Attribute Analysis

Add Field

Function name: add_field

Experimental

Adds a new attribute field with an optional default value.

vector schema attributes

Parameters

NameDescriptionRequiredDefault inputInput vector layer.Requiredinput.shp fieldNew field name.RequiredNEW_FIELD field_typeField type: integer, float, text, boolean.Requiredfloat defaultOptional default value.Optional— outputOutput vector path.Required—

Examples

Adds a typed field to the layer schema. wbe.add_field(default=0.0, field='NEW_FIELD', field_type='float', input='input.shp', output='add_field.shp')

Add Geometry Attributes

Function name: add_geometry_attributes

Experimental

Adds area, length, perimeter, and centroid attributes to vector features.

vector attributes measurements

Parameters

NameDescriptionRequiredDefault inputInput vector layer.Requiredinput.shp areaInclude AREA field (default true).OptionalTrue lengthInclude LENGTH field (default true).OptionalTrue perimeterInclude PERIMETER field (default true).OptionalTrue centroidInclude centroid X/Y fields (default true).OptionalTrue outputOutput vector path.Required—

Examples

Adds geometry-derived attributes to each feature. wbe.add_geometry_attributes(area=True, centroid=True, input='input.shp', length=True, output='geometry_attributes.shp', perimeter=True)

Attribute Correlation

Function name: attribute_correlation

This tool can be used to estimate the Pearson product-moment correlation coefficient (r) for each pair among a group of attributes associated with the database file of a shapefile. The r-value is a measure of the linear association in the variation of the attributes. The coefficient ranges from -1, indicated a perfect negative linear association, to 1, indicated a perfect positive linear association. An r-value of 0 indicates no correlation between the test variables.

Notice that this index is a measure of the linear association; two variables may be strongly related by a non-linear association (e.g. a power function curve) which will lead to an apparent weak association based on the Pearson coefficient. In fact, non-linear associations are very common among spatial variables, e.g. terrain indices such as slope and contributing area. In such cases, it is advisable that the input images are transformed prior to the estimation of the Pearson coefficient, or that an alternative, non-parametric statistic be used, e.g. the Spearman rank correlation coefficient.

The user must specify the name of the input vector Shapefile (input). Correlations will be calculated for each pair of numerical attributes contained within the input file's attribute table and presented in a correlation matrix HMTL output (output).

See Also

image_correlation, attribute_scattergram, attribute_histogram

Python API

def attribute_correlation(self, input: Vector, output_html_file: str) -> None:

Attribute Histogram

Function name: attribute_histogram

This tool can be used to create a histogram, which is a graph displaying the frequency distribution of data, for the values contained in a field of an input vector's attribute table. The user must specify the name of an input vector (input) and the name of one of the fields (field) contained in the associated attribute table. The tool output (output) is an HTML formatted histogram analysis report. If the specified field is non-numerical, the tool will produce a bar-chart of class frequency, similar to the tabular output of the list_unique_values tool.

See Also

list_unique_values, raster_histogram

Python API

def attribute_histogram(self, input: Vector, field_name: str, output_html_file: str) -> None:

Attribute Scattergram

Function name: attribute_scattergram

This tool can be used to create a scattergram for two numerical fields (fieldx and fieldy) contained within an input vector's attribute table (input). The user must specify the name of an input shapefile and the name of two of the fields contained it the associated attribute table. The tool output (output) is an HTML formatted report containing a graphical scattergram plot.

See Also

attribute_histogram, attribute_correlation

Python API

def attribute_scattergram(self, input: Vector, field_name_x: str, field_name_y: str, output_html_file: str, add_trendline: bool = False) -> None:

Delete Field

Function name: delete_field

Experimental

Deletes one or more attribute fields from a vector layer.

vector schema attributes

Parameters

NameDescriptionRequiredDefault inputInput vector layer.Requiredinput.shp fieldsComma-delimited field names to delete.RequiredFIELD_A,FIELD_B outputOutput vector path.Required—

Examples

Removes selected fields from a layer schema. wbe.delete_field(fields='FIELD_A,FIELD_B', input='input.shp', output='fields_deleted.shp')

