fix: mobile adjustments

base/src/expressions/parser/static_analysis.rs

@@ -711,7 +711,6 @@ fn get_function_args_signature(kind: &Function, arg_count: usize) -> Vec<Signatu
         Function::Value => args_signature_scalars(arg_count, 1, 0),
         Function::Valuetotext => args_signature_scalars(arg_count, 1, 1),
         Function::Average => vec![Signature::Vector; arg_count],
-        Function::Avedev => vec![Signature::Vector; arg_count],
         Function::Averagea => vec![Signature::Vector; arg_count],
         Function::Averageif => args_signature_sumif(arg_count),
         Function::Averageifs => vec![Signature::Vector; arg_count],
@@ -890,105 +889,6 @@ fn get_function_args_signature(kind: &Function, arg_count: usize) -> Vec<Signatu
         Function::Dvar => vec![Signature::Vector, Signature::Scalar, Signature::Vector],
         Function::Dvarp => vec![Signature::Vector, Signature::Scalar, Signature::Vector],
         Function::Dstdevp => vec![Signature::Vector, Signature::Scalar, Signature::Vector],
-
-        Function::BetaDist => args_signature_scalars(arg_count, 4, 2),
-        Function::BetaInv => args_signature_scalars(arg_count, 3, 2),
-        Function::BinomDist => args_signature_scalars(arg_count, 4, 0),
-        Function::BinomDistRange => args_signature_scalars(arg_count, 3, 1),
-        Function::BinomInv => args_signature_scalars(arg_count, 3, 0),
-        Function::ChisqDist => args_signature_scalars(arg_count, 4, 0),
-        Function::ChisqDistRT => args_signature_scalars(arg_count, 3, 0),
-        Function::ChisqInv => args_signature_scalars(arg_count, 3, 0),
-        Function::ChisqInvRT => args_signature_scalars(arg_count, 2, 0),
-        Function::ChisqTest => {
-            if arg_count == 2 {
-                vec![Signature::Vector, Signature::Vector]
-            } else {
-                vec![Signature::Error; arg_count]
-            }
-        }
-        Function::ConfidenceNorm => args_signature_scalars(arg_count, 3, 0),
-        Function::ConfidenceT => args_signature_scalars(arg_count, 3, 0),
-        Function::CovarianceP => {
-            if arg_count == 2 {
-                vec![Signature::Vector, Signature::Vector]
-            } else {
-                vec![Signature::Error; arg_count]
-            }
-        }
-        Function::CovarianceS => {
-            if arg_count == 2 {
-                vec![Signature::Vector, Signature::Vector]
-            } else {
-                vec![Signature::Error; arg_count]
-            }
-        }
-        Function::Devsq => vec![Signature::Vector; arg_count],
-        Function::ExponDist => args_signature_scalars(arg_count, 3, 0),
-        Function::FDist => args_signature_scalars(arg_count, 4, 0),
-        Function::FDistRT => args_signature_scalars(arg_count, 3, 0),
-        Function::FInv => args_signature_scalars(arg_count, 3, 0),
-        Function::FInvRT => args_signature_scalars(arg_count, 3, 0),
-        Function::Fisher => args_signature_scalars(arg_count, 1, 0),
-        Function::FisherInv => args_signature_scalars(arg_count, 1, 0),
-        Function::Gamma => args_signature_scalars(arg_count, 1, 0),
-        Function::GammaDist => args_signature_scalars(arg_count, 4, 0),
-        Function::GammaInv => args_signature_scalars(arg_count, 3, 0),
-        Function::GammaLn => args_signature_scalars(arg_count, 1, 0),
-        Function::GammaLnPrecise => args_signature_scalars(arg_count, 1, 0),
-        Function::HypGeomDist => args_signature_scalars(arg_count, 5, 0),
-        Function::LogNormDist => args_signature_scalars(arg_count, 4, 0),
-        Function::LogNormInv => args_signature_scalars(arg_count, 3, 0),
-        Function::NegbinomDist => args_signature_scalars(arg_count, 4, 0),
-        Function::NormDist => args_signature_scalars(arg_count, 4, 0),
-        Function::NormInv => args_signature_scalars(arg_count, 3, 0),
-        Function::NormSdist => args_signature_scalars(arg_count, 2, 0),
-        Function::NormSInv => args_signature_scalars(arg_count, 1, 0),
-        Function::Pearson => {
-            if arg_count == 2 {
-                vec![Signature::Vector, Signature::Vector]
-            } else {
-                vec![Signature::Error; arg_count]
-            }
-        }
-        Function::Phi => args_signature_scalars(arg_count, 1, 0),
-        Function::PoissonDist => args_signature_scalars(arg_count, 3, 0),
-        Function::Standardize => args_signature_scalars(arg_count, 3, 0),
-        Function::StDevP => vec![Signature::Vector; arg_count],
-        Function::StDevS => vec![Signature::Vector; arg_count],
-        Function::Stdeva => vec![Signature::Vector; arg_count],
-        Function::Stdevpa => vec![Signature::Vector; arg_count],
-        Function::TDist => args_signature_scalars(arg_count, 3, 0),
-        Function::TDist2T => args_signature_scalars(arg_count, 2, 0),
-        Function::TDistRT => args_signature_scalars(arg_count, 2, 0),
-        Function::TInv => args_signature_scalars(arg_count, 2, 0),
-        Function::TInv2T => args_signature_scalars(arg_count, 2, 0),
-        Function::TTest => {
-            if arg_count == 4 {
-                vec![
-                    Signature::Vector,
-                    Signature::Vector,
-                    Signature::Scalar,
-                    Signature::Scalar,
-                ]
-            } else {
-                vec![Signature::Error; arg_count]
-            }
-        }
-        Function::VarP => vec![Signature::Vector; arg_count],
-        Function::VarS => vec![Signature::Vector; arg_count],
-        Function::VarpA => vec![Signature::Vector; arg_count],
-        Function::VarA => vec![Signature::Vector; arg_count],
-        Function::WeibullDist => args_signature_scalars(arg_count, 4, 0),
-        Function::ZTest => {
-            if arg_count == 2 {
-                vec![Signature::Vector, Signature::Scalar]
-            } else if arg_count == 3 {
-                vec![Signature::Vector, Signature::Scalar, Signature::Scalar]
-            } else {
-                vec![Signature::Error; arg_count]
-            }
-        }
     }
 }
 
@@ -1090,7 +990,6 @@ fn static_analysis_on_function(kind: &Function, args: &[Node]) -> StaticResult {
         Function::Valuetotext => not_implemented(args),
         Function::Average => not_implemented(args),
         Function::Averagea => not_implemented(args),
-        Function::Avedev => not_implemented(args),
         Function::Averageif => not_implemented(args),
         Function::Averageifs => not_implemented(args),
         Function::Count => not_implemented(args),
@@ -1266,61 +1165,5 @@ fn static_analysis_on_function(kind: &Function, args: &[Node]) -> StaticResult {
         Function::Dvar => not_implemented(args),
         Function::Dvarp => not_implemented(args),
         Function::Dstdevp => not_implemented(args),
-
-        Function::BetaDist => StaticResult::Scalar,
-        Function::BetaInv => StaticResult::Scalar,
-        Function::BinomDist => StaticResult::Scalar,
-        Function::BinomDistRange => StaticResult::Scalar,
-        Function::BinomInv => StaticResult::Scalar,
-        Function::ChisqDist => StaticResult::Scalar,
-        Function::ChisqDistRT => StaticResult::Scalar,
-        Function::ChisqInv => StaticResult::Scalar,
-        Function::ChisqInvRT => StaticResult::Scalar,
-        Function::ChisqTest => StaticResult::Scalar,
-        Function::ConfidenceNorm => StaticResult::Scalar,
-        Function::ConfidenceT => StaticResult::Scalar,
-        Function::CovarianceP => StaticResult::Scalar,
-        Function::CovarianceS => StaticResult::Scalar,
-        Function::Devsq => StaticResult::Scalar,
-        Function::ExponDist => StaticResult::Scalar,
-        Function::FDist => StaticResult::Scalar,
-        Function::FDistRT => StaticResult::Scalar,
-        Function::FInv => StaticResult::Scalar,
-        Function::FInvRT => StaticResult::Scalar,
-        Function::Fisher => StaticResult::Scalar,
-        Function::FisherInv => StaticResult::Scalar,
-        Function::Gamma => StaticResult::Scalar,
-        Function::GammaDist => StaticResult::Scalar,
-        Function::GammaInv => StaticResult::Scalar,
-        Function::GammaLn => StaticResult::Scalar,
-        Function::GammaLnPrecise => StaticResult::Scalar,
-        Function::HypGeomDist => StaticResult::Scalar,
-        Function::LogNormDist => StaticResult::Scalar,
-        Function::LogNormInv => StaticResult::Scalar,
-        Function::NegbinomDist => StaticResult::Scalar,
-        Function::NormDist => StaticResult::Scalar,
-        Function::NormInv => StaticResult::Scalar,
-        Function::NormSdist => StaticResult::Scalar,
-        Function::NormSInv => StaticResult::Scalar,
-        Function::Pearson => StaticResult::Scalar,
-        Function::Phi => StaticResult::Scalar,
-        Function::PoissonDist => StaticResult::Scalar,
-        Function::Standardize => StaticResult::Scalar,
-        Function::StDevP => StaticResult::Scalar,
-        Function::StDevS => StaticResult::Scalar,
-        Function::Stdeva => StaticResult::Scalar,
-        Function::Stdevpa => StaticResult::Scalar,
-        Function::TDist => StaticResult::Scalar,
-        Function::TDist2T => StaticResult::Scalar,
-        Function::TDistRT => StaticResult::Scalar,
-        Function::TInv => StaticResult::Scalar,
-        Function::TInv2T => StaticResult::Scalar,
-        Function::TTest => StaticResult::Scalar,
-        Function::VarP => StaticResult::Scalar,
-        Function::VarS => StaticResult::Scalar,
-        Function::VarpA => StaticResult::Scalar,
-        Function::VarA => StaticResult::Scalar,
-        Function::WeibullDist => StaticResult::Scalar,
-        Function::ZTest => StaticResult::Scalar,
     }
 }

base/src/functions/mathematical.rs

@@ -8,74 +8,8 @@ use crate::single_number_fn;
 use crate::{
     calc_result::CalcResult, expressions::parser::Node, expressions::token::Error, model::Model,
 };
-use statrs::function::gamma::ln_gamma;
-use std::f64::consts::LN_2;
 use std::f64::consts::PI;
 
-const FACT_TABLE: [f64; 26] = [
-    1.0,                          // 0!
-    1.0,                          // 1!
-    2.0,                          // 2!
-    6.0,                          // 3!
-    24.0,                         // 4!
-    120.0,                        // 5!
-    720.0,                        // 6!
-    5040.0,                       // 7!
-    40320.0,                      // 8!
-    362880.0,                     // 9!
-    3628800.0,                    // 10!
-    39916800.0,                   // 11!
-    479001600.0,                  // 12!
-    6227020800.0,                 // 13!
-    87178291200.0,                // 14!
-    1307674368000.0,              // 15!
-    20922789888000.0,             // 16!
-    355687428096000.0,            // 17!
-    6402373705728000.0,           // 18!
-    121645100408832000.0,         // 19!
-    2432902008176640000.0,        // 20!
-    51090942171709440000.0,       // 21!
-    1124000727777607680000.0,     // 22!
-    25852016738884976640000.0,    // 23!
-    620448401733239439360000.0,   // 24!
-    15511210043330985984000000.0, // 25!
-];
-
-const FACTDOUBLE_TABLE: [f64; 32] = [
-    1.0,
-    1.0,
-    2.0,
-    3.0,
-    8.0,
-    15.0,
-    48.0,
-    105.0,
-    384.0,
-    945.0,
-    3840.0,
-    10395.0,
-    46080.0,
-    135135.0,
-    645120.0,
-    2027025.0,
-    10321920.0,
-    34459425.0,
-    185794560.0,
-    654729075.0,
-    3715891200.0,
-    13749310575.0,
-    81749606400.0,
-    316234143225.0,
-    1961990553600.0,
-    7905853580625.0,
-    51011754393600.0,
-    213458046676875.0,
-    1428329123020800.0,
-    6190283353629370.0,
-    42849873690624000.0,
-    191898783962511000.0,
-];
-
 #[cfg(not(target_arch = "wasm32"))]
 pub fn random() -> f64 {
     rand::random()
@@ -1088,7 +1022,7 @@ impl Model {
         cell: CellReferenceIndex,
     ) -> CalcResult {
         let arg_count = args.len();
-        if !(1..=3).contains(&arg_count) {
+        if arg_count > 3 {
             return CalcResult::new_args_number_error(cell);
         }
         let value = match self.get_number(&args[0], cell) {
@@ -1129,7 +1063,7 @@ impl Model {
         cell: CellReferenceIndex,
     ) -> CalcResult {
         let arg_count = args.len();
-        if !(1..=2).contains(&arg_count) {
+        if arg_count > 2 {
             return CalcResult::new_args_number_error(cell);
         }
         let value = match self.get_number(&args[0], cell) {
@@ -1159,7 +1093,7 @@ impl Model {
 
     pub(crate) fn fn_floor_math(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
         let arg_count = args.len();
-        if !(1..=3).contains(&arg_count) {
+        if arg_count > 3 {
             return CalcResult::new_args_number_error(cell);
         }
         let value = match self.get_number(&args[0], cell) {
@@ -1201,7 +1135,7 @@ impl Model {
         cell: CellReferenceIndex,
     ) -> CalcResult {
         let arg_count = args.len();
-        if !(1..=2).contains(&arg_count) {
+        if arg_count > 2 {
             return CalcResult::new_args_number_error(cell);
         }
         let value = match self.get_number(&args[0], cell) {
@@ -1275,7 +1209,7 @@ impl Model {
     }
 
     pub(crate) fn fn_trunc(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        if !(1..=2).contains(&args.len()) {
+        if args.len() > 2 {
             return CalcResult::new_args_number_error(cell);
         }
         let value = match self.get_number(&args[0], cell) {
@@ -1385,78 +1319,35 @@ impl Model {
     single_number_fn!(fn_sec, |f| Ok(1.0 / f64::cos(f)));
     single_number_fn!(fn_sech, |f| Ok(1.0 / f64::cosh(f)));
     single_number_fn!(fn_exp, |f: f64| Ok(f64::exp(f)));
-
     single_number_fn!(fn_fact, |x: f64| {
         let x = x.floor();
-
         if x < 0.0 {
             return Err(Error::NUM);
         }
-
-        if x == 0.0 {
-            return Ok(1.0);
+        let mut acc = 1.0;
+        let mut k = 2.0;
+        while k <= x {
+            acc *= k;
+            k += 1.0;
         }
-        if x < FACT_TABLE.len() as f64 {
-            return Ok(FACT_TABLE[x as usize]);
-        }
-
-        // Use ln Γ(x+1) to avoid overflow while deciding.
-        let ln_val = ln_gamma(x + 1.0);
-
-        // If gamma overflows or is invalid, map to NUM
-        if !ln_val.is_finite() || ln_val > f64::MAX.ln() {
-            return Err(Error::NUM);
-        }
-
-        Ok(ln_val.exp())
+        Ok(acc)
     });
-
     single_number_fn!(fn_factdouble, |x: f64| {
         let x = x.floor();
-        if x <= -1.0 {
+        if x < -1.0 {
             return Err(Error::NUM);
         }
-
-        if x <= 1.0 {
+        if x < 0.0 {
             return Ok(1.0);
         }
-
-        // From here x > 1 and integer
-        let n = x as i64;
-
-        if n < FACTDOUBLE_TABLE.len() as i64 {
-            return Ok(FACTDOUBLE_TABLE[n as usize]);
+        let mut acc = 1.0;
+        let mut k = if x % 2.0 == 0.0 { 2.0 } else { 1.0 };
+        while k <= x {
+            acc *= k;
+            k += 2.0;
         }
-
-        // n!! grows very fast, so we compute it using gamma in log-space:
-        //
-        // If n is even, n = 2k:
-        //   n!! = 2^k * k!
-        // If n is odd, n = 2k + 1:
-        //   n!! = (2k+1)! / (2^k * k!)
-        //
-        // and we use ln_gamma for factorials.
-
-        let ln_val = if n % 2 == 0 {
-            // even n = 2k
-            let k = (n / 2) as f64;
-            // ln(n!!) = k * ln(2) + ln(k!)
-            k * LN_2 + ln_gamma(k + 1.0)
-        } else {
-            // odd n = 2k + 1
-            let k = ((n - 1) / 2) as f64;
-            let nn = n as f64;
-            // ln(n!!) = ln((2k+1)!) - (k * ln(2) + ln(k!))
-            ln_gamma(nn + 1.0) - (k * LN_2 + ln_gamma(k + 1.0))
-        };
-
-        if !ln_val.is_finite() || ln_val > f64::MAX.ln() {
-            return Err(Error::NUM);
-        }
-
-        Ok(ln_val.exp())
+        Ok(acc)
     });
-
     single_number_fn!(fn_sign, |f| {
         if f == 0.0 {
             Ok(0.0)

base/src/functions/mod.rs

@@ -190,98 +190,6 @@ pub enum Function {
     Minifs,
     Geomean,
 
-    Avedev,
-    BetaDist,
-    BetaInv,
-    BinomDist,
-    BinomDistRange,
-    BinomInv,
-    ChisqDist,
-    ChisqDistRT,
-    ChisqInv,
-    ChisqInvRT,
-    ChisqTest,
-    ConfidenceNorm,
-    ConfidenceT,
-    // Correl,
-    CovarianceP,
-    CovarianceS,
-    Devsq,
-    ExponDist,
-    FDist,
-    FDistRT,
-    FInv,
-    FInvRT,
-    // FTest,
-    Fisher,
-    FisherInv,
-    // Forecast,
-    Gamma,
-    GammaDist,
-    GammaInv,
-    GammaLn,
-    GammaLnPrecise,
-    // Gauss,
-    // Growth,
-    // Harmean,
-    HypGeomDist,
-    // Intercept,
-    // Kurt,
-    // Large,
-    // Linest,
-    // Logest,
-    LogNormDist,
-    LogNormInv,
-    // MaxA,
-    // Median,
-    // MinA,
-    // ModeMult,
-    // ModeSingl,
-    NegbinomDist,
-    NormDist,
-    NormInv,
-    NormSdist,
-    NormSInv,
-    Pearson,
-    // PercentileExc,
-    // PercentileInc,
-    // PercentrankExc,
-    // PercentrankInc,
-    // Permut,
-    // Permutationa,
-    Phi,
-    PoissonDist,
-    // Prob,
-    // QuartileExc,
-    // QuartileInc,
-    // RankAvg,
-    // RankEq,
-    // Rsq
-    // Skew,
-    // SkewP,
-    // Slope,
-    // Small,
-    Standardize,
-    StDevP,
-    StDevS,
-    Stdeva,
-    Stdevpa,
-    // Steyx,
-    TDist,
-    TDist2T,
-    TDistRT,
-    TInv,
-    TInv2T,
-    TTest,
-    // Trend,
-    // Trimmean,
-    VarP,
-    VarS,
-    VarpA,
-    VarA,
-    WeibullDist,
-    ZTest,
-
     // Date and time
     Date,
     Datedif,
@@ -420,7 +328,7 @@ pub enum Function {
 }
 
 impl Function {
-    pub fn into_iter() -> IntoIter<Function, 324> {
+    pub fn into_iter() -> IntoIter<Function, 268> {
         [
             Function::And,
             Function::False,
@@ -545,7 +453,6 @@ impl Function {
             Function::Type,
             Function::Sheet,
             Function::Average,
-            Function::Avedev,
             Function::Averagea,
             Function::Averageif,
             Function::Averageifs,
@@ -691,61 +598,6 @@ impl Function {
             Function::Dvar,
             Function::Dvarp,
             Function::Dstdevp,
-            Function::BetaDist,
-            Function::BetaInv,
-            Function::BinomDist,
-            Function::BinomDistRange,
-            Function::BinomInv,
-            Function::ChisqDist,
-            Function::ChisqDistRT,
-            Function::ChisqInv,
-            Function::ChisqInvRT,
-            Function::ChisqTest,
-            Function::ConfidenceNorm,
-            Function::ConfidenceT,
-            Function::CovarianceP,
-            Function::CovarianceS,
-            Function::Devsq,
-            Function::ExponDist,
-            Function::FDist,
-            Function::FDistRT,
-            Function::FInv,
-            Function::FInvRT,
-            Function::Fisher,
-            Function::FisherInv,
-            Function::Gamma,
-            Function::GammaDist,
-            Function::GammaInv,
-            Function::GammaLn,
-            Function::GammaLnPrecise,
-            Function::HypGeomDist,
-            Function::LogNormDist,
-            Function::LogNormInv,
-            Function::NegbinomDist,
-            Function::NormDist,
-            Function::NormInv,
-            Function::NormSdist,
-            Function::NormSInv,
-            Function::Pearson,
-            Function::Phi,
-            Function::PoissonDist,
-            Function::Standardize,
-            Function::StDevP,
-            Function::StDevS,
-            Function::Stdeva,
-            Function::Stdevpa,
-            Function::TDist,
-            Function::TDist2T,
-            Function::TDistRT,
-            Function::TInv,
-            Function::TInv2T,
-            Function::TTest,
-            Function::VarP,
-            Function::VarS,
-            Function::VarpA,
-            Function::VarA,
-            Function::WeibullDist,
-            Function::ZTest,
         ]
         .into_iter()
     }
@@ -807,66 +659,6 @@ impl Function {
             Function::Sec => "_xlfn.SEC".to_string(),
             Function::Sech => "_xlfn.SECH".to_string(),
             Function::Acot => "_xlfn.ACOT".to_string(),
-            Function::GammaLnPrecise => "_xlfn.GAMMALN.PRECISE".to_string(),
-            Function::Gamma => "_xlfn.GAMMA".to_string(),
-            Function::GammaInv => "_xlfn.GAMMA.INV".to_string(),
-            Function::GammaLn => "_xlfn.GAMMALN".to_string(),
-            Function::BetaDist => "_xlfn.BETA.DIST".to_string(),
-            Function::BetaInv => "_xlfn.BETA.INV".to_string(),
-
-            Function::BinomDist => "_xlfn.BINOM.DIST".to_string(),
-            Function::BinomDistRange => "_xlfn.BINOM.DIST.RANGE".to_string(),
-            Function::BinomInv => "_xlfn.BINOM.INV".to_string(),
-            Function::NegbinomDist => "_xlfn.NEGBINOM.DIST".to_string(),
-
-            Function::ChisqDist => "_xlfn.CHISQ.DIST".to_string(),
-            Function::ChisqDistRT => "_xlfn.CHISQ.DIST.RT".to_string(),
-            Function::ChisqInv => "_xlfn.CHISQ.INV".to_string(),
-            Function::ChisqInvRT => "_xlfn.CHISQ.INV.RT".to_string(),
-            Function::ChisqTest => "_xlfn.CHISQ.TEST".to_string(),
-
-            Function::ConfidenceNorm => "_xlfn.CONFIDENCE.NORM".to_string(),
-            Function::ConfidenceT => "_xlfn.CONFIDENCE.T".to_string(),
-
-            Function::CovarianceP => "_xlfn.COVARIANCE.P".to_string(),
-            Function::CovarianceS => "_xlfn.COVARIANCE.S".to_string(),
-
-            Function::ExponDist => "_xlfn.EXPON.DIST".to_string(),
-
-            Function::FDist => "_xlfn.F.DIST".to_string(),
-            Function::FDistRT => "_xlfn.F.DIST.RT".to_string(),
-            Function::FInv => "_xlfn.F.INV".to_string(),
-            Function::FInvRT => "_xlfn.F.INV.RT".to_string(),
-
-            Function::HypGeomDist => "_xlfn.HYPGEOM.DIST".to_string(),
-
-            Function::LogNormDist => "_xlfn.LOGNORM.DIST".to_string(),
-            Function::LogNormInv => "_xlfn.LOGNORM.INV".to_string(),
-
-            Function::NormDist => "_xlfn.NORM.DIST".to_string(),
-            Function::NormInv => "_xlfn.NORM.INV".to_string(),
-            Function::NormSdist => "_xlfn.NORM.S.DIST".to_string(),
-            Function::NormSInv => "_xlfn.NORM.S.INV".to_string(),
-
-            Function::Phi => "_xlfn.PHI".to_string(),
-
-            Function::PoissonDist => "_xlfn.POISSON.DIST".to_string(),
-
-            Function::StDevP => "_xlfn.STDEV.P".to_string(),
-            Function::StDevS => "_xlfn.STDEV.S".to_string(),
-
-            Function::TDist => "_xlfn.T.DIST".to_string(),
-            Function::TDist2T => "_xlfn.T.DIST.2T".to_string(),
-            Function::TDistRT => "_xlfn.T.DIST.RT".to_string(),
-            Function::TInv => "_xlfn.T.INV".to_string(),
-            Function::TInv2T => "_xlfn.T.INV.2T".to_string(),
-            Function::TTest => "_xlfn.T.TEST".to_string(),
-
-            Function::VarP => "_xlfn.VAR.P".to_string(),
-            Function::VarS => "_xlfn.VAR.S".to_string(),
-
-            Function::WeibullDist => "_xlfn.WEIBULL.DIST".to_string(),
-            Function::ZTest => "_xlfn.Z.TEST".to_string(),
 
             _ => self.to_string(),
         }
@@ -1019,7 +811,6 @@ impl Function {
 
             "AVERAGE" => Some(Function::Average),
             "AVERAGEA" => Some(Function::Averagea),
-            "AVEDEV" => Some(Function::Avedev),
             "AVERAGEIF" => Some(Function::Averageif),
             "AVERAGEIFS" => Some(Function::Averageifs),
             "COUNT" => Some(Function::Count),
@@ -1166,62 +957,6 @@ impl Function {
             "DVARP" => Some(Function::Dvarp),
             "DSTDEVP" => Some(Function::Dstdevp),
 
