discovered

Python code

Algorithm ID: native:stdbscanclustering

import processing
processing.run("algorithm_id", {parameter_dictionary})

The algorithm id is displayed when you hover over the algorithm in the Processing Toolbox. The parameter dictionary provides the parameter NAMEs and values. See Usando os algoritmos do processamento a partir da consola for details on how to run processing algorithms from the Python console.

28.1.19.16. Statistics by categories

Calculates statistics of a field depending on a parent class. The parent class is a combination of values from other fields.

Parâmetros

Label	Nome	Type	Descrição
Input vector layer	INPUT	[vector: any]	Input vector layer with unique classes and values
Field to calculate statistics on (if empty, only count is calculated) Opcional	VALUES_FIELD_NAME	[tablefield: any]	If empty only the count will be calculated
Field(s) with categories	CATEGORIES_FIELD_NAME	[vector: any] [list]	The fields that (combined) define the categories
Statistics by category	OUTPUT	[table] Default: [Create temporary layer]	Specify the output table for the generated statistics. One of: Create Temporary Layer (TEMPORARY_OUTPUT) Save to File… Save to Geopackage… Save to Database Table… The file encoding can also be changed here.

Resultados

Label	Nome	Type	Descrição
Statistics by category	OUTPUT	[table]	Table containing the statistics

Depending on the type of the field being analyzed, the following statistics are returned for each grouped value:

Estatísitcas	Cadeia de carateres	Numérico	Data
Count (COUNT)
Unique values (UNIQUE)
Empty (null) values (EMPTY)
Non-empty values (FILLED)
Minimal value (MIN)
Maximal value (MAX)
Range (RANGE)
Sum (SUM)
Mean value (MEAN)
Median value (MEDIAN)
Standard Deviation (STD_DEV)
Coefficient of variation (CV)
Minority (rarest occurring value - MINORITY)
Majority (most frequently occurring value - MAJORITY)
First Quartile (FIRSTQUARTILE)
Third Quartile (THIRDQUARTILE)
Inter Quartile Range (IQR)
Minimum Length (MIN_LENGTH)
Mean Length (MEAN_LENGTH)
Maximum Length (MAX_LENGTH)

Python code

Algorithm ID: qgis:statisticsbycategories

import processing
processing.run("algorithm_id", {parameter_dictionary})

The algorithm id is displayed when you hover over the algorithm in the Processing Toolbox. The parameter dictionary provides the parameter NAMEs and values. See Usando os algoritmos do processamento a partir da consola for details on how to run processing algorithms from the Python console.

28.1.19.17. Sum line lengths

Takes a polygon layer and a line layer and measures the total length of lines and the total number of them that cross each polygon.

The resulting layer has the same features as the input polygon layer, but with two additional attributes containing the length and count of the lines across each polygon.

Allows features in-place modification of polygon features

Default menu: Vector ► Analysis Tools

Parâmetros

Label	Nome	Type	Descrição
Lines	LINES	[vector: line]	Input vector line layer
Polygons	POLYGONS	[vector: polygon]	Polygon vector layer
Lines length field name	LEN_FIELD	[string] Default: “LENGTH”	Name of the field for the lines length
Lines count field name	COUNT_FIELD	[string] Default: “COUNT”	Name of the field for the lines count
Line length	OUTPUT	[vector: polygon] Default: [Create temporary layer]	Specify the output polygon layer with generated statistics. One of: Create Temporary Layer (TEMPORARY_OUTPUT) Save to File… Save to Geopackage… Save to Database Table… The file encoding can also be changed here.

Resultados

Label	Nome	Type	Descrição
Line length	OUTPUT	[vector: polygon]	Polygon output layer with fields of lines length and line count

Python code

Algorithm ID: native:sumlinelengths

import processing
processing.run("algorithm_id", {parameter_dictionary})

The algorithm id is displayed when you hover over the algorithm in the Processing Toolbox. The parameter dictionary provides the parameter NAMEs and values. See Usando os algoritmos do processamento a partir da consola for details on how to run processing algorithms from the Python console.