Extract By Attribute

Function name: extract_by_attribute

This tool extracts features from an input vector into an output file based on attribute properties. The user must specify the name of the input (--input) and output (--output) files, along with the filter statement (--statement). The conditional statement is a single-line logical condition containing one or more attribute variables contained in the file's attribute table that evaluates to TRUE/FALSE. In addition to the common comparison and logical operators, i.e. < > <= >= == (EQUAL TO) != (NOT EQUAL TO) || (OR) && (AND), conditional statements may contain a any valid mathematical operation and the null value. IdentifierArgument AmountArgument TypesDescription min>= 1NumericReturns the minimum of the arguments max>= 1NumericReturns the maximum of the arguments len1String/TupleReturns the character length of a string, or the amount of elements in a tuple (not recursively) floor1NumericReturns the largest integer less than or equal to a number round1NumericReturns the nearest integer to a number. Rounds half-way cases away from 0.0 ceil1NumericReturns the smallest integer greater than or equal to a number if3Boolean, Any, AnyIf the first argument is true, returns the second argument, otherwise, returns the third contains2Tuple, any non-tupleReturns true if second argument exists in first tuple argument. contains_any2Tuple, Tuple of any non-tupleReturns true if one of the values in the second tuple argument exists in first tuple argument. typeof1Anyreturns "string", "float", "int", "boolean", "tuple", or "empty" depending on the type of the argument math::is_nan1NumericReturns true if the argument is the floating-point value NaN, false if it is another floating-point value, and throws an error if it is not a number math::is_finite1NumericReturns true if the argument is a finite floating-point number, false otherwise math::is_infinite1NumericReturns true if the argument is an infinite floating-point number, false otherwise math::is_normal1NumericReturns true if the argument is a floating-point number that is neither zero, infinite, subnormal, or NaN, false otherwise math::ln1NumericReturns the natural logarithm of the number math::log2Numeric, NumericReturns the logarithm of the number with respect to an arbitrary base math::log21NumericReturns the base 2 logarithm of the number math::log101NumericReturns the base 10 logarithm of the number math::exp1NumericReturns e^(number), (the exponential function) math::exp21NumericReturns 2^(number) math::pow2Numeric, NumericRaises a number to the power of the other number math::cos1NumericComputes the cosine of a number (in radians) math::acos1NumericComputes the arccosine of a number. The return value is in radians in the range [0, pi] or NaN if the number is outside the range [-1, 1] math::cosh1NumericHyperbolic cosine function math::acosh1NumericInverse hyperbolic cosine function math::sin1NumericComputes the sine of a number (in radians) math::asin1NumericComputes the arcsine of a number. The return value is in radians in the range [-pi/2, pi/2] or NaN if the number is outside the range [-1, 1] math::sinh1NumericHyperbolic sine function math::asinh1NumericInverse hyperbolic sine function math::tan1NumericComputes the tangent of a number (in radians) math::atan1NumericComputes the arctangent of a number. The return value is in radians in the range [-pi/2, pi/2] math::atan22Numeric, NumericComputes the four quadrant arctangent in radians math::tanh1NumericHyperbolic tangent function math::atanh1NumericInverse hyperbolic tangent function. math::sqrt1NumericReturns the square root of a number. Returns NaN for a negative number math::cbrt1NumericReturns the cube root of a number math::hypot2NumericCalculates the length of the hypotenuse of a right-angle triangle given legs of length given by the two arguments math::abs1NumericReturns the absolute value of a number, returning an integer if the argument was an integer, and a float otherwise str::regex_matches2String, StringReturns true if the first argument matches the regex in the second argument (Requires regex_support feature flag) str::regex_replace3String, String, StringReturns the first argument with all matches of the regex in the second argument replaced by the third argument (Requires regex_support feature flag) str::to_lowercase1StringReturns the lower-case version of the string str::to_uppercase1StringReturns the upper-case version of the string str::trim1StringStrips whitespace from the start and the end of the string str::from>= 0AnyReturns passed value as string bitand2IntComputes the bitwise and of the given integers bitor2IntComputes the bitwise or of the given integers bitxor2IntComputes the bitwise xor of the given integers bitnot1IntComputes the bitwise not of the given integer shl2IntComputes the given integer bitwise shifted left by the other given integer shr2IntComputes the given integer bitwise shifted right by the other given integer random0EmptyReturn a random float between 0 and 1. Requires the rand feature flag. pi0EmptyReturn the value of the PI constant./