-            "BETA.DIST" | "_XLFN.BETA.DIST" => Some(Function::BetaDist),
-            "BETA.INV" | "_XLFN.BETA.INV" => Some(Function::BetaInv),
-            "BINOM.DIST" | "_XLFN.BINOM.DIST" => Some(Function::BinomDist),
-            "BINOM.DIST.RANGE" | "_XLFN.BINOM.DIST.RANGE" => Some(Function::BinomDistRange),
-            "BINOM.INV" | "_XLFN.BINOM.INV" => Some(Function::BinomInv),
-            "CHISQ.DIST" | "_XLFN.CHISQ.DIST" => Some(Function::ChisqDist),
-            "CHISQ.DIST.RT" | "_XLFN.CHISQ.DIST.RT" => Some(Function::ChisqDistRT),
-            "CHISQ.INV" | "_XLFN.CHISQ.INV" => Some(Function::ChisqInv),
-            "CHISQ.INV.RT" | "_XLFN.CHISQ.INV.RT" => Some(Function::ChisqInvRT),
-            "CHISQ.TEST" | "_XLFN.CHISQ.TEST" => Some(Function::ChisqTest),
-            "CONFIDENCE.NORM" | "_XLFN.CONFIDENCE.NORM" => Some(Function::ConfidenceNorm),
-            "CONFIDENCE.T" | "_XLFN.CONFIDENCE.T" => Some(Function::ConfidenceT),
-            "COVARIANCE.P" | "_XLFN.COVARIANCE.P" => Some(Function::CovarianceP),
-            "COVARIANCE.S" | "_XLFN.COVARIANCE.S" => Some(Function::CovarianceS),
-            "DEVSQ" => Some(Function::Devsq),
-            "EXPON.DIST" | "_XLFN.EXPON.DIST" => Some(Function::ExponDist),
-            "F.DIST" | "_XLFN.F.DIST" => Some(Function::FDist),
-            "F.DIST.RT" | "_XLFN.F.DIST.RT" => Some(Function::FDistRT),
-            "F.INV" | "_XLFN.F.INV" => Some(Function::FInv),
-            "F.INV.RT" | "_XLFN.F.INV.RT" => Some(Function::FInvRT),
-            "FISHER" => Some(Function::Fisher),
-            "FISHERINV" => Some(Function::FisherInv),
-            "GAMMA" | "_XLFN.GAMMA" => Some(Function::Gamma),
-            "GAMMA.DIST" | "_XLFN.GAMMA.DIST" => Some(Function::GammaDist),
-            "GAMMA.INV" | "_XLFN.GAMMA.INV" => Some(Function::GammaInv),
-            "GAMMALN" | "_XLFN.GAMMALN" => Some(Function::GammaLn),
-            "GAMMALN.PRECISE" | "_XLFN.GAMMALN.PRECISE" => Some(Function::GammaLnPrecise),
-            "HYPGEOM.DIST" | "_XLFN.HYPGEOM.DIST" => Some(Function::HypGeomDist),
-            "LOGNORM.DIST" | "_XLFN.LOGNORM.DIST" => Some(Function::LogNormDist),
-            "LOGNORM.INV" | "_XLFN.LOGNORM.INV" => Some(Function::LogNormInv),
-            "NEGBINOM.DIST" | "_XLFN.NEGBINOM.DIST" => Some(Function::NegbinomDist),
-            "NORM.DIST" | "_XLFN.NORM.DIST" => Some(Function::NormDist),
-            "NORM.INV" | "_XLFN.NORM.INV" => Some(Function::NormInv),
-            "NORM.S.DIST" | "_XLFN.NORM.S.DIST" => Some(Function::NormSdist),
-            "NORM.S.INV" | "_XLFN.NORM.S.INV" => Some(Function::NormSInv),
-            "PEARSON" => Some(Function::Pearson),
-            "PHI" | "_XLFN.PHI" => Some(Function::Phi),
-            "POISSON.DIST" | "_XLFN.POISSON.DIST" => Some(Function::PoissonDist),
-            "STANDARDIZE" => Some(Function::Standardize),
-            "STDEV.P" | "_XLFN.STDEV.P" => Some(Function::StDevP),
-            "STDEV.S" | "_XLFN.STDEV.S" => Some(Function::StDevS),
-            "STDEVA" => Some(Function::Stdeva),
-            "STDEVPA" => Some(Function::Stdevpa),
-            "T.DIST" | "_XLFN.T.DIST" => Some(Function::TDist),
-            "T.DIST.2T" | "_XLFN.T.DIST.2T" => Some(Function::TDist2T),
-            "T.DIST.RT" | "_XLFN.T.DIST.RT" => Some(Function::TDistRT),
-            "T.INV" | "_XLFN.T.INV" => Some(Function::TInv),
-            "T.INV.2T" | "_XLFN.T.INV.2T" => Some(Function::TInv2T),
-            "T.TEST" | "_XLFN.T.TEST" => Some(Function::TTest),
-            "VAR.P" | "_XLFN.VAR.P" => Some(Function::VarP),
-            "VAR.S" | "_XLFN.VAR.S" => Some(Function::VarS),
-            "VARPA" => Some(Function::VarpA),
-            "VARA" => Some(Function::VarA),
-            "WEIBULL.DIST" | "_XLFN.WEIBULL.DIST" => Some(Function::WeibullDist),
-            "Z.TEST" | "_XLFN.Z.TEST" => Some(Function::ZTest),
-
             _ => None,
         }
     }
@@ -1330,7 +1065,6 @@ impl fmt::Display for Function {
             Function::Sheet => write!(f, "SHEET"),
             Function::Average => write!(f, "AVERAGE"),
             Function::Averagea => write!(f, "AVERAGEA"),
-            Function::Avedev => write!(f, "AVEDEV"),
             Function::Averageif => write!(f, "AVERAGEIF"),
             Function::Averageifs => write!(f, "AVERAGEIFS"),
             Function::Count => write!(f, "COUNT"),
@@ -1500,62 +1234,6 @@ impl fmt::Display for Function {
             Function::Dvar => write!(f, "DVAR"),
             Function::Dvarp => write!(f, "DVARP"),
             Function::Dstdevp => write!(f, "DSTDEVP"),
-
-            Function::BetaDist => write!(f, "BETA.DIST"),
-            Function::BetaInv => write!(f, "BETA.INV"),
-            Function::BinomDist => write!(f, "BINOM.DIST"),
-            Function::BinomDistRange => write!(f, "BINOM.DIST.RANGE"),
-            Function::BinomInv => write!(f, "BINOM.INV"),
-            Function::ChisqDist => write!(f, "CHISQ.DIST"),
-            Function::ChisqDistRT => write!(f, "CHISQ.DIST.RT"),
-            Function::ChisqInv => write!(f, "CHISQ.INV"),
-            Function::ChisqInvRT => write!(f, "CHISQ.INV.RT"),
-            Function::ChisqTest => write!(f, "CHISQ.TEST"),
-            Function::ConfidenceNorm => write!(f, "CONFIDENCE.NORM"),
-            Function::ConfidenceT => write!(f, "CONFIDENCE.T"),
-            Function::CovarianceP => write!(f, "COVARIANCE.P"),
-            Function::CovarianceS => write!(f, "COVARIANCE.S"),
-            Function::Devsq => write!(f, "DEVSQ"),
-            Function::ExponDist => write!(f, "EXPON.DIST"),
-            Function::FDist => write!(f, "F.DIST"),
-            Function::FDistRT => write!(f, "F.DIST.RT"),
-            Function::FInv => write!(f, "F.INV"),
-            Function::FInvRT => write!(f, "F.INV.RT"),
-            Function::Fisher => write!(f, "FISHER"),
-            Function::FisherInv => write!(f, "FISHERINV"),
-            Function::Gamma => write!(f, "GAMMA"),
-            Function::GammaDist => write!(f, "GAMMA.DIST"),
-            Function::GammaInv => write!(f, "GAMMA.INV"),
-            Function::GammaLn => write!(f, "GAMMALN"),
-            Function::GammaLnPrecise => write!(f, "GAMMALN.PRECISE"),
-            Function::HypGeomDist => write!(f, "HYPGEOM.DIST"),
-            Function::LogNormDist => write!(f, "LOGNORM.DIST"),
-            Function::LogNormInv => write!(f, "LOGNORM.INV"),
-            Function::NegbinomDist => write!(f, "NEGBINOM.DIST"),
-            Function::NormDist => write!(f, "NORM.DIST"),
-            Function::NormInv => write!(f, "NORM.INV"),
-            Function::NormSdist => write!(f, "NORM.S.DIST"),
-            Function::NormSInv => write!(f, "NORM.S.INV"),
-            Function::Pearson => write!(f, "PEARSON"),
-            Function::Phi => write!(f, "PHI"),
-            Function::PoissonDist => write!(f, "POISSON.DIST"),
-            Function::Standardize => write!(f, "STANDARDIZE"),
-            Function::StDevP => write!(f, "STDEV.P"),
-            Function::StDevS => write!(f, "STDEV.S"),
-            Function::Stdeva => write!(f, "STDEVA"),
-            Function::Stdevpa => write!(f, "STDEVPA"),
-            Function::TDist => write!(f, "T.DIST"),
-            Function::TDist2T => write!(f, "T.DIST.2T"),
-            Function::TDistRT => write!(f, "T.DIST.RT"),
-            Function::TInv => write!(f, "T.INV"),
-            Function::TInv2T => write!(f, "T.INV.2T"),
-            Function::TTest => write!(f, "T.TEST"),
-            Function::VarP => write!(f, "VAR.P"),
-            Function::VarS => write!(f, "VAR.S"),
-            Function::VarpA => write!(f, "VARPA"),
-            Function::VarA => write!(f, "VARA"),
-            Function::WeibullDist => write!(f, "WEIBULL.DIST"),
-            Function::ZTest => write!(f, "Z.TEST"),
         }
     }
 }
@@ -1676,7 +1354,6 @@ impl Model {
             Function::Sheet => self.fn_sheet(args, cell),
             Function::Average => self.fn_average(args, cell),
             Function::Averagea => self.fn_averagea(args, cell),
-            Function::Avedev => self.fn_avedev(args, cell),
             Function::Averageif => self.fn_averageif(args, cell),
             Function::Averageifs => self.fn_averageifs(args, cell),
             Function::Count => self.fn_count(args, cell),
@@ -1853,61 +1530,6 @@ impl Model {
             Function::Dvar => self.fn_dvar(args, cell),
             Function::Dvarp => self.fn_dvarp(args, cell),
             Function::Dstdevp => self.fn_dstdevp(args, cell),
-            Function::BetaDist => self.fn_beta_dist(args, cell),
-            Function::BetaInv => self.fn_beta_inv(args, cell),
-            Function::BinomDist => self.fn_binom_dist(args, cell),
-            Function::BinomDistRange => self.fn_binom_dist_range(args, cell),
-            Function::BinomInv => self.fn_binom_inv(args, cell),
-            Function::ChisqDist => self.fn_chisq_dist(args, cell),
-            Function::ChisqDistRT => self.fn_chisq_dist_rt(args, cell),
-            Function::ChisqInv => self.fn_chisq_inv(args, cell),
-            Function::ChisqInvRT => self.fn_chisq_inv_rt(args, cell),
-            Function::ChisqTest => self.fn_chisq_test(args, cell),
-            Function::ConfidenceNorm => self.fn_confidence_norm(args, cell),
-            Function::ConfidenceT => self.fn_confidence_t(args, cell),
-            Function::CovarianceP => self.fn_covariance_p(args, cell),
-            Function::CovarianceS => self.fn_covariance_s(args, cell),
-            Function::Devsq => self.fn_devsq(args, cell),
-            Function::ExponDist => self.fn_expon_dist(args, cell),
-            Function::FDist => self.fn_f_dist(args, cell),
-            Function::FDistRT => self.fn_f_dist_rt(args, cell),
-            Function::FInv => self.fn_f_inv(args, cell),
-            Function::FInvRT => self.fn_f_inv_rt(args, cell),
-            Function::Fisher => self.fn_fisher(args, cell),
-            Function::FisherInv => self.fn_fisher_inv(args, cell),
-            Function::Gamma => self.fn_gamma(args, cell),
-            Function::GammaDist => self.fn_gamma_dist(args, cell),
-            Function::GammaInv => self.fn_gamma_inv(args, cell),
-            Function::GammaLn => self.fn_gamma_ln(args, cell),
-            Function::GammaLnPrecise => self.fn_gamma_ln_precise(args, cell),
-            Function::HypGeomDist => self.fn_hyp_geom_dist(args, cell),
-            Function::LogNormDist => self.fn_log_norm_dist(args, cell),
-            Function::LogNormInv => self.fn_log_norm_inv(args, cell),
-            Function::NegbinomDist => self.fn_negbinom_dist(args, cell),
-            Function::NormDist => self.fn_norm_dist(args, cell),
-            Function::NormInv => self.fn_norm_inv(args, cell),
-            Function::NormSdist => self.fn_norm_s_dist(args, cell),
-            Function::NormSInv => self.fn_norm_s_inv(args, cell),
-            Function::Pearson => self.fn_pearson(args, cell),
-            Function::Phi => self.fn_phi(args, cell),
-            Function::PoissonDist => self.fn_poisson_dist(args, cell),
-            Function::Standardize => self.fn_standardize(args, cell),
-            Function::StDevP => self.fn_stdev_p(args, cell),
-            Function::StDevS => self.fn_stdev_s(args, cell),
-            Function::Stdeva => self.fn_stdeva(args, cell),
-            Function::Stdevpa => self.fn_stdevpa(args, cell),
-            Function::TDist => self.fn_t_dist(args, cell),
-            Function::TDist2T => self.fn_t_dist_2t(args, cell),
-            Function::TDistRT => self.fn_t_dist_rt(args, cell),
-            Function::TInv => self.fn_t_inv(args, cell),
-            Function::TInv2T => self.fn_t_inv_2t(args, cell),
-            Function::TTest => self.fn_t_test(args, cell),
-            Function::VarP => self.fn_var_p(args, cell),
-            Function::VarS => self.fn_var_s(args, cell),
-            Function::VarpA => self.fn_varpa(args, cell),
-            Function::VarA => self.fn_vara(args, cell),
-            Function::WeibullDist => self.fn_weibull_dist(args, cell),
-            Function::ZTest => self.fn_z_test(args, cell),
         }
     }
 }

base/src/functions/statistical.rs

@@ -1,10 +1,14 @@
 use crate::constants::{LAST_COLUMN, LAST_ROW};
-use crate::expressions::parser::ArrayNode;
 use crate::expressions::types::CellReferenceIndex;
 use crate::{
-    calc_result::CalcResult, expressions::parser::Node, expressions::token::Error, model::Model,
+    calc_result::{CalcResult, Range},
+    expressions::parser::Node,
+    expressions::token::Error,
+    model::Model,
 };
 
+use super::util::build_criteria;
+
 impl Model {
     pub(crate) fn fn_average(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
         if args.is_empty() {
@@ -86,6 +90,7 @@ impl Model {
         }
         CalcResult::Number(sum / count)
     }
+
     pub(crate) fn fn_averagea(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
         if args.is_empty() {
             return CalcResult::new_args_number_error(cell);
@@ -319,26 +324,350 @@ impl Model {
         CalcResult::Number(result)
     }
 
-    pub(crate) fn fn_avedev(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        if args.is_empty() {
+    pub(crate) fn fn_countif(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
+        if args.len() == 2 {
+            let arguments = vec![args[0].clone(), args[1].clone()];
+            self.fn_countifs(&arguments, cell)
+        } else {
+            CalcResult::new_args_number_error(cell)
+        }
+    }
+
+    /// AVERAGEIF(criteria_range, criteria, [average_range])
+    /// if average_rage is missing then criteria_range will be used
+    pub(crate) fn fn_averageif(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
+        if args.len() == 2 {
+            let arguments = vec![args[0].clone(), args[0].clone(), args[1].clone()];
+            self.fn_averageifs(&arguments, cell)
+        } else if args.len() == 3 {
+            let arguments = vec![args[2].clone(), args[0].clone(), args[1].clone()];
+            self.fn_averageifs(&arguments, cell)
+        } else {
+            CalcResult::new_args_number_error(cell)
+        }
+    }
+
+    // FIXME: This function shares a lot of code with apply_ifs. Can we merge them?
+    pub(crate) fn fn_countifs(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
+        let args_count = args.len();
+        if args_count < 2 || !args_count.is_multiple_of(2) {
             return CalcResult::new_args_number_error(cell);
         }
 
-        let mut values: Vec<f64> = Vec::new();
-        let mut sum = 0.0;
-        let mut count: u64 = 0;
-
-        #[inline]
-        fn accumulate(values: &mut Vec<f64>, sum: &mut f64, count: &mut u64, value: f64) {
-            values.push(value);
-            *sum += value;
-            *count += 1;
+        let case_count = args_count / 2;
+        // NB: this is a beautiful example of the borrow checker
+        // The order of these two definitions cannot be swapped.
+        let mut criteria = Vec::new();
+        let mut fn_criteria = Vec::new();
+        let ranges = &mut Vec::new();
+        for case_index in 0..case_count {
+            let criterion = self.evaluate_node_in_context(&args[case_index * 2 + 1], cell);
+            criteria.push(criterion);
+            // NB: We cannot do:
+            // fn_criteria.push(build_criteria(&criterion));
+            // because criterion doesn't live long enough
+            let result = self.evaluate_node_in_context(&args[case_index * 2], cell);
+            if result.is_error() {
+                return result;
+            }
+            if let CalcResult::Range { left, right } = result {
+                if left.sheet != right.sheet {
+                    return CalcResult::new_error(
+                        Error::VALUE,
+                        cell,
+                        "Ranges are in different sheets".to_string(),
+                    );
+                }
+                // TODO test ranges are of the same size as sum_range
+                ranges.push(Range { left, right });
+            } else {
+                return CalcResult::new_error(Error::VALUE, cell, "Expected a range".to_string());
+            }
+        }
+        for criterion in criteria.iter() {
+            fn_criteria.push(build_criteria(criterion));
         }
 
+        let mut total = 0.0;
+        let first_range = &ranges[0];
+        let left_row = first_range.left.row;
+        let left_column = first_range.left.column;
+        let right_row = first_range.right.row;
+        let right_column = first_range.right.column;
+
+        let dimension = match self.workbook.worksheet(first_range.left.sheet) {
+            Ok(s) => s.dimension(),
+            Err(_) => {
+                return CalcResult::new_error(
+                    Error::ERROR,
+                    cell,
+                    format!("Invalid worksheet index: '{}'", first_range.left.sheet),
+                )
+            }
+        };
+        let max_row = dimension.max_row;
+        let max_column = dimension.max_column;
+
+        let open_row = left_row == 1 && right_row == LAST_ROW;
+        let open_column = left_column == 1 && right_column == LAST_COLUMN;
+
+        for row in left_row..right_row + 1 {
+            if open_row && row > max_row {
+                // If the row is larger than the max row in the sheet then all cells are empty.
+                // We compute it only once
+                let mut is_true = true;
+                for fn_criterion in fn_criteria.iter() {
+                    if !fn_criterion(&CalcResult::EmptyCell) {
+                        is_true = false;
+                        break;
+                    }
+                }
+                if is_true {
+                    total += ((LAST_ROW - max_row) * (right_column - left_column + 1)) as f64;
+                }
+                break;
+            }
+            for column in left_column..right_column + 1 {
+                if open_column && column > max_column {
+                    // If the column is larger than the max column in the sheet then all cells are empty.
+                    // We compute it only once
+                    let mut is_true = true;
+                    for fn_criterion in fn_criteria.iter() {
+                        if !fn_criterion(&CalcResult::EmptyCell) {
+                            is_true = false;
+                            break;
+                        }
+                    }
+                    if is_true {
+                        total += (LAST_COLUMN - max_column) as f64;
+                    }
+                    break;
+                }
+                let mut is_true = true;
+                for case_index in 0..case_count {
+                    // We check if value in range n meets criterion n
+                    let range = &ranges[case_index];
+                    let fn_criterion = &fn_criteria[case_index];
+                    let value = self.evaluate_cell(CellReferenceIndex {
+                        sheet: range.left.sheet,
+                        row: range.left.row + row - first_range.left.row,
+                        column: range.left.column + column - first_range.left.column,
+                    });
+                    if !fn_criterion(&value) {
+                        is_true = false;
+                        break;
+                    }
+                }
+                if is_true {
+                    total += 1.0;
+                }
+            }
+        }
+        CalcResult::Number(total)
+    }
+
+    pub(crate) fn apply_ifs<F>(
+        &mut self,
+        args: &[Node],
+        cell: CellReferenceIndex,
+        mut apply: F,
+    ) -> Result<(), CalcResult>
+    where
+        F: FnMut(f64),
+    {
+        let args_count = args.len();
+        if args_count < 3 || args_count.is_multiple_of(2) {
+            return Err(CalcResult::new_args_number_error(cell));
+        }
+        let arg_0 = self.evaluate_node_in_context(&args[0], cell);
+        if arg_0.is_error() {
+            return Err(arg_0);
+        }
+        let sum_range = if let CalcResult::Range { left, right } = arg_0 {
+            if left.sheet != right.sheet {
+                return Err(CalcResult::new_error(
+                    Error::VALUE,
+                    cell,
+                    "Ranges are in different sheets".to_string(),
+                ));
+            }
+            Range { left, right }
+        } else {
+            return Err(CalcResult::new_error(
+                Error::VALUE,
+                cell,
+                "Expected a range".to_string(),
+            ));
+        };
+
+        let case_count = (args_count - 1) / 2;
+        // NB: this is a beautiful example of the borrow checker
+        // The order of these two definitions cannot be swapped.
+        let mut criteria = Vec::new();
+        let mut fn_criteria = Vec::new();
+        let ranges = &mut Vec::new();
+        for case_index in 1..=case_count {
+            let criterion = self.evaluate_node_in_context(&args[case_index * 2], cell);
+            // NB: criterion might be an error. That's ok
+            criteria.push(criterion);
+            // NB: We cannot do:
+            // fn_criteria.push(build_criteria(&criterion));
+            // because criterion doesn't live long enough
+            let result = self.evaluate_node_in_context(&args[case_index * 2 - 1], cell);
+            if result.is_error() {
+                return Err(result);
+            }
+            if let CalcResult::Range { left, right } = result {
+                if left.sheet != right.sheet {
+                    return Err(CalcResult::new_error(
+                        Error::VALUE,
+                        cell,
+                        "Ranges are in different sheets".to_string(),
+                    ));
+                }
+                // TODO test ranges are of the same size as sum_range
+                ranges.push(Range { left, right });
+            } else {
+                return Err(CalcResult::new_error(
+                    Error::VALUE,
+                    cell,
+                    "Expected a range".to_string(),
+                ));
+            }
+        }
+        for criterion in criteria.iter() {
+            fn_criteria.push(build_criteria(criterion));
+        }
+
+        let left_row = sum_range.left.row;
+        let left_column = sum_range.left.column;
+        let mut right_row = sum_range.right.row;
+        let mut right_column = sum_range.right.column;
+
+        if left_row == 1 && right_row == LAST_ROW {
+            right_row = match self.workbook.worksheet(sum_range.left.sheet) {
+                Ok(s) => s.dimension().max_row,
+                Err(_) => {
+                    return Err(CalcResult::new_error(
+                        Error::ERROR,
+                        cell,
+                        format!("Invalid worksheet index: '{}'", sum_range.left.sheet),
+                    ));
+                }
+            };
+        }
+        if left_column == 1 && right_column == LAST_COLUMN {
+            right_column = match self.workbook.worksheet(sum_range.left.sheet) {
+                Ok(s) => s.dimension().max_column,
+                Err(_) => {
+                    return Err(CalcResult::new_error(
+                        Error::ERROR,
+                        cell,
+                        format!("Invalid worksheet index: '{}'", sum_range.left.sheet),
+                    ));
+                }
+            };
+        }
+
+        for row in left_row..right_row + 1 {
+            for column in left_column..right_column + 1 {
+                let mut is_true = true;
+                for case_index in 0..case_count {
+                    // We check if value in range n meets criterion n
+                    let range = &ranges[case_index];
+                    let fn_criterion = &fn_criteria[case_index];
+                    let value = self.evaluate_cell(CellReferenceIndex {
+                        sheet: range.left.sheet,
+                        row: range.left.row + row - sum_range.left.row,
+                        column: range.left.column + column - sum_range.left.column,
+                    });
+                    if !fn_criterion(&value) {
+                        is_true = false;
+                        break;
+                    }
+                }
+                if is_true {
+                    let v = self.evaluate_cell(CellReferenceIndex {
+                        sheet: sum_range.left.sheet,
+                        row,
+                        column,
+                    });
+                    match v {
+                        CalcResult::Number(n) => apply(n),
+                        CalcResult::Error { .. } => return Err(v),
+                        _ => {}
+                    }
+                }
+            }
+        }
+        Ok(())
+    }
+
+    pub(crate) fn fn_averageifs(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
+        let mut total = 0.0;
+        let mut count = 0.0;
+
+        let average = |value: f64| {
+            total += value;
+            count += 1.0;
+        };
+        if let Err(e) = self.apply_ifs(args, cell, average) {
+            return e;
+        }
+
+        if count == 0.0 {
+            return CalcResult::Error {
+                error: Error::DIV,
+                origin: cell,
+                message: "division by 0".to_string(),
+            };
+        }
+        CalcResult::Number(total / count)
+    }
+
+    pub(crate) fn fn_minifs(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
+        let mut min = f64::INFINITY;
+        let apply_min = |value: f64| min = value.min(min);
+        if let Err(e) = self.apply_ifs(args, cell, apply_min) {
+            return e;
+        }
+
+        if min.is_infinite() {
+            min = 0.0;
+        }
+        CalcResult::Number(min)
+    }
+
+    pub(crate) fn fn_maxifs(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
+        let mut max = -f64::INFINITY;
+        let apply_max = |value: f64| max = value.max(max);
+        if let Err(e) = self.apply_ifs(args, cell, apply_max) {
+            return e;
+        }
+        if max.is_infinite() {
+            max = 0.0;
+        }
+        CalcResult::Number(max)
+    }
+
+    pub(crate) fn fn_geomean(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
+        if args.is_empty() {
+            return CalcResult::new_args_number_error(cell);
+        }
+        let mut count = 0.0;
+        let mut product = 1.0;
         for arg in args {
             match self.evaluate_node_in_context(arg, cell) {
                 CalcResult::Number(value) => {
-                    accumulate(&mut values, &mut sum, &mut count, value);
+                    count += 1.0;
+                    product *= value;
+                }
+                CalcResult::Boolean(b) => {
+                    if let Node::ReferenceKind { .. } = arg {
+                    } else {
+                        product *= if b { 1.0 } else { 0.0 };
+                        count += 1.0;
+                    }
                 }
                 CalcResult::Range { left, right } => {
                     if left.sheet != right.sheet {
@@ -348,99 +677,57 @@ impl Model {
                             "Ranges are in different sheets".to_string(),
                         );
                     }
-
-                    let row1 = left.row;
-                    let mut row2 = right.row;
-                    let column1 = left.column;
-                    let mut column2 = right.column;
-
-                    if row1 == 1 && row2 == LAST_ROW {
-                        row2 = match self.workbook.worksheet(left.sheet) {
-                            Ok(s) => s.dimension().max_row,
-                            Err(_) => {
-                                return CalcResult::new_error(
-                                    Error::ERROR,
-                                    cell,
-                                    format!("Invalid worksheet index: '{}'", left.sheet),
-                                );
-                            }
-                        };
-                    }
-                    if column1 == 1 && column2 == LAST_COLUMN {
-                        column2 = match self.workbook.worksheet(left.sheet) {
-                            Ok(s) => s.dimension().max_column,
-                            Err(_) => {
-                                return CalcResult::new_error(
-                                    Error::ERROR,
-                                    cell,
-                                    format!("Invalid worksheet index: '{}'", left.sheet),
-                                );
-                            }
-                        };
-                    }
-
-                    for row in row1..=row2 {
-                        for column in column1..=column2 {
+                    for row in left.row..(right.row + 1) {
+                        for column in left.column..(right.column + 1) {
                             match self.evaluate_cell(CellReferenceIndex {
                                 sheet: left.sheet,
                                 row,
                                 column,
                             }) {
                                 CalcResult::Number(value) => {
-                                    accumulate(&mut values, &mut sum, &mut count, value);
+                                    count += 1.0;
+                                    product *= value;
                                 }
                                 error @ CalcResult::Error { .. } => return error,
-                                _ => {
-                                    // ignore non-numeric
-                                }
-                            }
-                        }
-                    }
-                }
-                CalcResult::Array(array) => {
-                    for row in array {
-                        for value in row {
-                            match value {
-                                ArrayNode::Number(value) => {
-                                    accumulate(&mut values, &mut sum, &mut count, value);
-                                }
-                                ArrayNode::Error(error) => {
-                                    return CalcResult::Error {
-                                        error,
-                                        origin: cell,
-                                        message: "Error in array".to_string(),
-                                    }
-                                }
-                                _ => {
-                                    // ignore non-numeric
+                                CalcResult::Range { .. } => {
+                                    return CalcResult::new_error(
+                                        Error::ERROR,
+                                        cell,
+                                        "Unexpected Range".to_string(),
+                                    );
                                 }
+                                _ => {}
                             }
                         }
                     }
                 }
                 error @ CalcResult::Error { .. } => return error,
-                _ => {
-                    // ignore non-numeric
+                CalcResult::String(s) => {
+                    if let Node::ReferenceKind { .. } = arg {
+                        // Do nothing
+                    } else if let Ok(t) = s.parse::<f64>() {
+                        product *= t;
+                        count += 1.0;
+                    } else {
+                        return CalcResult::Error {
+                            error: Error::VALUE,
+                            origin: cell,
+                            message: "Argument cannot be cast into number".to_string(),
+                        };
+                    }
                 }
-            }
+                _ => {
+                    // Ignore everything else
+                }
+            };
         }
-
-        if count == 0 {
-            return CalcResult::new_error(
-                Error::DIV,
-                cell,
-                "AVEDEV with no numeric data".to_string(),
-            );
+        if count == 0.0 {
+            return CalcResult::Error {
+                error: Error::DIV,
+                origin: cell,
+                message: "Division by Zero".to_string(),
+            };
         }
-
-        let n = count as f64;
-        let mean = sum / n;
-
-        let mut sum_abs_dev = 0.0;
-        for v in &values {
-            sum_abs_dev += (v - mean).abs();
-        }
-
-        CalcResult::Number(sum_abs_dev / n)
+        CalcResult::Number(product.powf(1.0 / count))
     }
 }

