Struct Statistics 

pub struct Statistics {
    pub params: Box<StatisticsParameters>,
    pub sources: Box<MultipleRasterOrSingleVectorSource>,
    pub type: Type,
}

Statistics : The Statistics operator is a plot operator that computes count statistics over - a selection of numerical columns of a single vector dataset, or - multiple raster datasets. The output is a JSON description. For instance, you want to get an overview of a raster data source. Then, you can use this operator to get basic count statistics. ## Vector Data In the case of vector data, the operator generates one statistic for each of the selected numerical attributes. The operator returns an error if one of the selected attributes is not numeric. ## Raster Data For raster data, the operator generates one statistic for each input raster. ## Inputs The operator consumes exactly one vector or multiple raster operators. | Parameter | Type | | ——— | ———————————— | | source | MultipleRasterOrSingleVectorSource | ## Errors The operator returns an error in the following cases. - Vector data: The attribute for one of the given columnNames is not numeric. - Vector data: The attribute for one of the given columnNames does not exist. - Raster data: The length of the columnNames parameter does not match the number of input rasters. ### Example Output json { \"A\": { \"valueCount\": 6, \"validCount\": 6, \"min\": 1.0, \"max\": 6.0, \"mean\": 3.5, \"stddev\": 1.707, \"percentiles\": [ { \"percentile\": 0.25, \"value\": 2.0 }, { \"percentile\": 0.5, \"value\": 3.5 }, { \"percentile\": 0.75, \"value\": 5.0 } ] } }

Fields

params: Box<StatisticsParameters>

sources: Box<MultipleRasterOrSingleVectorSource>

type: Type

Implementations

impl Statistics

pub fn new( params: StatisticsParameters, sources: MultipleRasterOrSingleVectorSource, type: Type, ) -> Statistics

The Statistics operator is a plot operator that computes count statistics over - a selection of numerical columns of a single vector dataset, or - multiple raster datasets. The output is a JSON description. For instance, you want to get an overview of a raster data source. Then, you can use this operator to get basic count statistics. ## Vector Data In the case of vector data, the operator generates one statistic for each of the selected numerical attributes. The operator returns an error if one of the selected attributes is not numeric. ## Raster Data For raster data, the operator generates one statistic for each input raster. ## Inputs The operator consumes exactly one vector or multiple raster operators. | Parameter | Type | | ——— | ———————————— | | source | MultipleRasterOrSingleVectorSource | ## Errors The operator returns an error in the following cases. - Vector data: The attribute for one of the given columnNames is not numeric. - Vector data: The attribute for one of the given columnNames does not exist. - Raster data: The length of the columnNames parameter does not match the number of input rasters. ### Example Output json { \"A\": { \"valueCount\": 6, \"validCount\": 6, \"min\": 1.0, \"max\": 6.0, \"mean\": 3.5, \"stddev\": 1.707, \"percentiles\": [ { \"percentile\": 0.25, \"value\": 2.0 }, { \"percentile\": 0.5, \"value\": 3.5 }, { \"percentile\": 0.75, \"value\": 5.0 } ] } }

Trait Implementations

impl Clone for Statistics

fn clone(&self) -> Statistics

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for Statistics

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for Statistics

fn default() -> Statistics

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for Statistics

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl PartialEq for Statistics

fn eq(&self, other: &Statistics) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl Serialize for Statistics

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl StructuralPartialEq for Statistics