UPDATE: Adds 56 functions in the Statistical section
Uses statrs for numerical functions REFACTOR: Put statistical functions on its own module This might seem counter-intuitive but the wasm build after this refactor is 1528 bytes smaller :)
This commit is contained in:
Nicolás Hatcher
committed by
Nicolás Hatcher Andrés
Nicolás Hatcher Andrés
parent
67ef3bcf87
commit
6822505602
264
base/src/functions/statistical/covariance.rs
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264
base/src/functions/statistical/covariance.rs
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@@ -0,0 +1,264 @@
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use crate::expressions::types::CellReferenceIndex;
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use crate::{
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calc_result::CalcResult, expressions::parser::Node, expressions::token::Error, model::Model,
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};
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impl Model {
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pub(crate) fn fn_covariance_p(
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&mut self,
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args: &[Node],
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cell: CellReferenceIndex,
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) -> CalcResult {
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if args.len() != 2 {
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return CalcResult::new_args_number_error(cell);
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}
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let values1_opts = match self.evaluate_node_in_context(&args[0], cell) {
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CalcResult::Range { left, right } => match self.values_from_range(left, right) {
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Ok(v) => v,
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Err(error) => return error,
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},
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CalcResult::Array(a) => match self.values_from_array(a) {
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Ok(v) => v,
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Err(error) => {
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return CalcResult::new_error(
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Error::VALUE,
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cell,
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format!("Error in first array: {:?}", error),
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);
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}
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},
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_ => {
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return CalcResult::new_error(
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Error::VALUE,
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cell,
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"First argument must be a range or array".to_string(),
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);
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}
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};
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let values2_opts = match self.evaluate_node_in_context(&args[1], cell) {
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CalcResult::Range { left, right } => match self.values_from_range(left, right) {
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Ok(v) => v,
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Err(error) => return error,
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},
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CalcResult::Array(a) => match self.values_from_array(a) {
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Ok(v) => v,
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Err(error) => {
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return CalcResult::new_error(
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Error::VALUE,
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cell,
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format!("Error in second array: {:?}", error),
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);
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}
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},
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_ => {
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return CalcResult::new_error(
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Error::VALUE,
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cell,
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"Second argument must be a range or array".to_string(),
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);
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}
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};
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// Same number of cells
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if values1_opts.len() != values2_opts.len() {
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return CalcResult::new_error(
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Error::NA,
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cell,
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"COVARIANCE.P requires arrays of the same size".to_string(),
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);
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}
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// Count numeric data points in each array (ignoring text/booleans/empty)
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let count1 = values1_opts.iter().filter(|v| v.is_some()).count();
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let count2 = values2_opts.iter().filter(|v| v.is_some()).count();
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if count1 == 0 || count2 == 0 {
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return CalcResult::new_error(
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Error::DIV,
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cell,
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"COVARIANCE.P requires at least one numeric value in each array".to_string(),
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);
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}
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if count1 != count2 {
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return CalcResult::new_error(
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Error::NA,
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cell,
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"COVARIANCE.P arrays must have the same number of numeric data points".to_string(),
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);
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}
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// Build paired numeric vectors, position by position
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let mut xs: Vec<f64> = Vec::with_capacity(count1);
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let mut ys: Vec<f64> = Vec::with_capacity(count2);
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for (v1_opt, v2_opt) in values1_opts.into_iter().zip(values2_opts.into_iter()) {
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if let (Some(x), Some(y)) = (v1_opt, v2_opt) {
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xs.push(x);
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ys.push(y);
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}
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}
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let n = xs.len();
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if n == 0 {
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// Should be impossible given the checks above, but guard anyway
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return CalcResult::new_error(
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Error::DIV,
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cell,
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"COVARIANCE.P has no paired numeric data points".to_string(),
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);
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}
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let n_f = n as f64;
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let mut sum_x = 0.0;
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let mut sum_y = 0.0;
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for i in 0..n {
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sum_x += xs[i];
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sum_y += ys[i];
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}
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let mean_x = sum_x / n_f;
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let mean_y = sum_y / n_f;
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let mut sum_prod = 0.0;