base/src/functions/statistical/beta.rs

@@ -1,213 +0,0 @@
-use statrs::distribution::{Beta, Continuous, ContinuousCDF};
-
-use crate::expressions::types::CellReferenceIndex;
-use crate::{
-    calc_result::CalcResult, expressions::parser::Node, expressions::token::Error, model::Model,
-};
-
-impl Model {
-    // BETA.DIST(x, alpha, beta, cumulative, [A], [B])
-    pub(crate) fn fn_beta_dist(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        let arg_count = args.len();
-        if !(4..=6).contains(&arg_count) {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        let x = match self.get_number_no_bools(&args[0], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-        let alpha = match self.get_number_no_bools(&args[1], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-        let beta_param = match self.get_number_no_bools(&args[2], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-
-        // cumulative argument: interpret like Excel
-        let cumulative = match self.evaluate_node_in_context(&args[3], cell) {
-            CalcResult::Boolean(b) => b,
-            CalcResult::Number(n) => n != 0.0,
-            CalcResult::String(s) => {
-                let up = s.to_ascii_uppercase();
-                if up == "TRUE" {
-                    true
-                } else if up == "FALSE" {
-                    false
-                } else {
-                    return CalcResult::Error {
-                        error: Error::VALUE,
-                        origin: cell,
-                        message: "cumulative must be TRUE/FALSE or numeric".to_string(),
-                    };
-                }
-            }
-            error @ CalcResult::Error { .. } => return error,
-            _ => {
-                return CalcResult::Error {
-                    error: Error::VALUE,
-                    origin: cell,
-                    message: "Invalid cumulative argument".to_string(),
-                }
-            }
-        };
-
-        // Optional A, B
-        let a = if arg_count >= 5 {
-            match self.get_number_no_bools(&args[4], cell) {
-                Ok(f) => f,
-                Err(e) => return e,
-            }
-        } else {
-            0.0
-        };
-
-        let b = if arg_count >= 6 {
-            match self.get_number_no_bools(&args[5], cell) {
-                Ok(f) => f,
-                Err(e) => return e,
-            }
-        } else {
-            1.0
-        };
-
-        // Excel: alpha <= 0 or beta <= 0 → #NUM!
-        if alpha <= 0.0 || beta_param <= 0.0 {
-            return CalcResult::new_error(
-                Error::NUM,
-                cell,
-                "alpha and beta must be > 0 in BETA.DIST".to_string(),
-            );
-        }
-
-        // Excel: if x < A, x > B, or A = B → #NUM!
-        if b == a || x < a || x > b {
-            return CalcResult::new_error(
-                Error::NUM,
-                cell,
-                "x must be between A and B and A < B in BETA.DIST".to_string(),
-            );
-        }
-
-        // Transform to standard Beta(0,1)
-        let width = b - a;
-        let t = (x - a) / width;
-
-        let dist = match Beta::new(alpha, beta_param) {
-            Ok(d) => d,
-            Err(_) => {
-                return CalcResult::new_error(
-                    Error::NUM,
-                    cell,
-                    "Invalid parameters for Beta distribution".to_string(),
-                )
-            }
-        };
-
-        let result = if cumulative {
-            dist.cdf(t)
-        } else {
-            // general-interval beta pdf: f_X(x) = f_T(t) / (B - A), t=(x-A)/(B-A)
-            dist.pdf(t) / width
-        };
-
-        if result.is_nan() || result.is_infinite() {
-            return CalcResult::new_error(
-                Error::NUM,
-                cell,
-                "Invalid result for BETA.DIST".to_string(),
-            );
-        }
-
-        CalcResult::Number(result)
-    }
-
-    pub(crate) fn fn_beta_inv(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        let arg_count = args.len();
-        if !(3..=5).contains(&arg_count) {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        let p = match self.get_number_no_bools(&args[0], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-        let alpha = match self.get_number_no_bools(&args[1], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-        let beta_param = match self.get_number_no_bools(&args[2], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-
-        let a = if arg_count >= 4 {
-            match self.get_number_no_bools(&args[3], cell) {
-                Ok(f) => f,
-                Err(e) => return e,
-            }
-        } else {
-            0.0
-        };
-
-        let b = if arg_count >= 5 {
-            match self.get_number_no_bools(&args[4], cell) {
-                Ok(f) => f,
-                Err(e) => return e,
-            }
-        } else {
-            1.0
-        };
-
-        if alpha <= 0.0 || beta_param <= 0.0 {
-            return CalcResult::new_error(
-                Error::NUM,
-                cell,
-                "alpha and beta must be > 0 in BETA.INV".to_string(),
-            );
-        }
-
-        // probability <= 0 or probability > 1 → #NUM!
-        if p <= 0.0 || p > 1.0 {
-            return CalcResult::new_error(
-                Error::NUM,
-                cell,
-                "probability must be in (0,1] in BETA.INV".to_string(),
-            );
-        }
-
-        if b <= a {
-            return CalcResult::new_error(
-                Error::NUM,
-                cell,
-                "A must be < B in BETA.INV".to_string(),
-            );
-        }
-
-        let dist = match Beta::new(alpha, beta_param) {
-            Ok(d) => d,
-            Err(_) => {
-                return CalcResult::new_error(
-                    Error::NUM,
-                    cell,
-                    "Invalid parameters for Beta distribution".to_string(),
-                )
-            }
-        };
-
-        let t = dist.inverse_cdf(p);
-        if t.is_nan() || t.is_infinite() {
-            return CalcResult::new_error(
-                Error::NUM,
-                cell,
-                "Invalid result for BETA.INV".to_string(),
-            );
-        }
-
-        // Map back from [0,1] to [A,B]
-        let x = a + t * (b - a);
-        CalcResult::Number(x)
-    }
-}

base/src/functions/statistical/binom.rs

@@ -1,311 +0,0 @@
-use statrs::distribution::{Binomial, Discrete, DiscreteCDF};
-
-use crate::expressions::types::CellReferenceIndex;
-use crate::{
-    calc_result::CalcResult, expressions::parser::Node, expressions::token::Error, model::Model,
-};
-
-impl Model {
-    pub(crate) fn fn_binom_dist(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        if args.len() != 4 {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        // number_s
-        let number_s = match self.get_number_no_bools(&args[0], cell) {
-            Ok(f) => f.trunc(),
-            Err(e) => return e,
-        };
-
-        // trials
-        let trials = match self.get_number_no_bools(&args[1], cell) {
-            Ok(f) => f.trunc(),
-            Err(e) => return e,
-        };
-
-        // probability_s
-        let p = match self.get_number_no_bools(&args[2], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-
-        // cumulative (logical)
-        let cumulative = match self.get_boolean(&args[3], cell) {
-            Ok(b) => b,
-            Err(e) => return e,
-        };
-
-        // Domain checks
-        if trials < 0.0
-            || number_s < 0.0
-            || number_s > trials
-            || p.is_nan()
-            || !(0.0..=1.0).contains(&p)
-        {
-            return CalcResult::new_error(
-                Error::NUM,
-                cell,
-                "Invalid parameters for BINOM.DIST".to_string(),
-            );
-        }
-
-        // Limit to u64
-        if trials > u64::MAX as f64 {
-            return CalcResult::new_error(
-                Error::NUM,
-                cell,
-                "Number of trials too large".to_string(),
-            );
-        }
-
-        let n = trials as u64;
-        let k = number_s as u64;
-
-        let dist = match Binomial::new(p, n) {
-            Ok(d) => d,
-            Err(_) => {
-                return CalcResult::new_error(
-                    Error::NUM,
-                    cell,
-                    "Invalid parameters for binomial distribution".to_string(),
-                )
-            }
-        };
-
-        let prob = if cumulative { dist.cdf(k) } else { dist.pmf(k) };
-
-        if prob.is_nan() || prob.is_infinite() {
-            return CalcResult::new_error(
-                Error::NUM,
-                cell,
-                "Invalid result for BINOM.DIST".to_string(),
-            );
-        }
-
-        CalcResult::Number(prob)
-    }
-
-    pub(crate) fn fn_binom_dist_range(
-        &mut self,
-        args: &[Node],
-        cell: CellReferenceIndex,
-    ) -> CalcResult {
-        if args.len() < 3 || args.len() > 4 {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        // trials
-        let trials = match self.get_number_no_bools(&args[0], cell) {
-            Ok(f) => f.trunc(),
-            Err(e) => return e,
-        };
-
-        // probability_s
-        let p = match self.get_number_no_bools(&args[1], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-
-        // number_s (lower)
-        let number_s = match self.get_number_no_bools(&args[2], cell) {
-            Ok(f) => f.trunc(),
-            Err(e) => return e,
-        };
-
-        // number_s2 (upper, optional)
-        let number_s2 = if args.len() == 4 {
-            match self.get_number_no_bools(&args[3], cell) {
-                Ok(f) => f.trunc(),
-                Err(e) => return e,
-            }
-        } else {
-            number_s
-        };
-
-        if trials < 0.0
-            || number_s < 0.0
-            || number_s2 < 0.0
-            || number_s > number_s2
-            || number_s2 > trials
-            || p.is_nan()
-            || !(0.0..=1.0).contains(&p)
-        {
-            return CalcResult::new_error(
-                Error::NUM,
-                cell,
-                "Invalid parameters for BINOM.DIST.RANGE".to_string(),
-            );
-        }
-
-        if trials > u64::MAX as f64 {
-            return CalcResult::new_error(
-                Error::NUM,
-                cell,
-                "Number of trials too large".to_string(),
-            );
-        }
-
-        let n = trials as u64;
-        let lower = number_s as u64;
-        let upper = number_s2 as u64;
-
-        let dist = match Binomial::new(p, n) {
-            Ok(d) => d,
-            Err(_) => {
-                return CalcResult::new_error(
-                    Error::NUM,
-                    cell,
-                    "Invalid parameters for binomial distribution".to_string(),
-                )
-            }
-        };
-
-        let prob = if lower == 0 {
-            dist.cdf(upper)
-        } else {
-            let cdf_upper = dist.cdf(upper);
-            let cdf_below_lower = dist.cdf(lower - 1);
-            cdf_upper - cdf_below_lower
-        };
-
-        if prob.is_nan() || prob.is_infinite() {
-            return CalcResult::new_error(
-                Error::NUM,
-                cell,
-                "Invalid result for BINOM.DIST.RANGE".to_string(),
-            );
-        }
-
-        CalcResult::Number(prob)
-    }
-
-    pub(crate) fn fn_binom_inv(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        if args.len() != 3 {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        // trials
-        let trials = match self.get_number_no_bools(&args[0], cell) {
-            Ok(f) => f.trunc(),
-            Err(e) => return e,
-        };
-
-        // probability_s
-        let p = match self.get_number_no_bools(&args[1], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-
-        // alpha
-        let alpha = match self.get_number_no_bools(&args[2], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-
-        if trials < 0.0
-            || trials > u64::MAX as f64
-            || p.is_nan()
-            || !(0.0..=1.0).contains(&p)
-            || alpha.is_nan()
-            || !(0.0..=1.0).contains(&alpha)
-        {
-            return CalcResult::new_error(
-                Error::NUM,
-                cell,
-                "Invalid parameters for BINOM.INV".to_string(),
-            );
-        }
-
-        let n = trials as u64;
-
-        let dist = match Binomial::new(p, n) {
-            Ok(d) => d,
-            Err(_) => {
-                return CalcResult::new_error(
-                    Error::NUM,
-                    cell,
-                    "Invalid parameters for binomial distribution".to_string(),
-                )
-            }
-        };
-
-        // DiscreteCDF::inverse_cdf returns u64 for binomial
-        let k = statrs::distribution::DiscreteCDF::inverse_cdf(&dist, alpha);
-
-        CalcResult::Number(k as f64)
-    }
-
-    pub(crate) fn fn_negbinom_dist(
-        &mut self,
-        args: &[Node],
-        cell: CellReferenceIndex,
-    ) -> CalcResult {
-        use statrs::distribution::{Discrete, DiscreteCDF, NegativeBinomial};
-
-        if args.len() != 4 {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        let number_f = match self.get_number_no_bools(&args[0], cell) {
-            Ok(f) => f.trunc(),
-            Err(e) => return e,
-        };
-        let number_s = match self.get_number_no_bools(&args[1], cell) {
-            Ok(f) => f.trunc(),
-            Err(e) => return e,
-        };
-        let probability_s = match self.get_number_no_bools(&args[2], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-        let cumulative = match self.get_boolean(&args[3], cell) {
-            Ok(b) => b,
-            Err(e) => return e,
-        };
-
-        if number_f < 0.0 || number_s < 1.0 || !(0.0..=1.0).contains(&probability_s) {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "Invalid parameter for NEGBINOM.DIST".to_string(),
-            };
-        }
-
-        // Guard against absurdly large failures that won't fit in u64
-        if number_f > (u64::MAX as f64) {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "Invalid parameter for NEGBINOM.DIST".to_string(),
-            };
-        }
-
-        let dist = match NegativeBinomial::new(number_s, probability_s) {
-            Ok(d) => d,
-            Err(_) => {
-                return CalcResult::Error {
-                    error: Error::NUM,
-                    origin: cell,
-                    message: "Invalid parameter for NEGBINOM.DIST".to_string(),
-                }
-            }
-        };
-
-        let f_u = number_f as u64;
-        let result = if cumulative {
-            dist.cdf(f_u)
-        } else {
-            dist.pmf(f_u)
-        };
-
-        if !result.is_finite() {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "Invalid parameter for NEGBINOM.DIST".to_string(),
-            };
-        }
-
-        CalcResult::Number(result)
-    }
-}