The following are examples of valid conditional statements:

`HEIGHT >= 300.0

CROP == "corn"

(ELEV >= 525.0) && (HGT_AB_GR <= 5.0)

math::ln(CARBON) > 1.0

VALUE == null `

Python API

def extract_by_attribute(self, input: Vector, statement: str) -> Vector:

Field Calculator

Function name: field_calculator

Experimental

Calculates or updates a field value from SQL-style or expression-style formulas using feature attributes and geometry variables.

vector attributes expression

Parameters

NameDescriptionRequiredDefault inputInput vector layer.Requiredinput.shp fieldOutput field name.Requiredscore field_typeOutput field type: float, integer, text.Optionalfloat expressionExpression or SQL-style UPDATE assignment evaluated per feature.RequiredVALUE * 2.0 + $area overwriteOverwrite existing field if present (default true).OptionalTrue preview_rowsOptional number of preview rows to return in payload.Optional0 outputOutput vector path. Optional when preview_rows > 0.Optional—

Examples

Computes a derived numeric field using attributes and geometry. wbe.field_calculator(expression='VALUE * 2.0 + $area', field='score', field_type='float', input='input.shp', output='field_calc.shp', overwrite=True)

SQL-style conditional update using CASE and UPDATE wrapper. wbe.field_calculator(input='roads.gpkg', field='SPEED', field_type='integer', expression="UPDATE roads SET SPEED = CASE WHEN TYPE == 'motorway' THEN 100 WHEN TYPE == 'primary' THEN 80 ELSE 60 END", overwrite=True, output='roads_speed.gpkg')

Preview-only evaluation for first 10 rows (no output write). wbe.field_calculator(input='roads.gpkg', field='SPEED', field_type='integer', expression="CASE TYPE WHEN 'motorway' THEN 100 ELSE 60 END", overwrite=True, preview_rows=10)

Filter Vector Features By Area

Function name: filter_vector_features_by_area

Experimental

Filters polygon features below a minimum area threshold.

vector gis filter polygon legacy-port

Parameters

NameDescriptionRequiredDefault inputInput polygon vector layer.Requiredpolygons.shp thresholdMinimum polygon area to retain, in layer coordinate units squared.Required1000.0 outputOutput vector path.Required—

Examples

Removes polygons smaller than the specified area threshold. wbe.filter_vector_features_by_area(input='polygons.shp', output='filtered_polygons.shp', threshold=1000.0)

List Unique Values

Function name: list_unique_values

This tool can be used to list each of the unique values contained within a categorical field of an input vector file's attribute table. The tool outputs an HTML formatted report (output) containing a table of the unique values and their frequency of occurrence within the data. The user must specify the name of an input shapefile (input) and the name of one of the fields (field) contained in the associated attribute table. The specified field should not contained floating-point numerical data, since the number of categories will likely equal the number of records, which may be quite large. The tool effectively provides tabular output that is similar to the graphical output provided by the attribute_histogram tool, which, however, can be applied to continuous data.

See Also

attribute_histogram

Python API

def list_unique_values(self, input: Vector, field_name: str) -> Tuple[str, int]:

Rename Field

Function name: rename_field

Experimental

Renames an attribute field in a vector layer.

vector schema attributes

Parameters

NameDescriptionRequiredDefault inputInput vector layer.Requiredinput.shp fieldExisting field name.RequiredOLD_NAME new_fieldReplacement field name.RequiredNEW_NAME outputOutput vector path.Required—

Examples

Renames one attribute field. wbe.rename_field(field='OLD_NAME', input='input.shp', new_field='NEW_NAME', output='renamed.shp')