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for i in 0..n {
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let dx = xs[i] - mean_x;
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let dy = ys[i] - mean_y;
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sum_prod += dx * dy;
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}
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let cov = sum_prod / n_f;
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CalcResult::Number(cov)
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}
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pub(crate) fn fn_covariance_s(
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&mut self,
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args: &[Node],
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cell: CellReferenceIndex,
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) -> CalcResult {
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if args.len() != 2 {
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return CalcResult::new_args_number_error(cell);
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}
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let values1_opts = match self.evaluate_node_in_context(&args[0], cell) {
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CalcResult::Range { left, right } => match self.values_from_range(left, right) {
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Ok(v) => v,
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Err(error) => return error,
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},
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CalcResult::Array(a) => match self.values_from_array(a) {
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Ok(v) => v,
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Err(error) => {
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return CalcResult::new_error(
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Error::VALUE,
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cell,
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format!("Error in first array: {:?}", error),
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);
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}
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},
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_ => {
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return CalcResult::new_error(
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Error::VALUE,
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cell,
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"First argument must be a range or array".to_string(),
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);
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}
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};
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let values2_opts = match self.evaluate_node_in_context(&args[1], cell) {
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CalcResult::Range { left, right } => match self.values_from_range(left, right) {
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Ok(v) => v,
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Err(error) => return error,
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},
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CalcResult::Array(a) => match self.values_from_array(a) {
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Ok(v) => v,
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Err(error) => {
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return CalcResult::new_error(
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Error::VALUE,
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cell,
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format!("Error in second array: {:?}", error),
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);
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}
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},
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_ => {
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return CalcResult::new_error(
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Error::VALUE,
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cell,
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"Second argument must be a range or array".to_string(),
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);
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}
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};
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// Same number of cells
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if values1_opts.len() != values2_opts.len() {
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return CalcResult::new_error(
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Error::NA,
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cell,
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"COVARIANCE.S requires arrays of the same size".to_string(),
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);
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}
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// Count numeric data points in each array (ignoring text/booleans/empty)
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let count1 = values1_opts.iter().filter(|v| v.is_some()).count();
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let count2 = values2_opts.iter().filter(|v| v.is_some()).count();
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if count1 == 0 || count2 == 0 {
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return CalcResult::new_error(
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Error::DIV,
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cell,
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"COVARIANCE.S requires numeric values in each array".to_string(),
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);
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}
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if count1 != count2 {
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return CalcResult::new_error(
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Error::NA,
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cell,
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"COVARIANCE.S arrays must have the same number of numeric data points".to_string(),
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);
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}
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// Build paired numeric vectors
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let mut xs: Vec<f64> = Vec::with_capacity(count1);
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let mut ys: Vec<f64> = Vec::with_capacity(count2);
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for (v1_opt, v2_opt) in values1_opts.into_iter().zip(values2_opts.into_iter()) {
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if let (Some(x), Some(y)) = (v1_opt, v2_opt) {
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xs.push(x);
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ys.push(y);
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}
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}
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let n = xs.len();
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if n < 2 {
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return CalcResult::new_error(
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Error::DIV,
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cell,
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"COVARIANCE.S requires at least two paired data points".to_string(),
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);
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}
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let n_f = n as f64;
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let mut sum_x = 0.0;
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let mut sum_y = 0.0;
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for i in 0..n {
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sum_x += xs[i];
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sum_y += ys[i];
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}
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let mean_x = sum_x / n_f;
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let mean_y = sum_y / n_f;
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let mut sum_prod = 0.0;
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for i in 0..n {
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let dx = xs[i] - mean_x;
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let dy = ys[i] - mean_y;
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sum_prod += dx * dy;
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}
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let cov = sum_prod / (n_f - 1.0);
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CalcResult::Number(cov)
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}
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}
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