base/src/functions/statistical/chisq.rs

@@ -1,565 +0,0 @@
-use statrs::distribution::{ChiSquared, Continuous, ContinuousCDF};
-
-use crate::expressions::parser::ArrayNode;
-use crate::expressions::types::CellReferenceIndex;
-use crate::{
-    calc_result::CalcResult, expressions::parser::Node, expressions::token::Error, model::Model,
-};
-
-// Helper to check if two shapes are the same or compatible 1D shapes
-pub(crate) fn is_same_shape_or_1d(rows1: i32, cols1: i32, rows2: i32, cols2: i32) -> bool {
-    (rows1 == rows2 && cols1 == cols2)
-        || (rows1 == 1 && cols2 == 1 && cols1 == rows2)
-        || (rows2 == 1 && cols1 == 1 && cols2 == rows1)
-}
-
-impl Model {
-    // CHISQ.DIST(x, deg_freedom, cumulative)
-    pub(crate) fn fn_chisq_dist(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        if args.len() != 3 {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        let x = match self.get_number_no_bools(&args[0], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-
-        let df = match self.get_number_no_bools(&args[1], cell) {
-            Ok(f) => f.trunc(),
-            Err(e) => return e,
-        };
-
-        let cumulative = match self.get_boolean(&args[2], cell) {
-            Ok(b) => b,
-            Err(e) => return e,
-        };
-
-        if x < 0.0 {
-            return CalcResult::new_error(
-                Error::NUM,
-                cell,
-                "x must be >= 0 in CHISQ.DIST".to_string(),
-            );
-        }
-        if df < 1.0 {
-            return CalcResult::new_error(
-                Error::NUM,
-                cell,
-                "degrees of freedom must be >= 1 in CHISQ.DIST".to_string(),
-            );
-        }
-
-        let dist = match ChiSquared::new(df) {
-            Ok(d) => d,
-            Err(_) => {
-                return CalcResult::new_error(
-                    Error::NUM,
-                    cell,
-                    "Invalid parameters for Chi-squared distribution".to_string(),
-                )
-            }
-        };
-
-        let result = if cumulative { dist.cdf(x) } else { dist.pdf(x) };
-
-        if result.is_nan() || result.is_infinite() {
-            return CalcResult::new_error(
-                Error::NUM,
-                cell,
-                "Invalid result for CHISQ.DIST".to_string(),
-            );
-        }
-
-        CalcResult::Number(result)
-    }
-
-    // CHISQ.DIST.RT(x, deg_freedom)
-    pub(crate) fn fn_chisq_dist_rt(
-        &mut self,
-        args: &[Node],
-        cell: CellReferenceIndex,
-    ) -> CalcResult {
-        if args.len() != 2 {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        let x = match self.get_number_no_bools(&args[0], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-
-        let df_raw = match self.get_number_no_bools(&args[1], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-
-        let df = df_raw.trunc();
-
-        if x < 0.0 {
-            return CalcResult::new_error(
-                Error::NUM,
-                cell,
-                "x must be >= 0 in CHISQ.DIST.RT".to_string(),
-            );
-        }
-        if df < 1.0 {
-            return CalcResult::new_error(
-                Error::NUM,
-                cell,
-                "degrees of freedom must be >= 1 in CHISQ.DIST.RT".to_string(),
-            );
-        }
-
-        let dist = match ChiSquared::new(df) {
-            Ok(d) => d,
-            Err(_) => {
-                return CalcResult::new_error(
-                    Error::NUM,
-                    cell,
-                    "Invalid parameters for Chi-squared distribution".to_string(),
-                )
-            }
-        };
-
-        // Right-tail probability: P(X > x).
-        // Use sf(x) directly for better numerical properties than 1 - cdf(x).
-        let result = dist.sf(x);
-
-        if result.is_nan() || result.is_infinite() || result < 0.0 {
-            return CalcResult::new_error(
-                Error::NUM,
-                cell,
-                "Invalid result for CHISQ.DIST.RT".to_string(),
-            );
-        }
-
-        CalcResult::Number(result)
-    }
-
-    // CHISQ.INV(probability, deg_freedom)
-    pub(crate) fn fn_chisq_inv(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        if args.len() != 2 {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        let p = match self.get_number_no_bools(&args[0], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-
-        let df = match self.get_number_no_bools(&args[1], cell) {
-            Ok(f) => f.trunc(),
-            Err(e) => return e,
-        };
-
-        // if probability < 0 or > 1 → #NUM!
-        if !(0.0..=1.0).contains(&p) {
-            return CalcResult::new_error(
-                Error::NUM,
-                cell,
-                "probability must be in [0,1] in CHISQ.INV".to_string(),
-            );
-        }
-        if df < 1.0 {
-            return CalcResult::new_error(
-                Error::NUM,
-                cell,
-                "degrees of freedom must be >= 1 in CHISQ.INV".to_string(),
-            );
-        }
-
-        let dist = match ChiSquared::new(df) {
-            Ok(d) => d,
-            Err(_) => {
-                return CalcResult::new_error(
-                    Error::NUM,
-                    cell,
-                    "Invalid parameters for Chi-squared distribution".to_string(),
-                )
-            }
-        };
-
-        let x = dist.inverse_cdf(p);
-
-        if x.is_nan() || x.is_infinite() || x < 0.0 {
-            return CalcResult::new_error(
-                Error::NUM,
-                cell,
-                "Invalid result for CHISQ.INV".to_string(),
-            );
-        }
-
-        CalcResult::Number(x)
-    }
-
-    // CHISQ.INV.RT(probability, deg_freedom)
-    pub(crate) fn fn_chisq_inv_rt(
-        &mut self,
-        args: &[Node],
-        cell: CellReferenceIndex,
-    ) -> CalcResult {
-        if args.len() != 2 {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        let p = match self.get_number_no_bools(&args[0], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-
-        let df_raw = match self.get_number_no_bools(&args[1], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-
-        let df = df_raw.trunc();
-
-        // if probability < 0 or > 1 → #NUM!
-        if !(0.0..=1.0).contains(&p) {
-            return CalcResult::new_error(
-                Error::NUM,
-                cell,
-                "probability must be in [0,1] in CHISQ.INV.RT".to_string(),
-            );
-        }
-        if df < 1.0 {
-            return CalcResult::new_error(
-                Error::NUM,
-                cell,
-                "degrees of freedom must be >= 1 in CHISQ.INV.RT".to_string(),
-            );
-        }
-
-        let dist = match ChiSquared::new(df) {
-            Ok(d) => d,
-            Err(_) => {
-                return CalcResult::new_error(
-                    Error::NUM,
-                    cell,
-                    "Invalid parameters for Chi-squared distribution".to_string(),
-                )
-            }
-        };
-
-        // Right-tail inverse: p = P(X > x) = SF(x) = 1 - CDF(x)
-        // So x = inverse_cdf(1 - p).
-        let x = dist.inverse_cdf(1.0 - p);
-
-        if x.is_nan() || x.is_infinite() || x < 0.0 {
-            return CalcResult::new_error(
-                Error::NUM,
-                cell,
-                "Invalid result for CHISQ.INV.RT".to_string(),
-            );
-        }
-
-        CalcResult::Number(x)
-    }
-
-    pub(crate) fn values_from_range(
-        &mut self,
-        left: CellReferenceIndex,
-        right: CellReferenceIndex,
-    ) -> Result<Vec<Option<f64>>, CalcResult> {
-        let mut values = Vec::new();
-        for row_offset in 0..=(right.row - left.row) {
-            for col_offset in 0..=(right.column - left.column) {
-                let cell_ref = CellReferenceIndex {
-                    sheet: left.sheet,
-                    row: left.row + row_offset,
-                    column: left.column + col_offset,
-                };
-                let cell_value = self.evaluate_cell(cell_ref);
-                match cell_value {
-                    CalcResult::Number(v) => {
-                        values.push(Some(v));
-                    }
-                    error @ CalcResult::Error { .. } => return Err(error),
-                    _ => {
-                        values.push(None);
-                    }
-                }
-            }
-        }
-        Ok(values)
-    }
-
-    pub(crate) fn values_from_array(
-        &mut self,
-        array: Vec<Vec<ArrayNode>>,
-    ) -> Result<Vec<Option<f64>>, Error> {
-        let mut values = Vec::new();
-        for row in array {
-            for item in row {
-                match item {
-                    ArrayNode::Number(f) => {
-                        values.push(Some(f));
-                    }
-                    ArrayNode::Error(error) => {
-                        return Err(error);
-                    }
-                    _ => {
-                        values.push(None);
-                    }
-                }
-            }
-        }
-        Ok(values)
-    }
-
-    // CHISQ.TEST(actual_range, expected_range)
-    pub(crate) fn fn_chisq_test(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        if args.len() != 2 {
-            return CalcResult::new_args_number_error(cell);
-        }
-        let actual_range = self.evaluate_node_in_context(&args[0], cell);
-        let expected_range = self.evaluate_node_in_context(&args[1], cell);
-
-        let (width, height, values_left, values_right) = match (actual_range, expected_range) {
-            (
-                CalcResult::Range {
-                    left: l1,
-                    right: r1,
-                },
-                CalcResult::Range {
-                    left: l2,
-                    right: r2,
-                },
-            ) => {
-                if l1.sheet != l2.sheet {
-                    return CalcResult::new_error(
-                        Error::VALUE,
-                        cell,
-                        "Ranges are in different sheets".to_string(),
-                    );
-                }
-                let rows1 = r1.row - l1.row + 1;
-                let cols1 = r1.column - l1.column + 1;
-                let rows2 = r2.row - l2.row + 1;
-                let cols2 = r2.column - l2.column + 1;
-                if !is_same_shape_or_1d(rows1, cols1, rows2, cols2) {
-                    return CalcResult::new_error(
-                        Error::VALUE,
-                        cell,
-                        "Ranges must be of the same shape".to_string(),
-                    );
-                }
-                let values_left = match self.values_from_range(l1, r1) {
-                    Err(error) => {
-                        return error;
-                    }
-                    Ok(v) => v,
-                };
-                let values_right = match self.values_from_range(l2, r2) {
-                    Err(error) => {
-                        return error;
-                    }
-                    Ok(v) => v,
-                };
-                (rows1, cols1, values_left, values_right)
-            }
-            (
-                CalcResult::Array(left),
-                CalcResult::Range {
-                    left: l2,
-                    right: r2,
-                },
-            ) => {
-                let rows2 = r2.row - l2.row + 1;
-                let cols2 = r2.column - l2.column + 1;
-
-                let rows1 = left.len() as i32;
-                let cols1 = if rows1 > 0 { left[0].len() as i32 } else { 0 };
-                if !is_same_shape_or_1d(rows1, cols1, rows2, cols2) {
-                    return CalcResult::new_error(
-                        Error::VALUE,
-                        cell,
-                        "Array and range must be of the same shape".to_string(),
-                    );
-                }
-                let values_left = match self.values_from_array(left) {
-                    Err(error) => {
-                        return CalcResult::new_error(
-                            Error::VALUE,
-                            cell,
-                            format!("Error in first array: {:?}", error),
-                        );
-                    }
-                    Ok(v) => v,
-                };
-                let values_right = match self.values_from_range(l2, r2) {
-                    Err(error) => {
-                        return error;
-                    }
-                    Ok(v) => v,
-                };
-                (rows2, cols2, values_left, values_right)
-            }
-            (
-                CalcResult::Range {
-                    left: l1,
-                    right: r1,
-                },
-                CalcResult::Array(right),
-            ) => {
-                let rows1 = r1.row - l1.row + 1;
-                let cols1 = r1.column - l1.column + 1;
-
-                let rows2 = right.len() as i32;
-                let cols2 = if rows2 > 0 { right[0].len() as i32 } else { 0 };
-                if !is_same_shape_or_1d(rows1, cols1, rows2, cols2) {
-                    return CalcResult::new_error(
-                        Error::VALUE,
-                        cell,
-                        "Range and array must be of the same shape".to_string(),
-                    );
-                }
-                let values_left = match self.values_from_range(l1, r1) {
-                    Err(error) => {
-                        return error;
-                    }
-                    Ok(v) => v,
-                };
-                let values_right = match self.values_from_array(right) {
-                    Err(error) => {
-                        return CalcResult::new_error(
-                            Error::VALUE,
-                            cell,
-                            format!("Error in second array: {:?}", error),
-                        );
-                    }
-                    Ok(v) => v,
-                };
-                (rows1, cols1, values_left, values_right)
-            }
-            (CalcResult::Array(left), CalcResult::Array(right)) => {
-                let rows1 = left.len() as i32;
-                let rows2 = right.len() as i32;
-                let cols1 = if rows1 > 0 { left[0].len() as i32 } else { 0 };
-                let cols2 = if rows2 > 0 { right[0].len() as i32 } else { 0 };
-
-                if !is_same_shape_or_1d(rows1, cols1, rows2, cols2) {
-                    return CalcResult::new_error(
-                        Error::VALUE,
-                        cell,
-                        "Arrays must be of the same shape".to_string(),
-                    );
-                }
-                let values_left = match self.values_from_array(left) {
-                    Err(error) => {
-                        return CalcResult::new_error(
-                            Error::VALUE,
-                            cell,
-                            format!("Error in first array: {:?}", error),
-                        );
-                    }
-                    Ok(v) => v,
-                };
-                let values_right = match self.values_from_array(right) {
-                    Err(error) => {
-                        return CalcResult::new_error(
-                            Error::VALUE,
-                            cell,
-                            format!("Error in second array: {:?}", error),
-                        );
-                    }
-                    Ok(v) => v,
-                };
-                (rows1, cols1, values_left, values_right)
-            }
-            _ => {
-                return CalcResult::new_error(
-                    Error::VALUE,
-                    cell,
-                    "Both arguments must be ranges or arrays".to_string(),
-                );
-            }
-        };
-
-        let mut values = Vec::with_capacity(values_left.len());
-
-        // Now we have:
-        // - values: flattened (observed, expected)
-        // - width, height: shape
-        for i in 0..values_left.len() {
-            match (values_left[i], values_right[i]) {
-                (Some(v1), Some(v2)) => {
-                    values.push((v1, v2));
-                }
-                _ => {
-                    values.push((1.0, 1.0));
-                }
-            }
-        }
-        if width == 0 || height == 0 || values.len() < 2 {
-            return CalcResult::new_error(
-                Error::NUM,
-                cell,
-                "CHISQ.TEST requires at least two data points".to_string(),
-            );
-        }
-
-        let mut chi2 = 0.0;
-        for (obs, exp) in &values {
-            if *obs < 0.0 || *exp < 0.0 {
-                return CalcResult::new_error(
-                    Error::NUM,
-                    cell,
-                    "Negative value in CHISQ.TEST data".to_string(),
-                );
-            }
-            if *exp == 0.0 {
-                return CalcResult::new_error(
-                    Error::DIV,
-                    cell,
-                    "Zero expected value in CHISQ.TEST".to_string(),
-                );
-            }
-            let diff = obs - exp;
-            chi2 += (diff * diff) / exp;
-        }
-
-        if chi2 < 0.0 && chi2 > -1e-12 {
-            chi2 = 0.0;
-        }
-
-        let total = width * height;
-        if total <= 1 {
-            return CalcResult::new_error(
-                Error::NUM,
-                cell,
-                "CHISQ.TEST degrees of freedom is zero".to_string(),
-            );
-        }
-
-        let df = if width > 1 && height > 1 {
-            (width - 1) * (height - 1)
-        } else {
-            total - 1
-        };
-
-        let dist = match ChiSquared::new(df as f64) {
-            Ok(d) => d,
-            Err(_) => {
-                return CalcResult::new_error(
-                    Error::NUM,
-                    cell,
-                    "Invalid degrees of freedom in CHISQ.TEST".to_string(),
-                );
-            }
-        };
-
-        let mut p = 1.0 - dist.cdf(chi2);
-
-        // clamp tiny fp noise
-        if p < 0.0 && p > -1e-15 {
-            p = 0.0;
-        }
-        if p > 1.0 && p < 1.0 + 1e-15 {
-            p = 1.0;
-        }
-
-        CalcResult::Number(p)
-    }
-}

base/src/functions/statistical/covariance.rs

@@ -1,264 +0,0 @@
-use crate::expressions::types::CellReferenceIndex;
-use crate::{
-    calc_result::CalcResult, expressions::parser::Node, expressions::token::Error, model::Model,
-};
-
-impl Model {
-    pub(crate) fn fn_covariance_p(
-        &mut self,
-        args: &[Node],
-        cell: CellReferenceIndex,
-    ) -> CalcResult {
-        if args.len() != 2 {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        let values1_opts = match self.evaluate_node_in_context(&args[0], cell) {
-            CalcResult::Range { left, right } => match self.values_from_range(left, right) {
-                Ok(v) => v,
-                Err(error) => return error,
-            },
-            CalcResult::Array(a) => match self.values_from_array(a) {
-                Ok(v) => v,
-                Err(error) => {
-                    return CalcResult::new_error(
-                        Error::VALUE,
-                        cell,
-                        format!("Error in first array: {:?}", error),
-                    );
-                }
-            },
-            _ => {
-                return CalcResult::new_error(
-                    Error::VALUE,
-                    cell,
-                    "First argument must be a range or array".to_string(),
-                );
-            }
-        };
-
-        let values2_opts = match self.evaluate_node_in_context(&args[1], cell) {
-            CalcResult::Range { left, right } => match self.values_from_range(left, right) {
-                Ok(v) => v,
-                Err(error) => return error,
-            },
-            CalcResult::Array(a) => match self.values_from_array(a) {
-                Ok(v) => v,
-                Err(error) => {
-                    return CalcResult::new_error(
-                        Error::VALUE,
-                        cell,
-                        format!("Error in second array: {:?}", error),
-                    );
-                }
-            },
-            _ => {
-                return CalcResult::new_error(
-                    Error::VALUE,
-                    cell,
-                    "Second argument must be a range or array".to_string(),
-                );
-            }
-        };
-
-        // Same number of cells
-        if values1_opts.len() != values2_opts.len() {
-            return CalcResult::new_error(
-                Error::NA,
-                cell,
-                "COVARIANCE.P requires arrays of the same size".to_string(),
-            );
-        }
-
-        // Count numeric data points in each array (ignoring text/booleans/empty)
-        let count1 = values1_opts.iter().filter(|v| v.is_some()).count();
-        let count2 = values2_opts.iter().filter(|v| v.is_some()).count();
-
-        if count1 == 0 || count2 == 0 {
-            return CalcResult::new_error(
-                Error::DIV,
-                cell,
-                "COVARIANCE.P requires at least one numeric value in each array".to_string(),
-            );
-        }
-
-        if count1 != count2 {
-            return CalcResult::new_error(
-                Error::NA,
-                cell,
-                "COVARIANCE.P arrays must have the same number of numeric data points".to_string(),
-            );
-        }
-
-        // Build paired numeric vectors, position by position
-        let mut xs: Vec<f64> = Vec::with_capacity(count1);
-        let mut ys: Vec<f64> = Vec::with_capacity(count2);
-
-        for (v1_opt, v2_opt) in values1_opts.into_iter().zip(values2_opts.into_iter()) {
-            if let (Some(x), Some(y)) = (v1_opt, v2_opt) {
-                xs.push(x);
-                ys.push(y);
-            }
-        }
-
-        let n = xs.len();
-        if n == 0 {
-            // Should be impossible given the checks above, but guard anyway
-            return CalcResult::new_error(
-                Error::DIV,
-                cell,
-                "COVARIANCE.P has no paired numeric data points".to_string(),
-            );
-        }
-
-        let n_f = n as f64;
-
-        let mut sum_x = 0.0;
-        let mut sum_y = 0.0;
-        for i in 0..n {
-            sum_x += xs[i];
-            sum_y += ys[i];
-        }
-        let mean_x = sum_x / n_f;
-        let mean_y = sum_y / n_f;
-
-        let mut sum_prod = 0.0;
-        for i in 0..n {
-            let dx = xs[i] - mean_x;
-            let dy = ys[i] - mean_y;
-            sum_prod += dx * dy;
-        }
-
-        let cov = sum_prod / n_f;
-        CalcResult::Number(cov)
-    }
-
-    pub(crate) fn fn_covariance_s(
-        &mut self,
-        args: &[Node],
-        cell: CellReferenceIndex,
-    ) -> CalcResult {
-        if args.len() != 2 {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        let values1_opts = match self.evaluate_node_in_context(&args[0], cell) {
-            CalcResult::Range { left, right } => match self.values_from_range(left, right) {
-                Ok(v) => v,
-                Err(error) => return error,
-            },
-            CalcResult::Array(a) => match self.values_from_array(a) {
-                Ok(v) => v,
-                Err(error) => {
-                    return CalcResult::new_error(
-                        Error::VALUE,
-                        cell,
-                        format!("Error in first array: {:?}", error),
-                    );
-                }
-            },
-            _ => {
-                return CalcResult::new_error(
-                    Error::VALUE,
-                    cell,
-                    "First argument must be a range or array".to_string(),
-                );
-            }
-        };
-
-        let values2_opts = match self.evaluate_node_in_context(&args[1], cell) {
-            CalcResult::Range { left, right } => match self.values_from_range(left, right) {
-                Ok(v) => v,
-                Err(error) => return error,
-            },
-            CalcResult::Array(a) => match self.values_from_array(a) {
-                Ok(v) => v,
-                Err(error) => {
-                    return CalcResult::new_error(
-                        Error::VALUE,
-                        cell,
-                        format!("Error in second array: {:?}", error),
-                    );
-                }
-            },
-            _ => {
-                return CalcResult::new_error(
-                    Error::VALUE,
-                    cell,
-                    "Second argument must be a range or array".to_string(),
-                );
-            }
-        };
-
-        // Same number of cells
-        if values1_opts.len() != values2_opts.len() {
-            return CalcResult::new_error(
-                Error::NA,
-                cell,
-                "COVARIANCE.S requires arrays of the same size".to_string(),
-            );
-        }
-
-        // Count numeric data points in each array (ignoring text/booleans/empty)
-        let count1 = values1_opts.iter().filter(|v| v.is_some()).count();
-        let count2 = values2_opts.iter().filter(|v| v.is_some()).count();
-
-        if count1 == 0 || count2 == 0 {
-            return CalcResult::new_error(
-                Error::DIV,
-                cell,
-                "COVARIANCE.S requires numeric values in each array".to_string(),
-            );
-        }
-
-        if count1 != count2 {
-            return CalcResult::new_error(
-                Error::NA,
-                cell,
-                "COVARIANCE.S arrays must have the same number of numeric data points".to_string(),
-            );
-        }
-
-        // Build paired numeric vectors
-        let mut xs: Vec<f64> = Vec::with_capacity(count1);
-        let mut ys: Vec<f64> = Vec::with_capacity(count2);
-
-        for (v1_opt, v2_opt) in values1_opts.into_iter().zip(values2_opts.into_iter()) {
-            if let (Some(x), Some(y)) = (v1_opt, v2_opt) {
-                xs.push(x);
-                ys.push(y);
-            }
-        }
-
-        let n = xs.len();
-        if n < 2 {
-            return CalcResult::new_error(
-                Error::DIV,
-                cell,
-                "COVARIANCE.S requires at least two paired data points".to_string(),
-            );
-        }
-
-        let n_f = n as f64;
-
-        let mut sum_x = 0.0;
-        let mut sum_y = 0.0;
-        for i in 0..n {
-            sum_x += xs[i];
-            sum_y += ys[i];
-        }
-        let mean_x = sum_x / n_f;
-        let mean_y = sum_y / n_f;
-
-        let mut sum_prod = 0.0;
-        for i in 0..n {
-            let dx = xs[i] - mean_x;
-            let dy = ys[i] - mean_y;
-            sum_prod += dx * dy;
-        }
-
-        let cov = sum_prod / (n_f - 1.0);
-
-        CalcResult::Number(cov)
-    }
-}

base/src/functions/statistical/devsq.rs

@@ -1,135 +0,0 @@
-use crate::constants::{LAST_COLUMN, LAST_ROW};
-use crate::expressions::parser::ArrayNode;
-use crate::expressions::types::CellReferenceIndex;
-use crate::{
-    calc_result::CalcResult, expressions::parser::Node, expressions::token::Error, model::Model,
-};
-
-impl Model {
-    // DEVSQ(number1, [number2], ...)
-    pub(crate) fn fn_devsq(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        if args.is_empty() {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        let mut sum = 0.0;
-        let mut sumsq = 0.0;
-        let mut count: u64 = 0;
-
-        // tiny helper so we don't repeat ourselves
-        #[inline]
-        fn accumulate(sum: &mut f64, sumsq: &mut f64, count: &mut u64, value: f64) {
-            *sum += value;
-            *sumsq += value * value;
-            *count += 1;
-        }
-
-        for arg in args {
-            match self.evaluate_node_in_context(arg, cell) {
-                CalcResult::Number(value) => {
-                    accumulate(&mut sum, &mut sumsq, &mut count, value);
-                }
-                CalcResult::Range { left, right } => {
-                    if left.sheet != right.sheet {
-                        return CalcResult::new_error(
-                            Error::VALUE,
-                            cell,
-                            "Ranges are in different sheets".to_string(),
-                        );
-                    }
-                    let row1 = left.row;
-                    let mut row2 = right.row;
-                    let column1 = left.column;
-                    let mut column2 = right.column;
-
-                    if row1 == 1 && row2 == LAST_ROW {
-                        row2 = match self.workbook.worksheet(left.sheet) {
-                            Ok(s) => s.dimension().max_row,
-                            Err(_) => {
-                                return CalcResult::new_error(
-                                    Error::ERROR,
-                                    cell,
-                                    format!("Invalid worksheet index: '{}'", left.sheet),
-                                );
-                            }
-                        };
-                    }
-                    if column1 == 1 && column2 == LAST_COLUMN {
-                        column2 = match self.workbook.worksheet(left.sheet) {
-                            Ok(s) => s.dimension().max_column,
-                            Err(_) => {
-                                return CalcResult::new_error(
-                                    Error::ERROR,
-                                    cell,
-                                    format!("Invalid worksheet index: '{}'", left.sheet),
-                                );
-                            }
-                        };
-                    }
-
-                    for row in row1..row2 + 1 {
-                        for column in column1..(column2 + 1) {
-                            match self.evaluate_cell(CellReferenceIndex {
-                                sheet: left.sheet,
-                                row,
-                                column,
-                            }) {
-                                CalcResult::Number(value) => {
-                                    accumulate(&mut sum, &mut sumsq, &mut count, value);
-                                }
-                                error @ CalcResult::Error { .. } => return error,
-                                _ => {
-                                    // We ignore booleans and strings
-                                }
-                            }
-                        }
-                    }
-                }
-                CalcResult::Array(array) => {
-                    for row in array {
-                        for value in row {
-                            match value {
-                                ArrayNode::Number(value) => {
-                                    accumulate(&mut sum, &mut sumsq, &mut count, value);
-                                }
-                                ArrayNode::Error(error) => {
-                                    return CalcResult::Error {
-                                        error,
-                                        origin: cell,
-                                        message: "Error in array".to_string(),
-                                    }
-                                }
-                                _ => {
-                                    // We ignore booleans and strings
-                                }
-                            }
-                        }
-                    }
-                }
-                error @ CalcResult::Error { .. } => return error,
-                _ => {
-                    // We ignore booleans and strings
-                }
-            };
-        }
-
-        if count == 0 {
-            // No numeric data at all
-            return CalcResult::new_error(
-                Error::DIV,
-                cell,
-                "DEVSQ with no numeric data".to_string(),
-            );
-        }
-
-        let n = count as f64;
-        let mut result = sumsq - (sum * sum) / n;
-
-        // Numerical noise can make result slightly negative when it should be 0
-        if result < 0.0 && result > -1e-12 {
-            result = 0.0;
-        }
-
-        CalcResult::Number(result)
-    }
-}

base/src/functions/statistical/exponential.rs

@@ -1,54 +0,0 @@
-use crate::expressions::types::CellReferenceIndex;
-use crate::{
-    calc_result::CalcResult, expressions::parser::Node, expressions::token::Error, model::Model,
-};
-
-impl Model {
-    pub(crate) fn fn_expon_dist(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        // EXPON.DIST(x, lambda, cumulative)
-        if args.len() != 3 {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        let x = match self.get_number_no_bools(&args[0], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-
-        let lambda = match self.get_number_no_bools(&args[1], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-
-        let cumulative = match self.get_boolean(&args[2], cell) {
-            Ok(b) => b,
-            Err(e) => return e,
-        };
-
-        if x < 0.0 || lambda <= 0.0 {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "Invalid parameters for EXPON.DIST".to_string(),
-            };
-        }
-
-        let result = if cumulative {
-            // CDF
-            1.0 - (-lambda * x).exp()
-        } else {
-            // PDF
-            lambda * (-lambda * x).exp()
-        };
-
-        if result.is_nan() || result.is_infinite() {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "Invalid result for EXPON.DIST".to_string(),
-            };
-        }
-
-        CalcResult::Number(result)
-    }
-}

base/src/functions/statistical/fisher.rs

@@ -1,299 +0,0 @@
-use statrs::distribution::{Continuous, ContinuousCDF, FisherSnedecor};
-
-use crate::expressions::types::CellReferenceIndex;
-use crate::{
-    calc_result::CalcResult, expressions::parser::Node, expressions::token::Error, model::Model,
-};
-
-impl Model {
-    // FISHER(x) = 0.5 * ln((1 + x) / (1 - x))
-    pub(crate) fn fn_fisher(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        if args.len() != 1 {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        let x = match self.get_number_no_bools(&args[0], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-
-        if x <= -1.0 || x >= 1.0 {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "x must be between -1 and 1 (exclusive) in FISHER".to_string(),
-            };
-        }
-
-        let ratio = (1.0 + x) / (1.0 - x);
-        let result = 0.5 * ratio.ln();
-
-        if result.is_nan() || result.is_infinite() {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "Invalid result for FISHER".to_string(),
-            };
-        }
-
-        CalcResult::Number(result)
-    }
-
-    // FISHERINV(y) = (e^(2y) - 1) / (e^(2y) + 1) = tanh(y)
-    pub(crate) fn fn_fisher_inv(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        if args.len() != 1 {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        let y = match self.get_number_no_bools(&args[0], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-
-        // Use tanh directly to avoid overflow from exp(2y)
-        let result = y.tanh();
-
-        if result.is_nan() || result.is_infinite() {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "Invalid result for FISHERINV".to_string(),
-            };
-        }
-
-        CalcResult::Number(result)
-    }
-
-    // F.DIST(x, deg_freedom1, deg_freedom2, cumulative)
-    pub(crate) fn fn_f_dist(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        if args.len() != 4 {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        let x = match self.get_number_no_bools(&args[0], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-
-        let df1 = match self.get_number_no_bools(&args[1], cell) {
-            Ok(f) => f.trunc(),
-            Err(e) => return e,
-        };
-        let df2 = match self.get_number_no_bools(&args[2], cell) {
-            Ok(f) => f.trunc(),
-            Err(e) => return e,
-        };
-
-        let cumulative = match self.get_boolean(&args[3], cell) {
-            Ok(b) => b,
-            Err(e) => return e,
-        };
-
-        // Excel domain checks
-        if x < 0.0 {
-            return CalcResult::new_error(Error::NUM, cell, "x must be >= 0 in F.DIST".to_string());
-        }
-        if df1 < 1.0 || df2 < 1.0 {
-            return CalcResult::new_error(
-                Error::NUM,
-                cell,
-                "degrees of freedom must be >= 1 in F.DIST".to_string(),
-            );
-        }
-
-        let dist = match FisherSnedecor::new(df1, df2) {
-            Ok(d) => d,
-            Err(_) => {
-                return CalcResult::new_error(
-                    Error::NUM,
-                    cell,
-                    "Invalid parameters for F distribution".to_string(),
-                )
-            }
-        };
-
-        let result = if cumulative { dist.cdf(x) } else { dist.pdf(x) };
-
-        if result.is_nan() || result.is_infinite() {
-            return CalcResult::new_error(
-                Error::NUM,
-                cell,
-                "Invalid result for F.DIST".to_string(),
-            );
-        }
-
-        CalcResult::Number(result)
-    }
-
-    pub(crate) fn fn_f_dist_rt(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        // F.DIST.RT(x, deg_freedom1, deg_freedom2)
-        if args.len() != 3 {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        let x = match self.get_number_no_bools(&args[0], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-
-        let df1 = match self.get_number_no_bools(&args[1], cell) {
-            Ok(f) => f.trunc(),
-            Err(e) => return e,
-        };
-        let df2 = match self.get_number_no_bools(&args[2], cell) {
-            Ok(f) => f.trunc(),
-            Err(e) => return e,
-        };
-
-        if x < 0.0 {
-            return CalcResult::new_error(
-                Error::NUM,
-                cell,
-                "x must be >= 0 in F.DIST.RT".to_string(),
-            );
-        }
-        if df1 < 1.0 || df2 < 1.0 {
-            return CalcResult::new_error(
-                Error::NUM,
-                cell,
-                "degrees of freedom must be >= 1 in F.DIST.RT".to_string(),
-            );
-        }
-
-        let dist = match FisherSnedecor::new(df1, df2) {
-            Ok(d) => d,
-            Err(_) => {
-                return CalcResult::new_error(
-                    Error::NUM,
-                    cell,
-                    "Invalid parameters for F distribution".to_string(),
-                )
-            }
-        };
-
-        // Right-tail probability: P(F > x) = 1 - CDF(x)
-        let result = 1.0 - dist.cdf(x);
-
-        if result.is_nan() || result.is_infinite() || result < 0.0 {
-            return CalcResult::new_error(
-                Error::NUM,
-                cell,
-                "Invalid result for F.DIST.RT".to_string(),
-            );
-        }
-
-        CalcResult::Number(result)
-    }
-
-    // F.INV(probability, deg_freedom1, deg_freedom2)
-    pub(crate) fn fn_f_inv(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        if args.len() != 3 {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        let p = match self.get_number_no_bools(&args[0], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-        let df1 = match self.get_number_no_bools(&args[1], cell) {
-            Ok(f) => f.trunc(),
-            Err(e) => return e,
-        };
-        let df2 = match self.get_number_no_bools(&args[2], cell) {
-            Ok(f) => f.trunc(),
-            Err(e) => return e,
-        };
-
-        // probability < 0 or > 1 → #NUM!
-        if !(0.0..=1.0).contains(&p) {
-            return CalcResult::new_error(
-                Error::NUM,
-                cell,
-                "probability must be in [0,1] in F.INV".to_string(),
-            );
-        }
-        if df1 < 1.0 || df2 < 1.0 {
-            return CalcResult::new_error(
-                Error::NUM,
-                cell,
-                "degrees of freedom must be >= 1 in F.INV".to_string(),
-            );
-        }
-
-        let dist = match FisherSnedecor::new(df1, df2) {
-            Ok(d) => d,
-            Err(_) => {
-                return CalcResult::new_error(
-                    Error::NUM,
-                    cell,
-                    "Invalid parameters for F distribution".to_string(),
-                )
-            }
-        };
-
-        let x = dist.inverse_cdf(p);
-        if x.is_nan() || x.is_infinite() || x < 0.0 {
-            return CalcResult::new_error(Error::NUM, cell, "Invalid result for F.INV".to_string());
-        }
-
-        CalcResult::Number(x)
-    }
-
-    // F.INV.RT(probability, deg_freedom1, deg_freedom2)
-    pub(crate) fn fn_f_inv_rt(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        if args.len() != 3 {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        let p = match self.get_number_no_bools(&args[0], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-        let df1 = match self.get_number_no_bools(&args[1], cell) {
-            Ok(f) => f.trunc(),
-            Err(e) => return e,
-        };
-        let df2 = match self.get_number_no_bools(&args[2], cell) {
-            Ok(f) => f.trunc(),
-            Err(e) => return e,
-        };
-
-        if p <= 0.0 || p > 1.0 {
-            return CalcResult::new_error(
-                Error::NUM,
-                cell,
-                "probability must be in (0,1] in F.INV.RT".to_string(),
-            );
-        }
-        if df1 < 1.0 || df2 < 1.0 {
-            return CalcResult::new_error(
-                Error::NUM,
-                cell,
-                "degrees of freedom must be >= 1 in F.INV.RT".to_string(),
-            );
-        }
-
-        let dist = match FisherSnedecor::new(df1, df2) {
-            Ok(d) => d,
-            Err(_) => {
-                return CalcResult::new_error(
-                    Error::NUM,
-                    cell,
-                    "Invalid parameters for F distribution".to_string(),
-                )
-            }
-        };
-
-        // p is right-tail: p = P(F > x) = 1 - CDF(x)
-        let x = dist.inverse_cdf(1.0 - p);
-        if x.is_nan() || x.is_infinite() || x < 0.0 {
-            return CalcResult::new_error(
-                Error::NUM,
-                cell,
-                "Invalid result for F.INV.RT".to_string(),
-            );
-        }
-
-        CalcResult::Number(x)
-    }
-}

base/src/functions/statistical/gamma.rs

@@ -1,194 +0,0 @@
-use statrs::distribution::{Continuous, ContinuousCDF, Gamma};
-use statrs::function::gamma::{gamma, ln_gamma};
-
-use crate::expressions::types::CellReferenceIndex;
-use crate::{
-    calc_result::CalcResult, expressions::parser::Node, expressions::token::Error, model::Model,
-};
-
-impl Model {
-    pub(crate) fn fn_gamma(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        if args.len() != 1 {
-            return CalcResult::new_args_number_error(cell);
-        }
-        let x = match self.get_number_no_bools(&args[0], cell) {
-            Ok(f) => f,
-            Err(s) => return s,
-        };
-        if x < 0.0 && x.floor() == x {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "Invalid parameter for Gamma function".to_string(),
-            };
-        }
-        let result = gamma(x);
-        if result.is_nan() || result.is_infinite() {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "Invalid parameter for Gamma function".to_string(),
-            };
-        }
-        CalcResult::Number(result)
-    }
-
-    pub(crate) fn fn_gamma_dist(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        // GAMMA.DIST(x, alpha, beta, cumulative)
-        if args.len() != 4 {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        let x = match self.get_number_no_bools(&args[0], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-        let alpha = match self.get_number_no_bools(&args[1], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-        let beta_scale = match self.get_number_no_bools(&args[2], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-
-        let cumulative = match self.get_boolean(&args[3], cell) {
-            Ok(b) => b,
-            Err(e) => return e,
-        };
-
-        if x < 0.0 {
-            return CalcResult::new_error(
-                Error::NUM,
-                cell,
-                "x must be >= 0 in GAMMA.DIST".to_string(),
-            );
-        }
-        if alpha <= 0.0 || beta_scale <= 0.0 {
-            return CalcResult::new_error(
-                Error::NUM,
-                cell,
-                "alpha and beta must be > 0 in GAMMA.DIST".to_string(),
-            );
-        }
-
-        let rate = 1.0 / beta_scale;
-
-        let dist = match Gamma::new(alpha, rate) {
-            Ok(d) => d,
-            Err(_) => {
-                return CalcResult::new_error(
-                    Error::NUM,
-                    cell,
-                    "Invalid parameters for Gamma distribution".to_string(),
-                )
-            }
-        };
-
-        let result = if cumulative { dist.cdf(x) } else { dist.pdf(x) };
-
-        if result.is_nan() || result.is_infinite() {
-            return CalcResult::new_error(
-                Error::NUM,
-                cell,
-                "Invalid result for GAMMA.DIST".to_string(),
-            );
-        }
-
-        CalcResult::Number(result)
-    }
-
-    pub(crate) fn fn_gamma_inv(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        // GAMMA.INV(probability, alpha, beta)
-        if args.len() != 3 {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        let p = match self.get_number_no_bools(&args[0], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-        let alpha = match self.get_number_no_bools(&args[1], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-        let beta_scale = match self.get_number_no_bools(&args[2], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-
-        if !(0.0..=1.0).contains(&p) {
-            return CalcResult::new_error(
-                Error::NUM,
-                cell,
-                "probability must be in [0,1] in GAMMA.INV".to_string(),
-            );
-        }
-
-        if alpha <= 0.0 || beta_scale <= 0.0 {
-            return CalcResult::new_error(
-                Error::NUM,
-                cell,
-                "alpha and beta must be > 0 in GAMMA.INV".to_string(),
-            );
-        }
-
-        let rate = 1.0 / beta_scale;
-
-        let dist = match Gamma::new(alpha, rate) {
-            Ok(d) => d,
-            Err(_) => {
-                return CalcResult::new_error(
-                    Error::NUM,
-                    cell,
-                    "Invalid parameters for Gamma distribution".to_string(),
-                )
-            }
-        };
-
-        let x = dist.inverse_cdf(p);
-        if x.is_nan() || x.is_infinite() || x < 0.0 {
-            return CalcResult::new_error(
-                Error::NUM,
-                cell,
-                "Invalid result for GAMMA.INV".to_string(),
-            );
-        }
-
-        CalcResult::Number(x)
-    }
-
-    pub(crate) fn fn_gamma_ln(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        if args.len() != 1 {
-            return CalcResult::new_args_number_error(cell);
-        }
-        let x = match self.get_number_no_bools(&args[0], cell) {
-            Ok(f) => f,
-            Err(s) => return s,
-        };
-        if x < 0.0 {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "Invalid parameter for Gamma function".to_string(),
-            };
-        }
-        let result = ln_gamma(x);
-        if result.is_nan() || result.is_infinite() {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "Invalid parameter for Gamma Ln function".to_string(),
-            };
-        }
-        CalcResult::Number(result)
-    }
-
-    pub(crate) fn fn_gamma_ln_precise(
-        &mut self,
-        args: &[Node],
-        cell: CellReferenceIndex,
-    ) -> CalcResult {
-        self.fn_gamma_ln(args, cell)
-    }
-}

base/src/functions/statistical/geomean.rs

@@ -1,87 +0,0 @@
-use crate::expressions::types::CellReferenceIndex;
-use crate::{
-    calc_result::CalcResult, expressions::parser::Node, expressions::token::Error, model::Model,
-};
-
-impl Model {
-    pub(crate) fn fn_geomean(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        if args.is_empty() {
-            return CalcResult::new_args_number_error(cell);
-        }
-        let mut count = 0.0;
-        let mut product = 1.0;
-        for arg in args {
-            match self.evaluate_node_in_context(arg, cell) {
-                CalcResult::Number(value) => {
-                    count += 1.0;
-                    product *= value;
-                }
-                CalcResult::Boolean(b) => {
-                    if let Node::ReferenceKind { .. } = arg {
-                    } else {
-                        product *= if b { 1.0 } else { 0.0 };
-                        count += 1.0;
-                    }
-                }
-                CalcResult::Range { left, right } => {
-                    if left.sheet != right.sheet {
-                        return CalcResult::new_error(
-                            Error::VALUE,
-                            cell,
-                            "Ranges are in different sheets".to_string(),
-                        );
-                    }
-                    for row in left.row..(right.row + 1) {
-                        for column in left.column..(right.column + 1) {
-                            match self.evaluate_cell(CellReferenceIndex {
-                                sheet: left.sheet,
-                                row,
-                                column,
-                            }) {
-                                CalcResult::Number(value) => {
-                                    count += 1.0;
-                                    product *= value;
-                                }
-                                error @ CalcResult::Error { .. } => return error,
-                                CalcResult::Range { .. } => {
-                                    return CalcResult::new_error(
-                                        Error::ERROR,
-                                        cell,
-                                        "Unexpected Range".to_string(),
-                                    );
-                                }
-                                _ => {}
-                            }
-                        }
-                    }
-                }
-                error @ CalcResult::Error { .. } => return error,
-                CalcResult::String(s) => {
-                    if let Node::ReferenceKind { .. } = arg {
-                        // Do nothing
-                    } else if let Ok(t) = s.parse::<f64>() {
-                        product *= t;
-                        count += 1.0;
-                    } else {
-                        return CalcResult::Error {
-                            error: Error::VALUE,
-                            origin: cell,
-                            message: "Argument cannot be cast into number".to_string(),
-                        };
-                    }
-                }
-                _ => {
-                    // Ignore everything else
-                }
-            };
-        }
-        if count == 0.0 {
-            return CalcResult::Error {
-                error: Error::DIV,
-                origin: cell,
-                message: "Division by Zero".to_string(),
-            };
-        }
-        CalcResult::Number(product.powf(1.0 / count))
-    }
-}

base/src/functions/statistical/hypegeom.rs

@@ -1,108 +0,0 @@
-use statrs::distribution::{Discrete, DiscreteCDF, Hypergeometric};
-
-use crate::expressions::types::CellReferenceIndex;
-use crate::{
-    calc_result::CalcResult, expressions::parser::Node, expressions::token::Error, model::Model,
-};
-
-impl Model {
-    // =HYPGEOM.DIST(sample_s, number_sample, population_s, number_pop, cumulative)
-    pub(crate) fn fn_hyp_geom_dist(
-        &mut self,
-        args: &[Node],
-        cell: CellReferenceIndex,
-    ) -> CalcResult {
-        if args.len() != 5 {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        // sample_s (number of successes in the sample)
-        let sample_s = match self.get_number_no_bools(&args[0], cell) {
-            Ok(f) => f.trunc(),
-            Err(e) => return e,
-        };
-
-        // number_sample (sample size)
-        let number_sample = match self.get_number_no_bools(&args[1], cell) {
-            Ok(f) => f.trunc(),
-            Err(e) => return e,
-        };
-
-        // population_s (number of successes in the population)
-        let population_s = match self.get_number_no_bools(&args[2], cell) {
-            Ok(f) => f.trunc(),
-            Err(e) => return e,
-        };
-
-        // number_pop (population size)
-        let number_pop = match self.get_number_no_bools(&args[3], cell) {
-            Ok(f) => f.trunc(),
-            Err(e) => return e,
-        };
-
-        let cumulative = match self.get_boolean(&args[4], cell) {
-            Ok(b) => b,
-            Err(e) => return e,
-        };
-
-        if sample_s < 0.0 || sample_s > f64::min(number_sample, population_s) {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "Invalid parameters for HYPGEOM.DIST".to_string(),
-            };
-        }
-
-        if sample_s < f64::max(0.0, number_sample + population_s - number_pop) {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "Invalid parameters for HYPGEOM.DIST".to_string(),
-            };
-        }
-
-        if number_sample <= 0.0 || number_sample > number_pop {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "Invalid parameters for HYPGEOM.DIST".to_string(),
-            };
-        }
-
-        if population_s <= 0.0 || population_s > number_pop {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "Invalid parameters for HYPGEOM.DIST".to_string(),
-            };
-        }
-
-        let n_pop = number_pop as u64;
-        let k_pop = population_s as u64;
-        let n_sample = number_sample as u64;
-        let k = sample_s as u64;
-
-        let dist = match Hypergeometric::new(n_pop, k_pop, n_sample) {
-            Ok(d) => d,
-            Err(_) => {
-                return CalcResult::new_error(
-                    Error::NUM,
-                    cell,
-                    "Invalid parameters for hypergeometric distribution".to_string(),
-                )
-            }
-        };
-
-        let prob = if cumulative { dist.cdf(k) } else { dist.pmf(k) };
-
-        if !prob.is_finite() {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "Invalid result for HYPGEOM.DIST".to_string(),
-            };
-        }
-
-        CalcResult::Number(prob)
-    }
-}

base/src/functions/statistical/if_ifs.rs

@@ -1,337 +0,0 @@
-use crate::constants::{LAST_COLUMN, LAST_ROW};
-use crate::expressions::types::CellReferenceIndex;
-use crate::functions::util::build_criteria;
-use crate::{
-    calc_result::{CalcResult, Range},
-    expressions::parser::Node,
-    expressions::token::Error,
-    model::Model,
-};
-
-impl Model {
-    pub(crate) fn fn_countif(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        if args.len() == 2 {
-            let arguments = vec![args[0].clone(), args[1].clone()];
-            self.fn_countifs(&arguments, cell)
-        } else {
-            CalcResult::new_args_number_error(cell)
-        }
-    }
-
-    /// AVERAGEIF(criteria_range, criteria, [average_range])
-    /// if average_rage is missing then criteria_range will be used
-    pub(crate) fn fn_averageif(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        if args.len() == 2 {
-            let arguments = vec![args[0].clone(), args[0].clone(), args[1].clone()];
-            self.fn_averageifs(&arguments, cell)
-        } else if args.len() == 3 {
-            let arguments = vec![args[2].clone(), args[0].clone(), args[1].clone()];
-            self.fn_averageifs(&arguments, cell)
-        } else {
-            CalcResult::new_args_number_error(cell)
-        }
-    }
-
-    // FIXME: This function shares a lot of code with apply_ifs. Can we merge them?
-    pub(crate) fn fn_countifs(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        let args_count = args.len();
-        if args_count < 2 || !args_count.is_multiple_of(2) {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        let case_count = args_count / 2;
-        // NB: this is a beautiful example of the borrow checker
-        // The order of these two definitions cannot be swapped.
-        let mut criteria = Vec::new();
-        let mut fn_criteria = Vec::new();
-        let ranges = &mut Vec::new();
-        for case_index in 0..case_count {
-            let criterion = self.evaluate_node_in_context(&args[case_index * 2 + 1], cell);
-            criteria.push(criterion);
-            // NB: We cannot do:
-            // fn_criteria.push(build_criteria(&criterion));
-            // because criterion doesn't live long enough
-            let result = self.evaluate_node_in_context(&args[case_index * 2], cell);
-            if result.is_error() {
-                return result;
-            }
-            if let CalcResult::Range { left, right } = result {
-                if left.sheet != right.sheet {
-                    return CalcResult::new_error(
-                        Error::VALUE,
-                        cell,
-                        "Ranges are in different sheets".to_string(),
-                    );
-                }
-                // TODO test ranges are of the same size as sum_range
-                ranges.push(Range { left, right });
-            } else {
-                return CalcResult::new_error(Error::VALUE, cell, "Expected a range".to_string());
-            }
-        }
-        for criterion in criteria.iter() {
-            fn_criteria.push(build_criteria(criterion));
-        }
-
-        let mut total = 0.0;
-        let first_range = &ranges[0];
-        let left_row = first_range.left.row;
-        let left_column = first_range.left.column;
-        let right_row = first_range.right.row;
-        let right_column = first_range.right.column;
-
-        let dimension = match self.workbook.worksheet(first_range.left.sheet) {
-            Ok(s) => s.dimension(),
-            Err(_) => {
-                return CalcResult::new_error(
-                    Error::ERROR,
-                    cell,
-                    format!("Invalid worksheet index: '{}'", first_range.left.sheet),
-                )
-            }
-        };
-        let max_row = dimension.max_row;
-        let max_column = dimension.max_column;
-
-        let open_row = left_row == 1 && right_row == LAST_ROW;
-        let open_column = left_column == 1 && right_column == LAST_COLUMN;
-
-        for row in left_row..right_row + 1 {
-            if open_row && row > max_row {
-                // If the row is larger than the max row in the sheet then all cells are empty.
-                // We compute it only once
-                let mut is_true = true;
-                for fn_criterion in fn_criteria.iter() {
-                    if !fn_criterion(&CalcResult::EmptyCell) {
-                        is_true = false;
-                        break;
-                    }
-                }
-                if is_true {
-                    total += ((LAST_ROW - max_row) * (right_column - left_column + 1)) as f64;
-                }
-                break;
-            }
-            for column in left_column..right_column + 1 {
-                if open_column && column > max_column {
-                    // If the column is larger than the max column in the sheet then all cells are empty.
-                    // We compute it only once
-                    let mut is_true = true;
-                    for fn_criterion in fn_criteria.iter() {
-                        if !fn_criterion(&CalcResult::EmptyCell) {
-                            is_true = false;
-                            break;
-                        }
-                    }
-                    if is_true {
-                        total += (LAST_COLUMN - max_column) as f64;
-                    }
-                    break;
-                }
-                let mut is_true = true;
-                for case_index in 0..case_count {
-                    // We check if value in range n meets criterion n
-                    let range = &ranges[case_index];
-                    let fn_criterion = &fn_criteria[case_index];
-                    let value = self.evaluate_cell(CellReferenceIndex {
-                        sheet: range.left.sheet,
-                        row: range.left.row + row - first_range.left.row,
-                        column: range.left.column + column - first_range.left.column,
-                    });
-                    if !fn_criterion(&value) {
-                        is_true = false;
-                        break;
-                    }
-                }
-                if is_true {
-                    total += 1.0;
-                }
-            }
-        }
-        CalcResult::Number(total)
-    }
-
-    pub(crate) fn apply_ifs<F>(
-        &mut self,
-        args: &[Node],
-        cell: CellReferenceIndex,
-        mut apply: F,
-    ) -> Result<(), CalcResult>
-    where
-        F: FnMut(f64),
-    {
-        let args_count = args.len();
-        if args_count < 3 || args_count.is_multiple_of(2) {
-            return Err(CalcResult::new_args_number_error(cell));
-        }
-        let arg_0 = self.evaluate_node_in_context(&args[0], cell);
-        if arg_0.is_error() {
-            return Err(arg_0);
-        }
-        let sum_range = if let CalcResult::Range { left, right } = arg_0 {
-            if left.sheet != right.sheet {
-                return Err(CalcResult::new_error(
-                    Error::VALUE,
-                    cell,
-                    "Ranges are in different sheets".to_string(),
-                ));
-            }
-            Range { left, right }
-        } else {
-            return Err(CalcResult::new_error(
-                Error::VALUE,
-                cell,
-                "Expected a range".to_string(),
-            ));
-        };
-
-        let case_count = (args_count - 1) / 2;
-        // NB: this is a beautiful example of the borrow checker
-        // The order of these two definitions cannot be swapped.
-        let mut criteria = Vec::new();
-        let mut fn_criteria = Vec::new();
-        let ranges = &mut Vec::new();
-        for case_index in 1..=case_count {
-            let criterion = self.evaluate_node_in_context(&args[case_index * 2], cell);
-            // NB: criterion might be an error. That's ok
-            criteria.push(criterion);
-            // NB: We cannot do:
-            // fn_criteria.push(build_criteria(&criterion));
-            // because criterion doesn't live long enough
-            let result = self.evaluate_node_in_context(&args[case_index * 2 - 1], cell);
-            if result.is_error() {
-                return Err(result);
-            }
-            if let CalcResult::Range { left, right } = result {
-                if left.sheet != right.sheet {
-                    return Err(CalcResult::new_error(
-                        Error::VALUE,
-                        cell,
-                        "Ranges are in different sheets".to_string(),
-                    ));
-                }
-                // TODO test ranges are of the same size as sum_range
-                ranges.push(Range { left, right });
-            } else {
-                return Err(CalcResult::new_error(
-                    Error::VALUE,
-                    cell,
-                    "Expected a range".to_string(),
-                ));
-            }
-        }
-        for criterion in criteria.iter() {
-            fn_criteria.push(build_criteria(criterion));
-        }
-
-        let left_row = sum_range.left.row;
-        let left_column = sum_range.left.column;
-        let mut right_row = sum_range.right.row;
-        let mut right_column = sum_range.right.column;
-
-        if left_row == 1 && right_row == LAST_ROW {
-            right_row = match self.workbook.worksheet(sum_range.left.sheet) {
-                Ok(s) => s.dimension().max_row,
-                Err(_) => {
-                    return Err(CalcResult::new_error(
-                        Error::ERROR,
-                        cell,
-                        format!("Invalid worksheet index: '{}'", sum_range.left.sheet),
-                    ));
-                }
-            };
-        }
-        if left_column == 1 && right_column == LAST_COLUMN {
-            right_column = match self.workbook.worksheet(sum_range.left.sheet) {
-                Ok(s) => s.dimension().max_column,
-                Err(_) => {
-                    return Err(CalcResult::new_error(
-                        Error::ERROR,
-                        cell,
-                        format!("Invalid worksheet index: '{}'", sum_range.left.sheet),
-                    ));
-                }
-            };
-        }
-
-        for row in left_row..right_row + 1 {
-            for column in left_column..right_column + 1 {
-                let mut is_true = true;
-                for case_index in 0..case_count {
-                    // We check if value in range n meets criterion n
-                    let range = &ranges[case_index];
-                    let fn_criterion = &fn_criteria[case_index];
-                    let value = self.evaluate_cell(CellReferenceIndex {
-                        sheet: range.left.sheet,
-                        row: range.left.row + row - sum_range.left.row,
-                        column: range.left.column + column - sum_range.left.column,
-                    });
-                    if !fn_criterion(&value) {
-                        is_true = false;
-                        break;
-                    }
-                }
-                if is_true {
-                    let v = self.evaluate_cell(CellReferenceIndex {
-                        sheet: sum_range.left.sheet,
-                        row,
-                        column,
-                    });
-                    match v {
-                        CalcResult::Number(n) => apply(n),
-                        CalcResult::Error { .. } => return Err(v),
-                        _ => {}
-                    }
-                }
-            }
-        }
-        Ok(())
-    }
-
-    pub(crate) fn fn_averageifs(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        let mut total = 0.0;
-        let mut count = 0.0;
-
-        let average = |value: f64| {
-            total += value;
-            count += 1.0;
-        };
-        if let Err(e) = self.apply_ifs(args, cell, average) {
-            return e;
-        }
-
-        if count == 0.0 {
-            return CalcResult::Error {
-                error: Error::DIV,
-                origin: cell,
-                message: "division by 0".to_string(),
-            };
-        }
-        CalcResult::Number(total / count)
-    }
-
-    pub(crate) fn fn_minifs(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        let mut min = f64::INFINITY;
-        let apply_min = |value: f64| min = value.min(min);
-        if let Err(e) = self.apply_ifs(args, cell, apply_min) {
-            return e;
-        }
-
-        if min.is_infinite() {
-            min = 0.0;
-        }
-        CalcResult::Number(min)
-    }
-
-    pub(crate) fn fn_maxifs(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        let mut max = -f64::INFINITY;
-        let apply_max = |value: f64| max = value.max(max);
-        if let Err(e) = self.apply_ifs(args, cell, apply_max) {
-            return e;
-        }
-        if max.is_infinite() {
-            max = 0.0;
-        }
-        CalcResult::Number(max)
-    }
-}

base/src/functions/statistical/log_normal.rs

@@ -1,124 +0,0 @@
-use statrs::distribution::{Continuous, ContinuousCDF, LogNormal};
-
-use crate::expressions::types::CellReferenceIndex;
-use crate::{
-    calc_result::CalcResult, expressions::parser::Node, expressions::token::Error, model::Model,
-};
-
-impl Model {
-    pub(crate) fn fn_log_norm_dist(
-        &mut self,
-        args: &[Node],
-        cell: CellReferenceIndex,
-    ) -> CalcResult {
-        if args.len() != 4 {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        let x = match self.get_number_no_bools(&args[0], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-        let mean = match self.get_number_no_bools(&args[1], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-        let std_dev = match self.get_number_no_bools(&args[2], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-        let cumulative = match self.get_boolean(&args[3], cell) {
-            Ok(b) => b,
-            Err(e) => return e,
-        };
-
-        // Excel domain checks
-        if x <= 0.0 || std_dev <= 0.0 {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "Invalid parameter for LOGNORM.DIST".to_string(),
-            };
-        }
-
-        let dist = match LogNormal::new(mean, std_dev) {
-            Ok(d) => d,
-            Err(_) => {
-                return CalcResult::Error {
-                    error: Error::NUM,
-                    origin: cell,
-                    message: "Invalid parameter for LOGNORM.DIST".to_string(),
-                }
-            }
-        };
-
-        let result = if cumulative { dist.cdf(x) } else { dist.pdf(x) };
-
-        if !result.is_finite() {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "Invalid parameter for LOGNORM.DIST".to_string(),
-            };
-        }
-
-        CalcResult::Number(result)
-    }
-
-    pub(crate) fn fn_log_norm_inv(
-        &mut self,
-        args: &[Node],
-        cell: CellReferenceIndex,
-    ) -> CalcResult {
-        use statrs::distribution::{ContinuousCDF, LogNormal};
-
-        if args.len() != 3 {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        let p = match self.get_number_no_bools(&args[0], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-        let mean = match self.get_number_no_bools(&args[1], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-        let std_dev = match self.get_number_no_bools(&args[2], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-
-        // Excel domain checks
-        if p <= 0.0 || p >= 1.0 || std_dev <= 0.0 {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "Invalid parameter for LOGNORM.INV".to_string(),
-            };
-        }
-
-        let dist = match LogNormal::new(mean, std_dev) {
-            Ok(d) => d,
-            Err(_) => {
-                return CalcResult::Error {
-                    error: Error::NUM,
-                    origin: cell,
-                    message: "Invalid parameter for LOGNORM.INV".to_string(),
-                }
-            }
-        };
-
-        let result = dist.inverse_cdf(p);
-
-        if !result.is_finite() {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "Invalid parameter for LOGNORM.INV".to_string(),
-            };
-        }
-
-        CalcResult::Number(result)
-    }
-}

base/src/functions/statistical/mod.rs

@@ -1,23 +0,0 @@
-mod beta;
-mod binom;
-mod chisq;
-mod count_and_average;
-mod covariance;
-mod devsq;
-mod exponential;
-mod fisher;
-mod gamma;
-mod geomean;
-mod hypegeom;
-mod if_ifs;
-mod log_normal;
-mod normal;
-mod pearson;
-mod phi;
-mod poisson;
-mod standard_dev;
-mod standardize;
-mod t_dist;
-mod variance;
-mod weibull;
-mod z_test;

base/src/functions/statistical/normal.rs

@@ -1,325 +0,0 @@
-use statrs::distribution::{Continuous, ContinuousCDF, Normal, StudentsT};
-
-use crate::expressions::types::CellReferenceIndex;
-use crate::{
-    calc_result::CalcResult, expressions::parser::Node, expressions::token::Error, model::Model,
-};
-
-impl Model {
-    // NORM.DIST(x, mean, standard_dev, cumulative)
-    pub(crate) fn fn_norm_dist(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        if args.len() != 4 {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        let x = match self.get_number_no_bools(&args[0], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-        let mean = match self.get_number_no_bools(&args[1], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-        let std_dev = match self.get_number_no_bools(&args[2], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-        let cumulative = match self.get_boolean(&args[3], cell) {
-            Ok(b) => b,
-            Err(e) => return e,
-        };
-
-        // Excel: standard_dev must be > 0
-        if std_dev <= 0.0 {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "standard_dev must be > 0 in NORM.DIST".to_string(),
-            };
-        }
-
-        let dist = match Normal::new(mean, std_dev) {
-            Ok(d) => d,
-            Err(_) => {
-                return CalcResult::Error {
-                    error: Error::NUM,
-                    origin: cell,
-                    message: "Invalid parameters for NORM.DIST".to_string(),
-                }
-            }
-        };
-
-        let result = if cumulative { dist.cdf(x) } else { dist.pdf(x) };
-
-        if !result.is_finite() {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "Invalid result for NORM.DIST".to_string(),
-            };
-        }
-
-        CalcResult::Number(result)
-    }
-
-    // NORM.INV(probability, mean, standard_dev)
-    pub(crate) fn fn_norm_inv(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        if args.len() != 3 {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        let p = match self.get_number_no_bools(&args[0], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-        let mean = match self.get_number_no_bools(&args[1], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-        let std_dev = match self.get_number_no_bools(&args[2], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-
-        if p <= 0.0 || p >= 1.0 || std_dev <= 0.0 {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "Invalid parameters for NORM.INV".to_string(),
-            };
-        }
-
-        let dist = match Normal::new(mean, std_dev) {
-            Ok(d) => d,
-            Err(_) => {
-                return CalcResult::Error {
-                    error: Error::NUM,
-                    origin: cell,
-                    message: "Invalid parameters for NORM.INV".to_string(),
-                }
-            }
-        };
-
-        let x = dist.inverse_cdf(p);
-
-        if !x.is_finite() {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "Invalid result for NORM.INV".to_string(),
-            };
-        }
-
-        CalcResult::Number(x)
-    }
-
-    // NORM.S.DIST(z, cumulative)
-    pub(crate) fn fn_norm_s_dist(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        if args.len() != 2 {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        let z = match self.get_number_no_bools(&args[0], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-        let cumulative = match self.get_boolean(&args[1], cell) {
-            Ok(b) => b,
-            Err(e) => return e,
-        };
-
-        let dist = match Normal::new(0.0, 1.0) {
-            Ok(d) => d,
-            Err(_) => {
-                return CalcResult::Error {
-                    error: Error::ERROR,
-                    origin: cell,
-                    message: "Failed to construct standard normal distribution".to_string(),
-                }
-            }
-        };
-
-        let result = if cumulative { dist.cdf(z) } else { dist.pdf(z) };
-
-        if !result.is_finite() {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "Invalid result for NORM.S.DIST".to_string(),
-            };
-        }
-
-        CalcResult::Number(result)
-    }
-
-    // NORM.S.INV(probability)
-    pub(crate) fn fn_norm_s_inv(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        if args.len() != 1 {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        let p = match self.get_number_no_bools(&args[0], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-
-        if p <= 0.0 || p >= 1.0 {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "probability must be in (0,1) in NORM.S.INV".to_string(),
-            };
-        }
-
-        let dist = match Normal::new(0.0, 1.0) {
-            Ok(d) => d,
-            Err(_) => {
-                return CalcResult::Error {
-                    error: Error::ERROR,
-                    origin: cell,
-                    message: "Failed to construct standard normal distribution".to_string(),
-                }
-            }
-        };
-
-        let z = dist.inverse_cdf(p);
-
-        if !z.is_finite() {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "Invalid result for NORM.S.INV".to_string(),
-            };
-        }
-
-        CalcResult::Number(z)
-    }
-
-    pub(crate) fn fn_confidence_norm(
-        &mut self,
-        args: &[Node],
-        cell: CellReferenceIndex,
-    ) -> CalcResult {
-        if args.len() != 3 {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        let alpha = match self.get_number_no_bools(&args[0], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-        let std_dev = match self.get_number_no_bools(&args[1], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-        let size = match self.get_number_no_bools(&args[2], cell) {
-            Ok(f) => f.floor(),
-            Err(e) => return e,
-        };
-
-        if alpha <= 0.0 || alpha >= 1.0 || std_dev <= 0.0 {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "Invalid parameters for CONFIDENCE.NORM".to_string(),
-            };
-        }
-        if size < 1.0 {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "Sample size must be at least 1".to_string(),
-            };
-        }
-
-        let normal = match Normal::new(0.0, 1.0) {
-            Ok(d) => d,
-            Err(_) => {
-                return CalcResult::new_error(
-                    Error::ERROR,
-                    cell,
-                    "Failed to construct normal distribution".to_string(),
-                )
-            }
-        };
-
-        let quantile = normal.inverse_cdf(1.0 - alpha / 2.0);
-        if !quantile.is_finite() {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "Invalid quantile for CONFIDENCE.NORM".to_string(),
-            };
-        }
-
-        let margin = quantile * std_dev / size.sqrt();
-        CalcResult::Number(margin)
-    }
-
-    pub(crate) fn fn_confidence_t(
-        &mut self,
-        args: &[Node],
-        cell: CellReferenceIndex,
-    ) -> CalcResult {
-        if args.len() != 3 {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        let alpha = match self.get_number_no_bools(&args[0], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-        let std_dev = match self.get_number_no_bools(&args[1], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-        let size = match self.get_number_no_bools(&args[2], cell) {
-            Ok(f) => f.trunc(),
-            Err(e) => return e,
-        };
-
-        // Domain checks
-        if alpha <= 0.0 || alpha >= 1.0 || std_dev <= 0.0 {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "Invalid parameters for CONFIDENCE.T".to_string(),
-            };
-        }
-
-        // Need at least 2 observations so df = n - 1 > 0
-        if size < 2.0 {
-            return CalcResult::Error {
-                error: Error::DIV,
-                origin: cell,
-                message: "Sample size must be at least 2".to_string(),
-            };
-        }
-
-        let df = size - 1.0;
-
-        let t_dist = match StudentsT::new(0.0, 1.0, df) {
-            Ok(d) => d,
-            Err(_) => {
-                return CalcResult::new_error(
-                    Error::ERROR,
-                    cell,
-                    "Failed to construct Student's t distribution".to_string(),
-                )
-            }
-        };
-
-        // Two-sided CI => use 1 - alpha/2
-        let t_crit = t_dist.inverse_cdf(1.0 - alpha / 2.0);
-        if !t_crit.is_finite() {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "Invalid quantile for CONFIDENCE.T".to_string(),
-            };
-        }
-
-        let margin = t_crit * std_dev / size.sqrt();
-        CalcResult::Number(margin)
-    }
-}

base/src/functions/statistical/pearson.rs

@@ -1,235 +0,0 @@
-use crate::expressions::types::CellReferenceIndex;
-use crate::functions::statistical::chisq::is_same_shape_or_1d;
-use crate::{
-    calc_result::CalcResult, expressions::parser::Node, expressions::token::Error, model::Model,
-};
-
-impl Model {
-    // PEARSON(array1, array2)
-    pub(crate) fn fn_pearson(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        if args.len() != 2 {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        let left_arg = self.evaluate_node_in_context(&args[0], cell);
-        let right_arg = self.evaluate_node_in_context(&args[1], cell);
-
-        let (values_left, values_right) = match (left_arg, right_arg) {
-            (
-                CalcResult::Range {
-                    left: l1,
-                    right: r1,
-                },
-                CalcResult::Range {
-                    left: l2,
-                    right: r2,
-                },
-            ) => {
-                if l1.sheet != l2.sheet {
-                    return CalcResult::new_error(
-                        Error::VALUE,
-                        cell,
-                        "Ranges are in different sheets".to_string(),
-                    );
-                }
-
-                let rows1 = r1.row - l1.row + 1;
-                let cols1 = r1.column - l1.column + 1;
-                let rows2 = r2.row - l2.row + 1;
-                let cols2 = r2.column - l2.column + 1;
-
-                if !is_same_shape_or_1d(rows1, cols1, rows2, cols2) {
-                    return CalcResult::new_error(
-                        Error::VALUE,
-                        cell,
-                        "Ranges must be of the same shape".to_string(),
-                    );
-                }
-
-                let values_left = match self.values_from_range(l1, r1) {
-                    Err(error) => return error,
-                    Ok(v) => v,
-                };
-                let values_right = match self.values_from_range(l2, r2) {
-                    Err(error) => return error,
-                    Ok(v) => v,
-                };
-
-                (values_left, values_right)
-            }
-            (
-                CalcResult::Array(left),
-                CalcResult::Range {
-                    left: l2,
-                    right: r2,
-                },
-            ) => {
-                let rows2 = r2.row - l2.row + 1;
-                let cols2 = r2.column - l2.column + 1;
-
-                let rows1 = left.len() as i32;
-                let cols1 = if rows1 > 0 { left[0].len() as i32 } else { 0 };
-
-                if !is_same_shape_or_1d(rows1, cols1, rows2, cols2) {
-                    return CalcResult::new_error(
-                        Error::VALUE,
-                        cell,
-                        "Array and range must be of the same shape".to_string(),
-                    );
-                }
-
-                let values_left = match self.values_from_array(left) {
-                    Err(error) => {
-                        return CalcResult::new_error(
-                            Error::VALUE,
-                            cell,
-                            format!("Error in first array: {:?}", error),
-                        );
-                    }
-                    Ok(v) => v,
-                };
-                let values_right = match self.values_from_range(l2, r2) {
-                    Err(error) => return error,
-                    Ok(v) => v,
-                };
-
-                (values_left, values_right)
-            }
-            (
-                CalcResult::Range {
-                    left: l1,
-                    right: r1,
-                },
-                CalcResult::Array(right),
-            ) => {
-                let rows1 = r1.row - l1.row + 1;
-                let cols1 = r1.column - l1.column + 1;
-
-                let rows2 = right.len() as i32;
-                let cols2 = if rows2 > 0 { right[0].len() as i32 } else { 0 };
-
-                if !is_same_shape_or_1d(rows1, cols1, rows2, cols2) {
-                    return CalcResult::new_error(
-                        Error::VALUE,
-                        cell,
-                        "Range and array must be of the same shape".to_string(),
-                    );
-                }
-
-                let values_left = match self.values_from_range(l1, r1) {
-                    Err(error) => return error,
-                    Ok(v) => v,
-                };
-                let values_right = match self.values_from_array(right) {
-                    Err(error) => {
-                        return CalcResult::new_error(
-                            Error::VALUE,
-                            cell,
-                            format!("Error in second array: {:?}", error),
-                        );
-                    }
-                    Ok(v) => v,
-                };
-
-                (values_left, values_right)
-            }
-            (CalcResult::Array(left), CalcResult::Array(right)) => {
-                let rows1 = left.len() as i32;
-                let rows2 = right.len() as i32;
-                let cols1 = if rows1 > 0 { left[0].len() as i32 } else { 0 };
-                let cols2 = if rows2 > 0 { right[0].len() as i32 } else { 0 };
-
-                if !is_same_shape_or_1d(rows1, cols1, rows2, cols2) {
-                    return CalcResult::new_error(
-                        Error::VALUE,
-                        cell,
-                        "Arrays must be of the same shape".to_string(),
-                    );
-                }
-
-                let values_left = match self.values_from_array(left) {
-                    Err(error) => {
-                        return CalcResult::new_error(
-                            Error::VALUE,
-                            cell,
-                            format!("Error in first array: {:?}", error),
-                        );
-                    }
-                    Ok(v) => v,
-                };
-                let values_right = match self.values_from_array(right) {
-                    Err(error) => {
-                        return CalcResult::new_error(
-                            Error::VALUE,
-                            cell,
-                            format!("Error in second array: {:?}", error),
-                        );
-                    }
-                    Ok(v) => v,
-                };
-
-                (values_left, values_right)
-            }
-            _ => {
-                return CalcResult::new_error(
-                    Error::VALUE,
-                    cell,
-                    "Both arguments must be ranges or arrays".to_string(),
-                );
-            }
-        };
-
-        // Flatten into (x, y) pairs, skipping non-numeric entries (None)
-        let mut n: f64 = 0.0;
-        let mut sum_x = 0.0;
-        let mut sum_y = 0.0;
-        let mut sum_x2 = 0.0;
-        let mut sum_y2 = 0.0;
-        let mut sum_xy = 0.0;
-
-        let len = values_left.len().min(values_right.len());
-        for i in 0..len {
-            match (values_left[i], values_right[i]) {
-                (Some(x), Some(y)) => {
-                    n += 1.0;
-                    sum_x += x;
-                    sum_y += y;
-                    sum_x2 += x * x;
-                    sum_y2 += y * y;
-                    sum_xy += x * y;
-                }
-                _ => {
-                    // Ignore pairs where at least one side is non-numeric
-                }
-            }
-        }
-
-        if n < 2.0 {
-            return CalcResult::new_error(
-                Error::DIV,
-                cell,
-                "PEARSON requires at least two numeric pairs".to_string(),
-            );
-        }
-
-        // Pearson correlation:
-        // r = [ n*Σxy - (Σx)(Σy) ] / sqrt( [n*Σx² - (Σx)²] [n*Σy² - (Σy)²] )
-        let num = n * sum_xy - sum_x * sum_y;
-        let denom_x = n * sum_x2 - sum_x * sum_x;
-        let denom_y = n * sum_y2 - sum_y * sum_y;
-
-        if denom_x.abs() < 1e-15 || denom_y.abs() < 1e-15 {
-            // Zero variance in at least one series
-            return CalcResult::new_error(
-                Error::DIV,
-                cell,
-                "PEARSON cannot be computed when one series has zero variance".to_string(),
-            );
-        }
-
-        let denom = (denom_x * denom_y).sqrt();
-        let r = num / denom;
-
-        CalcResult::Number(r)
-    }
-}

base/src/functions/statistical/phi.rs

@@ -1,21 +0,0 @@
-use crate::expressions::types::CellReferenceIndex;
-use crate::{calc_result::CalcResult, expressions::parser::Node, model::Model};
-
-impl Model {
-    // PHI(x) = standard normal PDF at x
-    pub(crate) fn fn_phi(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        if args.len() != 1 {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        let x = match self.get_number_no_bools(&args[0], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-
-        // Standard normal PDF: (1 / sqrt(2π)) * exp(-x^2 / 2)
-        let result = (-(x * x) / 2.0).exp() / (2.0 * std::f64::consts::PI).sqrt();
-
-        CalcResult::Number(result)
-    }
-}

base/src/functions/statistical/poisson.rs

@@ -1,94 +0,0 @@
-use statrs::distribution::{Discrete, DiscreteCDF, Poisson};
-
-use crate::expressions::types::CellReferenceIndex;
-use crate::{
-    calc_result::CalcResult, expressions::parser::Node, expressions::token::Error, model::Model,
-};
-
-impl Model {
-    // =POISSON.DIST(x, mean, cumulative)
-    pub(crate) fn fn_poisson_dist(
-        &mut self,
-        args: &[Node],
-        cell: CellReferenceIndex,
-    ) -> CalcResult {
-        if args.len() != 3 {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        // x
-        let x = match self.get_number_no_bools(&args[0], cell) {
-            Ok(f) => f.trunc(),
-            Err(e) => return e,
-        };
-
-        // mean (lambda)
-        let lambda = match self.get_number_no_bools(&args[1], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-
-        let cumulative = match self.get_boolean(&args[2], cell) {
-            Ok(b) => b,
-            Err(e) => return e,
-        };
-
-        if x < 0.0 || lambda < 0.0 {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "Invalid parameters for POISSON.DIST".to_string(),
-            };
-        }
-
-        // Guard against insane k for u64
-        if x < 0.0 || x > (u64::MAX as f64) {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "Invalid parameters for POISSON.DIST".to_string(),
-            };
-        }
-
-        let k = x as u64;
-
-        // Special-case lambda = 0: degenerate distribution at 0
-        if lambda == 0.0 {
-            let result = if cumulative {
-                // For x >= 0, P(X <= x) = 1
-                1.0
-            } else {
-                // P(X = 0) = 1, P(X = k>0) = 0
-                if k == 0 {
-                    1.0
-                } else {
-                    0.0
-                }
-            };
-            return CalcResult::Number(result);
-        }
-
-        let dist = match Poisson::new(lambda) {
-            Ok(d) => d,
-            Err(_) => {
-                return CalcResult::Error {
-                    error: Error::NUM,
-                    origin: cell,
-                    message: "Invalid parameters for POISSON.DIST".to_string(),
-                }
-            }
-        };
-
-        let prob = if cumulative { dist.cdf(k) } else { dist.pmf(k) };
-
-        if !prob.is_finite() {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "Invalid result for POISSON.DIST".to_string(),
-            };
-        }
-
-        CalcResult::Number(prob)
-    }
-}

base/src/functions/statistical/standard_dev.rs

@@ -1,519 +0,0 @@
-use crate::constants::{LAST_COLUMN, LAST_ROW};
-use crate::expressions::parser::ArrayNode;
-use crate::expressions::types::CellReferenceIndex;
-use crate::{
-    calc_result::CalcResult, expressions::parser::Node, expressions::token::Error, model::Model,
-};
-
-impl Model {
-    pub(crate) fn fn_stdev_p(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        if args.is_empty() {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        let mut sum = 0.0;
-        let mut sumsq = 0.0;
-        let mut count: u64 = 0;
-
-        #[inline]
-        fn accumulate(sum: &mut f64, sumsq: &mut f64, count: &mut u64, value: f64) {
-            *sum += value;
-            *sumsq += value * value;
-            *count += 1;
-        }
-
-        for arg in args {
-            match self.evaluate_node_in_context(arg, cell) {
-                CalcResult::Number(value) => {
-                    accumulate(&mut sum, &mut sumsq, &mut count, value);
-                }
-                CalcResult::Range { left, right } => {
-                    if left.sheet != right.sheet {
-                        return CalcResult::new_error(
-                            Error::VALUE,
-                            cell,
-                            "Ranges are in different sheets".to_string(),
-                        );
-                    }
-
-                    let row1 = left.row;
-                    let mut row2 = right.row;
-                    let column1 = left.column;
-                    let mut column2 = right.column;
-
-                    if row1 == 1 && row2 == LAST_ROW {
-                        row2 = match self.workbook.worksheet(left.sheet) {
-                            Ok(s) => s.dimension().max_row,
-                            Err(_) => {
-                                return CalcResult::new_error(
-                                    Error::ERROR,
-                                    cell,
-                                    format!("Invalid worksheet index: '{}'", left.sheet),
-                                );
-                            }
-                        };
-                    }
-                    if column1 == 1 && column2 == LAST_COLUMN {
-                        column2 = match self.workbook.worksheet(left.sheet) {
-                            Ok(s) => s.dimension().max_column,
-                            Err(_) => {
-                                return CalcResult::new_error(
-                                    Error::ERROR,
-                                    cell,
-                                    format!("Invalid worksheet index: '{}'", left.sheet),
-                                );
-                            }
-                        };
-                    }
-
-                    for row in row1..row2 + 1 {
-                        for column in column1..(column2 + 1) {
-                            match self.evaluate_cell(CellReferenceIndex {
-                                sheet: left.sheet,
-                                row,
-                                column,
-                            }) {
-                                CalcResult::Number(value) => {
-                                    accumulate(&mut sum, &mut sumsq, &mut count, value);
-                                }
-                                error @ CalcResult::Error { .. } => return error,
-                                _ => {
-                                    // ignore non-numeric
-                                }
-                            }
-                        }
-                    }
-                }
-                CalcResult::Array(array) => {
-                    for row in array {
-                        for value in row {
-                            match value {
-                                ArrayNode::Number(value) => {
-                                    accumulate(&mut sum, &mut sumsq, &mut count, value);
-                                }
-                                ArrayNode::Error(error) => {
-                                    return CalcResult::Error {
-                                        error,
-                                        origin: cell,
-                                        message: "Error in array".to_string(),
-                                    }
-                                }
-                                _ => {
-                                    // ignore non-numeric
-                                }
-                            }
-                        }
-                    }
-                }
-                error @ CalcResult::Error { .. } => return error,
-                _ => {
-                    // ignore non-numeric
-                }
-            }
-        }
-
-        if count == 0 {
-            return CalcResult::new_error(
-                Error::DIV,
-                cell,
-                "STDEV.P with no numeric data".to_string(),
-            );
-        }
-
-        let n = count as f64;
-        let mut var = (sumsq - (sum * sum) / n) / n;
-
-        // clamp tiny negatives from FP noise
-        if var < 0.0 && var > -1e-12 {
-            var = 0.0;
-        }
-
-        CalcResult::Number(var.sqrt())
-    }
-
-    pub(crate) fn fn_stdev_s(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        if args.is_empty() {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        let mut sum = 0.0;
-        let mut sumsq = 0.0;
-        let mut count: u64 = 0;
-
-        #[inline]
-        fn accumulate(sum: &mut f64, sumsq: &mut f64, count: &mut u64, value: f64) {
-            *sum += value;
-            *sumsq += value * value;
-            *count += 1;
-        }
-
-        for arg in args {
-            match self.evaluate_node_in_context(arg, cell) {
-                CalcResult::Number(value) => {
-                    accumulate(&mut sum, &mut sumsq, &mut count, value);
-                }
-                CalcResult::Range { left, right } => {
-                    if left.sheet != right.sheet {
-                        return CalcResult::new_error(
-                            Error::VALUE,
-                            cell,
-                            "Ranges are in different sheets".to_string(),
-                        );
-                    }
-
-                    let row1 = left.row;
-                    let mut row2 = right.row;
-                    let column1 = left.column;
-                    let mut column2 = right.column;
-
-                    if row1 == 1 && row2 == LAST_ROW {
-                        row2 = match self.workbook.worksheet(left.sheet) {
-                            Ok(s) => s.dimension().max_row,
-                            Err(_) => {
-                                return CalcResult::new_error(
-                                    Error::ERROR,
-                                    cell,
-                                    format!("Invalid worksheet index: '{}'", left.sheet),
-                                );
-                            }
-                        };
-                    }
-                    if column1 == 1 && column2 == LAST_COLUMN {
-                        column2 = match self.workbook.worksheet(left.sheet) {
-                            Ok(s) => s.dimension().max_column,
-                            Err(_) => {
-                                return CalcResult::new_error(
-                                    Error::ERROR,
-                                    cell,
-                                    format!("Invalid worksheet index: '{}'", left.sheet),
-                                );
-                            }
-                        };
-                    }
-
-                    for row in row1..row2 + 1 {
-                        for column in column1..(column2 + 1) {
-                            match self.evaluate_cell(CellReferenceIndex {
-                                sheet: left.sheet,
-                                row,
-                                column,
-                            }) {
-                                CalcResult::Number(value) => {
-                                    accumulate(&mut sum, &mut sumsq, &mut count, value);
-                                }
-                                error @ CalcResult::Error { .. } => return error,
-                                _ => {
-                                    // ignore non-numeric
-                                }
-                            }
-                        }
-                    }
-                }
-                CalcResult::Array(array) => {
-                    for row in array {
-                        for value in row {
-                            match value {
-                                ArrayNode::Number(value) => {
-                                    accumulate(&mut sum, &mut sumsq, &mut count, value);
-                                }
-                                ArrayNode::Error(error) => {
-                                    return CalcResult::Error {
-                                        error,
-                                        origin: cell,
-                                        message: "Error in array".to_string(),
-                                    }
-                                }
-                                _ => {
-                                    // ignore non-numeric
-                                }
-                            }
-                        }
-                    }
-                }
-                error @ CalcResult::Error { .. } => return error,
-                _ => {
-                    // ignore non-numeric
-                }
-            }
-        }
-
-        if count <= 1 {
-            return CalcResult::new_error(
-                Error::DIV,
-                cell,
-                "STDEV.S requires at least two numeric values".to_string(),
-            );
-        }
-
-        let n = count as f64;
-        let mut var = (sumsq - (sum * sum) / n) / (n - 1.0);
-
-        if var < 0.0 && var > -1e-12 {
-            var = 0.0;
-        }
-
-        CalcResult::Number(var.sqrt())
-    }
-
-    pub(crate) fn fn_stdeva(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        if args.is_empty() {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        let mut sum = 0.0;
-        let mut sumsq = 0.0;
-        let mut count: u64 = 0;
-
-        #[inline]
-        fn accumulate(sum: &mut f64, sumsq: &mut f64, count: &mut u64, value: f64) {
-            *sum += value;
-            *sumsq += value * value;
-            *count += 1;
-        }
-
-        for arg in args {
-            match self.evaluate_node_in_context(arg, cell) {
-                CalcResult::Number(value) => {
-                    accumulate(&mut sum, &mut sumsq, &mut count, value);
-                }
-                CalcResult::Range { left, right } => {
-                    if left.sheet != right.sheet {
-                        return CalcResult::new_error(
-                            Error::VALUE,
-                            cell,
-                            "Ranges are in different sheets".to_string(),
-                        );
-                    }
-
-                    let row1 = left.row;
-                    let mut row2 = right.row;
-                    let column1 = left.column;
-                    let mut column2 = right.column;
-
-                    if row1 == 1 && row2 == LAST_ROW {
-                        row2 = match self.workbook.worksheet(left.sheet) {
-                            Ok(s) => s.dimension().max_row,
-                            Err(_) => {
-                                return CalcResult::new_error(
-                                    Error::ERROR,
-                                    cell,
-                                    format!("Invalid worksheet index: '{}'", left.sheet),
-                                );
-                            }
-                        };
-                    }
-                    if column1 == 1 && column2 == LAST_COLUMN {
-                        column2 = match self.workbook.worksheet(left.sheet) {
-                            Ok(s) => s.dimension().max_column,
-                            Err(_) => {
-                                return CalcResult::new_error(
-                                    Error::ERROR,
-                                    cell,
-                                    format!("Invalid worksheet index: '{}'", left.sheet),
-                                );
-                            }
-                        };
-                    }
-
-                    for row in row1..row2 + 1 {
-                        for column in column1..(column2 + 1) {
-                            match self.evaluate_cell(CellReferenceIndex {
-                                sheet: left.sheet,
-                                row,
-                                column,
-                            }) {
-                                CalcResult::Number(value) => {
-                                    accumulate(&mut sum, &mut sumsq, &mut count, value);
-                                }
-                                CalcResult::String(_) => {
-                                    accumulate(&mut sum, &mut sumsq, &mut count, 0.0);
-                                }
-                                CalcResult::Boolean(value) => {
-                                    let val = if value { 1.0 } else { 0.0 };
-                                    accumulate(&mut sum, &mut sumsq, &mut count, val);
-                                }
-                                error @ CalcResult::Error { .. } => return error,
-                                _ => {
-                                    // ignore non-numeric for now
-                                }
-                            }
-                        }
-                    }
-                }
-                CalcResult::Array(array) => {
-                    for row in array {
-                        for value in row {
-                            match value {
-                                ArrayNode::Number(value) => {
-                                    accumulate(&mut sum, &mut sumsq, &mut count, value);
-                                }
-                                ArrayNode::Error(error) => {
-                                    return CalcResult::Error {
-                                        error,
-                                        origin: cell,
-                                        message: "Error in array".to_string(),
-                                    }
-                                }
-                                _ => {
-                                    // ignore non-numeric for now
-                                }
-                            }
-                        }
-                    }
-                }
-                error @ CalcResult::Error { .. } => return error,
-                _ => {
-                    // ignore non-numeric for now
-                }
-            }
-        }
-
-        if count <= 1 {
-            return CalcResult::new_error(
-                Error::DIV,
-                cell,
-                "STDEVA requires at least two numeric values".to_string(),
-            );
-        }
-
-        let n = count as f64;
-        let mut var = (sumsq - (sum * sum) / n) / (n - 1.0);
-
-        if var < 0.0 && var > -1e-12 {
-            var = 0.0;
-        }
-
-        CalcResult::Number(var.sqrt())
-    }
-
-    pub(crate) fn fn_stdevpa(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        if args.is_empty() {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        let mut sum = 0.0;
-        let mut sumsq = 0.0;
-        let mut count: u64 = 0;
-
-        #[inline]
-        fn accumulate(sum: &mut f64, sumsq: &mut f64, count: &mut u64, value: f64) {
-            *sum += value;
-            *sumsq += value * value;
-            *count += 1;
-        }
-
-        for arg in args {
-            match self.evaluate_node_in_context(arg, cell) {
-                CalcResult::Number(value) => {
-                    accumulate(&mut sum, &mut sumsq, &mut count, value);
-                }
-                CalcResult::Range { left, right } => {
-                    if left.sheet != right.sheet {
-                        return CalcResult::new_error(
-                            Error::VALUE,
-                            cell,
-                            "Ranges are in different sheets".to_string(),
-                        );
-                    }
-
-                    let row1 = left.row;
-                    let mut row2 = right.row;
-                    let column1 = left.column;
-                    let mut column2 = right.column;
-
-                    if row1 == 1 && row2 == LAST_ROW {
-                        row2 = match self.workbook.worksheet(left.sheet) {
-                            Ok(s) => s.dimension().max_row,
-                            Err(_) => {
-                                return CalcResult::new_error(
-                                    Error::ERROR,
-                                    cell,
-                                    format!("Invalid worksheet index: '{}'", left.sheet),
-                                );
-                            }
-                        };
-                    }
-                    if column1 == 1 && column2 == LAST_COLUMN {
-                        column2 = match self.workbook.worksheet(left.sheet) {
-                            Ok(s) => s.dimension().max_column,
-                            Err(_) => {
-                                return CalcResult::new_error(
-                                    Error::ERROR,
-                                    cell,
-                                    format!("Invalid worksheet index: '{}'", left.sheet),
-                                );
-                            }
-                        };
-                    }
-
-                    for row in row1..row2 + 1 {
-                        for column in column1..(column2 + 1) {
-                            match self.evaluate_cell(CellReferenceIndex {
-                                sheet: left.sheet,
-                                row,
-                                column,
-                            }) {
-                                CalcResult::Number(value) => {
-                                    accumulate(&mut sum, &mut sumsq, &mut count, value);
-                                }
-                                CalcResult::String(_) => {
-                                    accumulate(&mut sum, &mut sumsq, &mut count, 0.0);
-                                }
-                                CalcResult::Boolean(value) => {
-                                    let val = if value { 1.0 } else { 0.0 };
-                                    accumulate(&mut sum, &mut sumsq, &mut count, val);
-                                }
-                                error @ CalcResult::Error { .. } => return error,
-                                _ => {
-                                    // ignore non-numeric for now
-                                }
-                            }
-                        }
-                    }
-                }
-                CalcResult::Array(array) => {
-                    for row in array {
-                        for value in row {
-                            match value {
-                                ArrayNode::Number(value) => {
-                                    accumulate(&mut sum, &mut sumsq, &mut count, value);
-                                }
-                                ArrayNode::Error(error) => {
-                                    return CalcResult::Error {
-                                        error,
-                                        origin: cell,
-                                        message: "Error in array".to_string(),
-                                    }
-                                }
-                                _ => {
-                                    // ignore non-numeric for now
-                                }
-                            }
-                        }
-                    }
-                }
-                error @ CalcResult::Error { .. } => return error,
-                _ => {
-                    // ignore non-numeric for now
-                }
-            }
-        }
-
-        if count == 0 {
-            return CalcResult::new_error(
-                Error::DIV,
-                cell,
-                "STDEVPA with no numeric data".to_string(),
-            );
-        }
-
-        let n = count as f64;
-        let mut var = (sumsq - (sum * sum) / n) / n;
-
-        if var < 0.0 && var > -1e-12 {
-            var = 0.0;
-        }
-
-        CalcResult::Number(var.sqrt())
-    }
-}

base/src/functions/statistical/standardize.rs

@@ -1,38 +0,0 @@
-use crate::expressions::types::CellReferenceIndex;
-use crate::{
-    calc_result::CalcResult, expressions::parser::Node, expressions::token::Error, model::Model,
-};
-
-impl Model {
-    pub(crate) fn fn_standardize(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        // STANDARDIZE(x, mean, standard_dev)
-        if args.len() != 3 {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        let x = match self.get_number_no_bools(&args[0], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-        let mean = match self.get_number_no_bools(&args[1], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-        let std_dev = match self.get_number_no_bools(&args[2], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-
-        if std_dev <= 0.0 {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "standard_dev must be > 0 in STANDARDIZE".to_string(),
-            };
-        }
-
-        let z = (x - mean) / std_dev;
-
-        CalcResult::Number(z)
-    }
-}

base/src/functions/statistical/t_dist.rs

@@ -1,588 +0,0 @@
-use statrs::distribution::{Continuous, ContinuousCDF, StudentsT};
-
-use crate::expressions::types::CellReferenceIndex;
-use crate::{
-    calc_result::CalcResult, expressions::parser::Node, expressions::token::Error, model::Model,
-};
-
-fn mean(xs: &[f64]) -> f64 {
-    let n = xs.len();
-    if n == 0 {
-        return 0.0;
-    }
-    let mut s = 0.0;
-    for &x in xs {
-        s += x;
-    }
-    s / (n as f64)
-}
-
-fn sample_var(xs: &[f64]) -> f64 {
-    let n = xs.len();
-    if n < 2 {
-        return 0.0;
-    }
-    let m = mean(xs);
-    let mut s = 0.0;
-    for &x in xs {
-        let d = x - m;
-        s += d * d;
-    }
-    s / ((n - 1) as f64)
-}
-
-enum TTestType {
-    Paired,
-    TwoSampleEqualVar,
-    TwoSampleUnequalVar,
-}
-
-enum TTestTails {
-    OneTailed,
-    TwoTailed,
-}
-
-impl Model {
-    // T.DIST(x, deg_freedom, cumulative)
-    pub(crate) fn fn_t_dist(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        if args.len() != 3 {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        let x = match self.get_number_no_bools(&args[0], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-
-        let df = match self.get_number_no_bools(&args[1], cell) {
-            Ok(f) => f.trunc(),
-            Err(e) => return e,
-        };
-
-        let cumulative = match self.get_boolean(&args[2], cell) {
-            Ok(b) => b,
-            Err(e) => return e,
-        };
-
-        if df < 1.0 {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "deg_freedom must be >= 1 in T.DIST".to_string(),
-            };
-        }
-
-        let dist = match StudentsT::new(0.0, 1.0, df) {
-            Ok(d) => d,
-            Err(_) => {
-                return CalcResult::Error {
-                    error: Error::NUM,
-                    origin: cell,
-                    message: "Invalid parameters for T.DIST".to_string(),
-                }
-            }
-        };
-
-        let result = if cumulative { dist.cdf(x) } else { dist.pdf(x) };
-
-        if !result.is_finite() {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "Invalid result for T.DIST".to_string(),
-            };
-        }
-
-        CalcResult::Number(result)
-    }
-
-    // T.DIST.2T(x, deg_freedom)
-    pub(crate) fn fn_t_dist_2t(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        if args.len() != 2 {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        let x = match self.get_number_no_bools(&args[0], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-
-        let df = match self.get_number_no_bools(&args[1], cell) {
-            Ok(f) => f.trunc(),
-            Err(e) => return e,
-        };
-
-        if x < 0.0 {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "x must be >= 0 in T.DIST.2T".to_string(),
-            };
-        }
-
-        if df < 1.0 {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "deg_freedom must be >= 1 in T.DIST.2T".to_string(),
-            };
-        }
-
-        let dist = match StudentsT::new(0.0, 1.0, df) {
-            Ok(d) => d,
-            Err(_) => {
-                return CalcResult::Error {
-                    error: Error::NUM,
-                    origin: cell,
-                    message: "Invalid parameters for T.DIST.2T".to_string(),
-                }
-            }
-        };
-
-        let upper_tail = 1.0 - dist.cdf(x);
-        let mut result = 2.0 * upper_tail;
-
-        result = result.clamp(0.0, 1.0);
-
-        if !result.is_finite() {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "Invalid result for T.DIST.2T".to_string(),
-            };
-        }
-
-        CalcResult::Number(result)
-    }
-
-    // T.DIST.RT(x, deg_freedom)
-    pub(crate) fn fn_t_dist_rt(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        if args.len() != 2 {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        let x = match self.get_number_no_bools(&args[0], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-
-        let df = match self.get_number_no_bools(&args[1], cell) {
-            Ok(f) => f.trunc(),
-            Err(e) => return e,
-        };
-
-        if df < 1.0 {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "deg_freedom must be >= 1 in T.DIST.RT".to_string(),
-            };
-        }
-
-        let dist = match StudentsT::new(0.0, 1.0, df) {
-            Ok(d) => d,
-            Err(_) => {
-                return CalcResult::Error {
-                    error: Error::NUM,
-                    origin: cell,
-                    message: "Invalid parameters for T.DIST.RT".to_string(),
-                }
-            }
-        };
-
-        let result = 1.0 - dist.cdf(x);
-
-        if !result.is_finite() || result < 0.0 {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "Invalid result for T.DIST.RT".to_string(),
-            };
-        }
-
-        CalcResult::Number(result)
-    }
-
-    // T.INV(probability, deg_freedom)
-    pub(crate) fn fn_t_inv(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        if args.len() != 2 {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        let p = match self.get_number_no_bools(&args[0], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-
-        let df = match self.get_number_no_bools(&args[1], cell) {
-            Ok(f) => f.trunc(),
-            Err(e) => return e,
-        };
-
-        if p <= 0.0 || p >= 1.0 || df < 1.0 {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "Invalid parameters for T.INV".to_string(),
-            };
-        }
-
-        let dist = match StudentsT::new(0.0, 1.0, df) {
-            Ok(d) => d,
-            Err(_) => {
-                return CalcResult::Error {
-                    error: Error::NUM,
-                    origin: cell,
-                    message: "Invalid parameters for T.INV".to_string(),
-                }
-            }
-        };
-
-        let x = dist.inverse_cdf(p);
-
-        if !x.is_finite() {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "Invalid result for T.INV".to_string(),
-            };
-        }
-
-        CalcResult::Number(x)
-    }
-
-    // T.INV.2T(probability, deg_freedom)
-    pub(crate) fn fn_t_inv_2t(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        if args.len() != 2 {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        let p = match self.get_number_no_bools(&args[0], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-
-        let df = match self.get_number_no_bools(&args[1], cell) {
-            Ok(f) => f.trunc(),
-            Err(e) => return e,
-        };
-
-        if p <= 0.0 || p > 1.0 || df < 1.0 {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "Invalid parameters for T.INV.2T".to_string(),
-            };
-        }
-
-        let dist = match StudentsT::new(0.0, 1.0, df) {
-            Ok(d) => d,
-            Err(_) => {
-                return CalcResult::Error {
-                    error: Error::NUM,
-                    origin: cell,
-                    message: "Invalid parameters for T.INV.2T".to_string(),
-                }
-            }
-        };
-
-        // Two-sided: F(x) = 1 - p/2
-        let target_cdf = 1.0 - p / 2.0;
-        let x = dist.inverse_cdf(target_cdf);
-
-        if !x.is_finite() {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "Invalid result for T.INV.2T".to_string(),
-            };
-        }
-
-        CalcResult::Number(x.abs())
-    }
-
-    // T.TEST(array1, array2, tails, type)
-    pub(crate) fn fn_t_test(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        if args.len() != 4 {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        let values1_opts = match self.evaluate_node_in_context(&args[0], cell) {
-            CalcResult::Range { left, right } => match self.values_from_range(left, right) {
-                Ok(v) => v,
-                Err(error) => return error,
-            },
-            CalcResult::Array(a) => match self.values_from_array(a) {
-                Ok(v) => v,
-                Err(error) => {
-                    return CalcResult::new_error(
-                        Error::VALUE,
-                        cell,
-                        format!("Error in first array: {:?}", error),
-                    );
-                }
-            },
-            _ => {
-                return CalcResult::new_error(
-                    Error::VALUE,
-                    cell,
-                    "First argument must be a range or array".to_string(),
-                );
-            }
-        };
-
-        let values2_opts = match self.evaluate_node_in_context(&args[1], cell) {
-            CalcResult::Range { left, right } => match self.values_from_range(left, right) {
-                Ok(v) => v,
-                Err(error) => return error,
-            },
-            CalcResult::Array(a) => match self.values_from_array(a) {
-                Ok(v) => v,
-                Err(error) => {
-                    return CalcResult::new_error(
-                        Error::VALUE,
-                        cell,
-                        format!("Error in second array: {:?}", error),
-                    );
-                }
-            },
-            _ => {
-                return CalcResult::new_error(
-                    Error::VALUE,
-                    cell,
-                    "Second argument must be a range or array".to_string(),
-                );
-            }
-        };
-
-        let tails = match self.get_number(&args[2], cell) {
-            Ok(f) => {
-                let tf = f.trunc();
-                if tf == 1.0 {
-                    TTestTails::OneTailed
-                } else if tf == 2.0 {
-                    TTestTails::TwoTailed
-                } else {
-                    return CalcResult::new_error(
-                        Error::NUM,
-                        cell,
-                        "tails must be 1 or 2".to_string(),
-                    );
-                }
-            }
-            Err(e) => return e,
-        };
-        let test_type = match self.get_number(&args[3], cell) {
-            Ok(f) => {
-                let tf = f.trunc();
-                match tf {
-                    1.0 => TTestType::Paired,
-                    2.0 => TTestType::TwoSampleEqualVar,
-                    3.0 => TTestType::TwoSampleUnequalVar,
-                    _ => {
-                        return CalcResult::new_error(
-                            Error::NUM,
-                            cell,
-                            "type must be 1, 2, or 3".to_string(),
-                        );
-                    }
-                }
-            }
-            Err(e) => return e,
-        };
-
-        let (values1, values2): (Vec<f64>, Vec<f64>) = if matches!(test_type, TTestType::Paired) {
-            values1_opts
-                .into_iter()
-                .zip(values2_opts)
-                .filter_map(|(o1, o2)| match (o1, o2) {
-                    (Some(v1), Some(v2)) => Some((v1, v2)),
-                    _ => None, // skip if either is None
-                })
-                .unzip()
-        } else {
-            // keep only numeric entries, ignore non-numeric (Option::None)
-            let v1: Vec<f64> = values1_opts.into_iter().flatten().collect();
-            let v2: Vec<f64> = values2_opts.into_iter().flatten().collect();
-            (v1, v2)
-        };
-
-        let n1 = values1.len();
-        let n2 = values2.len();
-
-        if n1 == 0 || n2 == 0 {
-            return CalcResult::new_error(
-                Error::DIV,
-                cell,
-                "T.TEST requires non-empty samples".to_string(),
-            );
-        }
-
-        let (t_stat, df) = match test_type {
-            TTestType::Paired => {
-                if n1 != n2 {
-                    return CalcResult::new_error(
-                        Error::NA,
-                        cell,
-                        "For paired T.TEST, both samples must have the same length".to_string(),
-                    );
-                }
-                if n1 < 2 {
-                    return CalcResult::new_error(
-                        Error::DIV,
-                        cell,
-                        "Paired T.TEST requires at least two pairs".to_string(),
-                    );
-                }
-
-                let mut diffs = Vec::with_capacity(n1);
-                for i in 0..n1 {
-                    diffs.push(values1[i] - values2[i]);
-                }
-
-                let nd = diffs.len();
-                let md = mean(&diffs);
-                let vd = sample_var(&diffs);
-                if vd <= 0.0 {
-                    return CalcResult::new_error(
-                        Error::DIV,
-                        cell,
-                        "Zero variance in paired T.TEST".to_string(),
-                    );
-                }
-                let sd = vd.sqrt();
-                let t_stat = md / (sd / (nd as f64).sqrt());
-                let df = (nd - 1) as f64;
-                (t_stat, df)
-            }
-
-            // 2: two-sample, equal variance (homoscedastic)
-            TTestType::TwoSampleEqualVar => {
-                if n1 < 2 || n2 < 2 {
-                    return CalcResult::new_error(
-                        Error::DIV,
-                        cell,
-                        "Two-sample T.TEST type 2 requires at least two values in each sample"
-                            .to_string(),
-                    );
-                }
-
-                let m1 = mean(&values1);
-                let m2 = mean(&values2);
-                let v1 = sample_var(&values1);
-                let v2 = sample_var(&values2);
-
-                let df_i = (n1 + n2 - 2) as i32;
-                if df_i <= 0 {
-                    return CalcResult::new_error(
-                        Error::DIV,
-                        cell,
-                        "Degrees of freedom must be positive in T.TEST type 2".to_string(),
-                    );
-                }
-                let df = df_i as f64;
-
-                let sp2 = (((n1 - 1) as f64) * v1 + ((n2 - 1) as f64) * v2) / df; // pooled variance
-
-                if sp2 <= 0.0 {
-                    return CalcResult::new_error(
-                        Error::DIV,
-                        cell,
-                        "Zero pooled variance in T.TEST type 2".to_string(),
-                    );
-                }
-
-                let denom = (sp2 * (1.0 / (n1 as f64) + 1.0 / (n2 as f64))).sqrt();
-                if denom == 0.0 {
-                    return CalcResult::new_error(
-                        Error::DIV,
-                        cell,
-                        "Zero denominator in T.TEST type 2".to_string(),
-                    );
-                }
-
-                let t_stat = (m1 - m2) / denom;
-                (t_stat, df)
-            }
-
-            // two-sample, unequal variance (Welch)
-            TTestType::TwoSampleUnequalVar => {
-                if n1 < 2 || n2 < 2 {
-                    return CalcResult::new_error(
-                        Error::DIV,
-                        cell,
-                        "Two-sample T.TEST type 3 requires at least two values in each sample"
-                            .to_string(),
-                    );
-                }
-
-                let m1 = mean(&values1);
-                let m2 = mean(&values2);
-                let v1 = sample_var(&values1);
-                let v2 = sample_var(&values2);
-
-                let s1n = v1 / (n1 as f64);
-                let s2n = v2 / (n2 as f64);
-                let denom = (s1n + s2n).sqrt();
-                if denom == 0.0 {
-                    return CalcResult::new_error(
-                        Error::DIV,
-                        cell,
-                        "Zero denominator in T.TEST type 3".to_string(),
-                    );
-                }
-
-                let t_stat = (m1 - m2) / denom;
-
-                let num_df = (s1n + s2n).powi(2);
-                let den_df = (s1n * s1n) / ((n1 - 1) as f64) + (s2n * s2n) / ((n2 - 1) as f64);
-                if den_df == 0.0 {
-                    return CalcResult::new_error(
-                        Error::DIV,
-                        cell,
-                        "Invalid degrees of freedom in T.TEST type 3".to_string(),
-                    );
-                }
-                let df = num_df / den_df;
-                (t_stat, df)
-            }
-        };
-
-        if df <= 0.0 {
-            return CalcResult::new_error(
-                Error::DIV,
-                cell,
-                "Degrees of freedom must be positive in T.TEST".to_string(),
-            );
-        }
-
-        let dist = match StudentsT::new(0.0, 1.0, df) {
-            Ok(d) => d,
-            Err(_) => {
-                return CalcResult::new_error(
-                    Error::NUM,
-                    cell,
-                    "Invalid parameters for Student's t distribution".to_string(),
-                );
-            }
-        };
-
-        let t_abs = t_stat.abs();
-        let cdf = dist.cdf(t_abs);
-
-        let mut p = match tails {
-            TTestTails::OneTailed => 1.0 - cdf,
-            TTestTails::TwoTailed => 2.0 * (1.0 - cdf),
-        };
-
-        // clamp tiny fp noise
-        if p < 0.0 && p > -1e-15 {
-            p = 0.0;
-        }
-        if p > 1.0 && p < 1.0 + 1e-15 {
-            p = 1.0;
-        }
-
-        CalcResult::Number(p)
-    }
-}

base/src/functions/statistical/variance.rs

@@ -1,518 +0,0 @@
-use crate::constants::{LAST_COLUMN, LAST_ROW};
-use crate::expressions::parser::ArrayNode;
-use crate::expressions::types::CellReferenceIndex;
-use crate::{
-    calc_result::CalcResult, expressions::parser::Node, expressions::token::Error, model::Model,
-};
-
-impl Model {
-    pub(crate) fn fn_var_p(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        if args.is_empty() {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        let mut sum = 0.0;
-        let mut sumsq = 0.0;
-        let mut count: u64 = 0;
-
-        #[inline]
-        fn accumulate(sum: &mut f64, sumsq: &mut f64, count: &mut u64, value: f64) {
-            *sum += value;
-            *sumsq += value * value;
-            *count += 1;
-        }
-
-        for arg in args {
-            match self.evaluate_node_in_context(arg, cell) {
-                CalcResult::Number(value) => {
-                    accumulate(&mut sum, &mut sumsq, &mut count, value);
-                }
-                CalcResult::Range { left, right } => {
-                    if left.sheet != right.sheet {
-                        return CalcResult::new_error(
-                            Error::VALUE,
-                            cell,
-                            "Ranges are in different sheets".to_string(),
-                        );
-                    }
-
-                    let row1 = left.row;
-                    let mut row2 = right.row;
-                    let column1 = left.column;
-                    let mut column2 = right.column;
-
-                    if row1 == 1 && row2 == LAST_ROW {
-                        row2 = match self.workbook.worksheet(left.sheet) {
-                            Ok(s) => s.dimension().max_row,
-                            Err(_) => {
-                                return CalcResult::new_error(
-                                    Error::ERROR,
-                                    cell,
-                                    format!("Invalid worksheet index: '{}'", left.sheet),
-                                );
-                            }
-                        };
-                    }
-                    if column1 == 1 && column2 == LAST_COLUMN {
-                        column2 = match self.workbook.worksheet(left.sheet) {
-                            Ok(s) => s.dimension().max_column,
-                            Err(_) => {
-                                return CalcResult::new_error(
-                                    Error::ERROR,
-                                    cell,
-                                    format!("Invalid worksheet index: '{}'", left.sheet),
-                                );
-                            }
-                        };
-                    }
-
-                    for row in row1..row2 + 1 {
-                        for column in column1..(column2 + 1) {
-                            match self.evaluate_cell(CellReferenceIndex {
-                                sheet: left.sheet,
-                                row,
-                                column,
-                            }) {
-                                CalcResult::Number(value) => {
-                                    accumulate(&mut sum, &mut sumsq, &mut count, value);
-                                }
-                                error @ CalcResult::Error { .. } => return error,
-                                _ => {
-                                    // ignore non-numeric
-                                }
-                            }
-                        }
-                    }
-                }
-                CalcResult::Array(array) => {
-                    for row in array {
-                        for value in row {
-                            match value {
-                                ArrayNode::Number(value) => {
-                                    accumulate(&mut sum, &mut sumsq, &mut count, value);
-                                }
-                                ArrayNode::Error(error) => {
-                                    return CalcResult::Error {
-                                        error,
-                                        origin: cell,
-                                        message: "Error in array".to_string(),
-                                    }
-                                }
-                                _ => {
-                                    // ignore non-numeric
-                                }
-                            }
-                        }
-                    }
-                }
-                error @ CalcResult::Error { .. } => return error,
-                _ => {
-                    // ignore non-numeric
-                }
-            }
-        }
-
-        if count == 0 {
-            return CalcResult::new_error(
-                Error::DIV,
-                cell,
-                "VAR.P with no numeric data".to_string(),
-            );
-        }
-
-        let n = count as f64;
-        let mut var = (sumsq - (sum * sum) / n) / n;
-
-        if var < 0.0 && var > -1e-12 {
-            var = 0.0;
-        }
-
-        CalcResult::Number(var)
-    }
-
-    pub(crate) fn fn_var_s(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        if args.is_empty() {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        let mut sum = 0.0;
-        let mut sumsq = 0.0;
-        let mut count: u64 = 0;
-
-        #[inline]
-        fn accumulate(sum: &mut f64, sumsq: &mut f64, count: &mut u64, value: f64) {
-            *sum += value;
-            *sumsq += value * value;
-            *count += 1;
-        }
-
-        for arg in args {
-            match self.evaluate_node_in_context(arg, cell) {
-                CalcResult::Number(value) => {
-                    accumulate(&mut sum, &mut sumsq, &mut count, value);
-                }
-                CalcResult::Range { left, right } => {
-                    if left.sheet != right.sheet {
-                        return CalcResult::new_error(
-                            Error::VALUE,
-                            cell,
-                            "Ranges are in different sheets".to_string(),
-                        );
-                    }
-
-                    let row1 = left.row;
-                    let mut row2 = right.row;
-                    let column1 = left.column;
-                    let mut column2 = right.column;
-
-                    if row1 == 1 && row2 == LAST_ROW {
-                        row2 = match self.workbook.worksheet(left.sheet) {
-                            Ok(s) => s.dimension().max_row,
-                            Err(_) => {
-                                return CalcResult::new_error(
-                                    Error::ERROR,
-                                    cell,
-                                    format!("Invalid worksheet index: '{}'", left.sheet),
-                                );
-                            }
-                        };
-                    }
-                    if column1 == 1 && column2 == LAST_COLUMN {
-                        column2 = match self.workbook.worksheet(left.sheet) {
-                            Ok(s) => s.dimension().max_column,
-                            Err(_) => {
-                                return CalcResult::new_error(
-                                    Error::ERROR,
-                                    cell,
-                                    format!("Invalid worksheet index: '{}'", left.sheet),
-                                );
-                            }
-                        };
-                    }
-
-                    for row in row1..row2 + 1 {
-                        for column in column1..(column2 + 1) {
-                            match self.evaluate_cell(CellReferenceIndex {
-                                sheet: left.sheet,
-                                row,
-                                column,
-                            }) {
-                                CalcResult::Number(value) => {
-                                    accumulate(&mut sum, &mut sumsq, &mut count, value);
-                                }
-                                error @ CalcResult::Error { .. } => return error,
-                                _ => {
-                                    // ignore non-numeric
-                                }
-                            }
-                        }
-                    }
-                }
-                CalcResult::Array(array) => {
-                    for row in array {
-                        for value in row {
-                            match value {
-                                ArrayNode::Number(value) => {
-                                    accumulate(&mut sum, &mut sumsq, &mut count, value);
-                                }
-                                ArrayNode::Error(error) => {
-                                    return CalcResult::Error {
-                                        error,
-                                        origin: cell,
-                                        message: "Error in array".to_string(),
-                                    }
-                                }
-                                _ => {
-                                    // ignore non-numeric
-                                }
-                            }
-                        }
-                    }
-                }
-                error @ CalcResult::Error { .. } => return error,
-                _ => {
-                    // ignore non-numeric
-                }
-            }
-        }
-
-        if count <= 1 {
-            return CalcResult::new_error(
-                Error::DIV,
-                cell,
-                "VAR.S requires at least two numeric values".to_string(),
-            );
-        }
-
-        let n = count as f64;
-        let mut var = (sumsq - (sum * sum) / n) / (n - 1.0);
-
-        if var < 0.0 && var > -1e-12 {
-            var = 0.0;
-        }
-
-        CalcResult::Number(var)
-    }
-
-    pub(crate) fn fn_vara(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        if args.is_empty() {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        let mut sum = 0.0;
-        let mut sumsq = 0.0;
-        let mut count: u64 = 0;
-
-        #[inline]
-        fn accumulate(sum: &mut f64, sumsq: &mut f64, count: &mut u64, value: f64) {
-            *sum += value;
-            *sumsq += value * value;
-            *count += 1;
-        }
-
-        for arg in args {
-            match self.evaluate_node_in_context(arg, cell) {
-                CalcResult::Number(value) => {
-                    accumulate(&mut sum, &mut sumsq, &mut count, value);
-                }
-                CalcResult::Range { left, right } => {
-                    if left.sheet != right.sheet {
-                        return CalcResult::new_error(
-                            Error::VALUE,
-                            cell,
-                            "Ranges are in different sheets".to_string(),
-                        );
-                    }
-
-                    let row1 = left.row;
-                    let mut row2 = right.row;
-                    let column1 = left.column;
-                    let mut column2 = right.column;
-
-                    if row1 == 1 && row2 == LAST_ROW {
-                        row2 = match self.workbook.worksheet(left.sheet) {
-                            Ok(s) => s.dimension().max_row,
-                            Err(_) => {
-                                return CalcResult::new_error(
-                                    Error::ERROR,
-                                    cell,
-                                    format!("Invalid worksheet index: '{}'", left.sheet),
-                                );
-                            }
-                        };
-                    }
-                    if column1 == 1 && column2 == LAST_COLUMN {
-                        column2 = match self.workbook.worksheet(left.sheet) {
-                            Ok(s) => s.dimension().max_column,
-                            Err(_) => {
-                                return CalcResult::new_error(
-                                    Error::ERROR,
-                                    cell,
-                                    format!("Invalid worksheet index: '{}'", left.sheet),
-                                );
-                            }
-                        };
-                    }
-
-                    for row in row1..=row2 {
-                        for column in column1..=column2 {
-                            match self.evaluate_cell(CellReferenceIndex {
-                                sheet: left.sheet,
-                                row,
-                                column,
-                            }) {
-                                CalcResult::Number(value) => {
-                                    accumulate(&mut sum, &mut sumsq, &mut count, value);
-                                }
-                                CalcResult::String(_) => {
-                                    accumulate(&mut sum, &mut sumsq, &mut count, 0.0);
-                                }
-                                CalcResult::Boolean(value) => {
-                                    let val = if value { 1.0 } else { 0.0 };
-                                    accumulate(&mut sum, &mut sumsq, &mut count, val);
-                                }
-                                error @ CalcResult::Error { .. } => return error,
-                                _ => {
-                                    // ignore non-numeric for now (A semantics to be added)
-                                }
-                            }
-                        }
-                    }
-                }
-                CalcResult::Array(array) => {
-                    for row in array {
-                        for value in row {
-                            match value {
-                                ArrayNode::Number(value) => {
-                                    accumulate(&mut sum, &mut sumsq, &mut count, value);
-                                }
-                                ArrayNode::Error(error) => {
-                                    return CalcResult::Error {
-                                        error,
-                                        origin: cell,
-                                        message: "Error in array".to_string(),
-                                    }
-                                }
-                                _ => {
-                                    // ignore non-numeric for now (A semantics to be added)
-                                }
-                            }
-                        }
-                    }
-                }
-                error @ CalcResult::Error { .. } => return error,
-                _ => {
-                    // ignore non-numeric for now (A semantics to be added)
-                }
-            }
-        }
-
-        if count <= 1 {
-            return CalcResult::new_error(
-                Error::DIV,
-                cell,
-                "VARA requires at least two numeric values".to_string(),
-            );
-        }
-
-        let n = count as f64;
-        let mut var = (sumsq - (sum * sum) / n) / (n - 1.0);
-
-        if var < 0.0 && var > -1e-12 {
-            var = 0.0;
-        }
-
-        CalcResult::Number(var)
-    }
-
-    pub(crate) fn fn_varpa(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        if args.is_empty() {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        let mut sum = 0.0;
-        let mut sumsq = 0.0;
-        let mut count: u64 = 0;
-
-        #[inline]
-        fn accumulate(sum: &mut f64, sumsq: &mut f64, count: &mut u64, value: f64) {
-            *sum += value;
-            *sumsq += value * value;
-            *count += 1;
-        }
-
-        for arg in args {
-            match self.evaluate_node_in_context(arg, cell) {
-                CalcResult::Number(value) => {
-                    accumulate(&mut sum, &mut sumsq, &mut count, value);
-                }
-                CalcResult::Range { left, right } => {
-                    if left.sheet != right.sheet {
-                        return CalcResult::new_error(
-                            Error::VALUE,
-                            cell,
-                            "Ranges are in different sheets".to_string(),
-                        );
-                    }
-
-                    let row1 = left.row;
-                    let mut row2 = right.row;
-                    let column1 = left.column;
-                    let mut column2 = right.column;
-
-                    if row1 == 1 && row2 == LAST_ROW {
-                        row2 = match self.workbook.worksheet(left.sheet) {
-                            Ok(s) => s.dimension().max_row,
-                            Err(_) => {
-                                return CalcResult::new_error(
-                                    Error::ERROR,
-                                    cell,
-                                    format!("Invalid worksheet index: '{}'", left.sheet),
-                                );
-                            }
-                        };
-                    }
-                    if column1 == 1 && column2 == LAST_COLUMN {
-                        column2 = match self.workbook.worksheet(left.sheet) {
-                            Ok(s) => s.dimension().max_column,
-                            Err(_) => {
-                                return CalcResult::new_error(
-                                    Error::ERROR,
-                                    cell,
-                                    format!("Invalid worksheet index: '{}'", left.sheet),
-                                );
-                            }
-                        };
-                    }
-
-                    for row in row1..row2 + 1 {
-                        for column in column1..(column2 + 1) {
-                            match self.evaluate_cell(CellReferenceIndex {
-                                sheet: left.sheet,
-                                row,
-                                column,
-                            }) {
-                                CalcResult::Number(value) => {
-                                    accumulate(&mut sum, &mut sumsq, &mut count, value);
-                                }
-                                CalcResult::String(_) => {
-                                    accumulate(&mut sum, &mut sumsq, &mut count, 0.0);
-                                }
-                                CalcResult::Boolean(value) => {
-                                    let val = if value { 1.0 } else { 0.0 };
-                                    accumulate(&mut sum, &mut sumsq, &mut count, val);
-                                }
-                                error @ CalcResult::Error { .. } => return error,
-                                _ => {
-                                    // ignore non-numeric for now
-                                }
-                            }
-                        }
-                    }
-                }
-                CalcResult::Array(array) => {
-                    for row in array {
-                        for value in row {
-                            match value {
-                                ArrayNode::Number(value) => {
-                                    accumulate(&mut sum, &mut sumsq, &mut count, value);
-                                }
-                                ArrayNode::Error(error) => {
-                                    return CalcResult::Error {
-                                        error,
-                                        origin: cell,
-                                        message: "Error in array".to_string(),
-                                    }
-                                }
-                                _ => {
-                                    // ignore non-numeric for now
-                                }
-                            }
-                        }
-                    }
-                }
-                error @ CalcResult::Error { .. } => return error,
-                _ => {
-                    // ignore non-numeric for now
-                }
-            }
-        }
-
-        if count == 0 {
-            return CalcResult::new_error(
-                Error::DIV,
-                cell,
-                "VARPA with no numeric data".to_string(),
-            );
-        }
-
-        let n = count as f64;
-        let mut var = (sumsq - (sum * sum) / n) / n;
-
-        if var < 0.0 && var > -1e-12 {
-            var = 0.0;
-        }
-
-        CalcResult::Number(var)
-    }
-}

base/src/functions/statistical/weibull.rs

@@ -1,71 +0,0 @@
-use statrs::distribution::{Continuous, ContinuousCDF, Weibull};
-
-use crate::expressions::types::CellReferenceIndex;
-use crate::{
-    calc_result::CalcResult, expressions::parser::Node, expressions::token::Error, model::Model,
-};
-
-impl Model {
-    // WEIBULL.DIST(x, alpha, beta, cumulative)
-    pub(crate) fn fn_weibull_dist(
-        &mut self,
-        args: &[Node],
-        cell: CellReferenceIndex,
-    ) -> CalcResult {
-        if args.len() != 4 {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        let x = match self.get_number_no_bools(&args[0], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-
-        let alpha = match self.get_number_no_bools(&args[1], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-
-        let beta = match self.get_number_no_bools(&args[2], cell) {
-            Ok(f) => f,
-            Err(e) => return e,
-        };
-
-        let cumulative = match self.get_boolean(&args[3], cell) {
-            Ok(b) => b,
-            Err(e) => return e,
-        };
-
-        if x < 0.0 || alpha <= 0.0 || beta <= 0.0 {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "Invalid parameters for WEIBULL.DIST".to_string(),
-            };
-        }
-
-        // statrs::Weibull: shape = k (alpha), scale = lambda (beta)
-        let dist = match Weibull::new(alpha, beta) {
-            Ok(d) => d,
-            Err(_) => {
-                return CalcResult::Error {
-                    error: Error::NUM,
-                    origin: cell,
-                    message: "Invalid parameters for WEIBULL.DIST".to_string(),
-                }
-            }
-        };
-
-        let result = if cumulative { dist.cdf(x) } else { dist.pdf(x) };
-
-        if !result.is_finite() {
-            return CalcResult::Error {
-                error: Error::NUM,
-                origin: cell,
-                message: "Invalid result for WEIBULL.DIST".to_string(),
-            };
-        }
-
-        CalcResult::Number(result)
-    }
-}

base/src/functions/statistical/z_test.rs

@@ -1,171 +0,0 @@
-use statrs::distribution::{ContinuousCDF, Normal};
-
-use crate::expressions::token::Error;
-use crate::expressions::types::CellReferenceIndex;
-use crate::{calc_result::CalcResult, expressions::parser::Node, model::Model};
-
-impl Model {
-    // Z.TEST(array, x, [sigma])
-    pub(crate) fn fn_z_test(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
-        // 2 or 3 arguments
-        if args.len() < 2 || args.len() > 3 {
-            return CalcResult::new_args_number_error(cell);
-        }
-
-        let array_arg = self.evaluate_node_in_context(&args[0], cell);
-
-        // Flatten first argument into Vec<Option<f64>> (numeric / non-numeric)
-        let values = match array_arg {
-            CalcResult::Range { left, right } => match self.values_from_range(left, right) {
-                Ok(v) => v,
-                Err(error) => return error,
-            },
-            CalcResult::Array(array) => match self.values_from_array(array) {
-                Ok(v) => v,
-                Err(error) => {
-                    return CalcResult::new_error(
-                        Error::VALUE,
-                        cell,
-                        format!("Error in array argument: {:?}", error),
-                    );
-                }
-            },
-            CalcResult::Number(v) => vec![Some(v)],
-            error @ CalcResult::Error { .. } => return error,
-            _ => {
-                return CalcResult::new_error(
-                    Error::VALUE,
-                    cell,
-                    "Z.TEST first argument must be a range or array".to_string(),
-                );
-            }
-        };
-
-        // Collect basic stats on numeric entries
-        let mut sum = 0.0;
-        let mut count: u64 = 0;
-
-        for x in values.iter().flatten() {
-            sum += x;
-            count += 1;
-        }
-
-        // Excel: if array has no numeric values -> #N/A
-        if count == 0 {
-            return CalcResult::new_error(
-                Error::NA,
-                cell,
-                "Z.TEST array has no numeric data".to_string(),
-            );
-        }
-
-        let n = count as f64;
-        let mean = sum / n;
-
-        // x argument (hypothesized population mean)
-        let x_value = match self.evaluate_node_in_context(&args[1], cell) {
-            CalcResult::Number(v) => v,
-            error @ CalcResult::Error { .. } => return error,
-            _ => {
-                return CalcResult::new_error(
-                    Error::VALUE,
-                    cell,
-                    "Z.TEST second argument (x) must be numeric".to_string(),
-                );
-            }
-        };
-
-        // Optional sigma
-        let mut sigma: Option<f64> = None;
-        if args.len() == 3 {
-            match self.evaluate_node_in_context(&args[2], cell) {
-                CalcResult::Number(v) => {
-                    if v == 0.0 {
-                        return CalcResult::new_error(
-                            Error::NUM,
-                            cell,
-                            "Z.TEST sigma cannot be zero".to_string(),
-                        );
-                    }
-                    sigma = Some(v);
-                }
-                error @ CalcResult::Error { .. } => return error,
-                _ => {
-                    return CalcResult::new_error(
-                        Error::VALUE,
-                        cell,
-                        "Z.TEST sigma (third argument) must be numeric".to_string(),
-                    );
-                }
-            }
-        }
-
-        // If sigma omitted, use sample standard deviation STDEV(array)
-        let sigma_value = if let Some(s) = sigma {
-            s
-        } else {
-            // Excel: if only one numeric value and sigma omitted -> #DIV/0!
-            if count <= 1 {
-                return CalcResult::new_error(
-                    Error::DIV,
-                    cell,
-                    "Z.TEST requires at least two values when sigma is omitted".to_string(),
-                );
-            }
-
-            // Compute sum of squared deviations
-            let mut sumsq_dev = 0.0;
-            for x in values.iter().flatten() {
-                let d = x - mean;
-                sumsq_dev += d * d;
-            }
-
-            let var = sumsq_dev / (n - 1.0);
-            if var <= 0.0 {
-                return CalcResult::new_error(
-                    Error::DIV,
-                    cell,
-                    "Z.TEST standard deviation is zero".to_string(),
-                );
-            }
-
-            var.sqrt()
-        };
-
-        // Compute z statistic: (mean - x) / (sigma / sqrt(n))
-        let denom = sigma_value / n.sqrt();
-        if denom == 0.0 {
-            return CalcResult::new_error(
-                Error::DIV,
-                cell,
-                "Z.TEST denominator is zero".to_string(),
-            );
-        }
-
-        let z = (mean - x_value) / denom;
-
-        // Standard normal CDF
-        let dist = match Normal::new(0.0, 1.0) {
-            Ok(d) => d,
-            Err(_) => {
-                return CalcResult::new_error(
-                    Error::NUM,
-                    cell,
-                    "Cannot create standard normal distribution in Z.TEST".to_string(),
-                );
-            }
-        };
-
-        let mut p = 1.0 - dist.cdf(z);
-
-        // clamp tiny FP noise
-        if p < 0.0 && p > -1e-15 {
-            p = 0.0;
-        }
-        if p > 1.0 && p < 1.0 + 1e-15 {
-            p = 1.0;
-        }
-
-        CalcResult::Number(p)
-    }
-}

base/src/test/mod.rs

@@ -18,7 +18,6 @@ mod test_fn_concatenate;
 mod test_fn_count;
 mod test_fn_day;
 mod test_fn_exact;
-mod test_fn_fact;
 mod test_fn_financial;
 mod test_fn_formulatext;
 mod test_fn_if;
@@ -56,17 +55,12 @@ mod test_yearfrac_basis;
 pub(crate) mod util;
 
 mod engineering;
-mod statistical;
 mod test_fn_offset;
 mod test_number_format;
 
 mod test_arrays;
-mod test_combin_combina;
 mod test_escape_quotes;
-mod test_even_odd;
-mod test_exp_sign;
 mod test_extend;
-mod test_fn_datevalue_timevalue;
 mod test_fn_fv;
 mod test_fn_round;
 mod test_fn_type;
@@ -86,6 +80,5 @@ mod test_percentage;
 mod test_set_functions_error_handling;
 mod test_sheet_names;
 mod test_today;
-mod test_trigonometric_reciprocals;
 mod test_types;
 mod user_model;

base/src/test/statistical/mod.rs

@@ -1,22 +0,0 @@
-mod test_fn_avedev;
-mod test_fn_binom;
-mod test_fn_chisq;
-mod test_fn_chisq_test;
-mod test_fn_confidence;
-mod test_fn_covariance;
-mod test_fn_devsq;
-mod test_fn_expon_dist;
-mod test_fn_f;
-mod test_fn_fisher;
-mod test_fn_hyp_geom_dist;
-mod test_fn_log_norm;
-mod test_fn_norm_dist;
-mod test_fn_pearson;
-mod test_fn_phi;
-mod test_fn_poisson;
-mod test_fn_stdev;
-mod test_fn_t_dist;
-mod test_fn_t_test;
-mod test_fn_var;
-mod test_fn_weibull;
-mod test_fn_z_test;

base/src/test/statistical/test_fn_avedev.rs

@@ -1,40 +0,0 @@
-#![allow(clippy::unwrap_used)]
-
-use crate::test::util::new_empty_model;
-
-#[test]
-fn smoke_test() {
-    let mut model = new_empty_model();
-    model._set("A1", "=STDEV.P(10, 12, 23, 23, 16, 23, 21)");
-    model._set("A2", "=STDEV.S(10, 12, 23, 23, 16, 23, 21)");
-    model.evaluate();
-
-    assert_eq!(model._get_text("A1"), *"5.174505793");
-
-    assert_eq!(model._get_text("A2"), *"5.589105048");
-}
-
-#[test]
-fn numbers() {
-    let mut model = new_empty_model();
-
-    model._set("A2", "24");
-    model._set("A3", "25");
-    model._set("A4", "27");
-    model._set("A5", "23");
-    model._set("A6", "45");
-    model._set("A7", "23.5");
-    model._set("A8", "34");
-    model._set("A9", "23");
-    model._set("A10", "23");
-    model._set("A11", "TRUE");
-    model._set("A12", "'23");
-    model._set("A13", "Text");
-    model._set("A14", "FALSE");
-    model._set("A15", "45");
-
-    model._set("B1", "=AVEDEV(A2:A15)");
-    model.evaluate();
-
-    assert_eq!(model._get_text("B1"), *"7.25");
-}

base/src/test/statistical/test_fn_binom.rs

@@ -1,86 +0,0 @@
-#![allow(clippy::unwrap_used)]
-
-use crate::test::util::new_empty_model;
-
-#[test]
-fn test_fn_binom_dist_smoke() {
-    let mut model = new_empty_model();
-    model._set("A1", "=BINOM.DIST(6, 10, 0.5, TRUE)");
-    model._set("A2", "=BINOM.DIST(6, 10, 0.5, FALSE)");
-    model._set("A3", "=BINOM.DIST(6, 10, 0.5)"); // wrong args
-    model._set("A4", "=BINOM.DIST(6, 10, 0.5, TRUE, FALSE)"); // too many args
-    model.evaluate();
-
-    // P(X <= 6) for X ~ Bin(10, 0.5) = 0.828125
-    assert_eq!(model._get_text("A1"), *"0.828125");
-
-    // P(X = 6) for X ~ Bin(10, 0.5) = 0.205078125
-    assert_eq!(model._get_text("A2"), *"0.205078125");
-
-    assert_eq!(model._get_text("A3"), *"#ERROR!");
-    assert_eq!(model._get_text("A4"), *"#ERROR!");
-}
-
-#[test]
-fn test_fn_binom_dist_range_smoke() {
-    let mut model = new_empty_model();
-    model._set("A1", "=BINOM.DIST.RANGE(60, 0.75, 48)");
-    model._set("A2", "=BINOM.DIST.RANGE(60, 0.75, 45, 50)");
-    model._set("A3", "=BINOM.DIST.RANGE(60, 1.2, 45, 50)"); // p > 1 -> #NUM!
-    model._set("A4", "=BINOM.DIST.RANGE(60, 0.75, 50, 45)"); // lower > upper -> #NUM!");
-    model.evaluate();
-
-    assert_eq!(model._get_text("A1"), *"0.083974967");
-
-    assert_eq!(model._get_text("A2"), *"0.523629793");
-
-    assert_eq!(model._get_text("A3"), *"#NUM!");
-    assert_eq!(model._get_text("A4"), *"#NUM!");
-}
-
-#[test]
-fn test_fn_binom_inv_smoke() {
-    let mut model = new_empty_model();
-    model._set("A1", "=BINOM.INV(6, 0.5, 0.75)");
-    model._set("A2", "=BINOM.INV(6, 0.5, -0.1)"); // alpha < 0 -> #NUM!
-    model._set("A3", "=BINOM.INV(6, 1.2, 0.75)"); // p > 1 -> #NUM!
-    model._set("A4", "=BINOM.INV(6, 0.5)"); // args error
-    model.evaluate();
-
-    assert_eq!(model._get_text("A1"), *"4");
-    assert_eq!(model._get_text("A2"), *"#NUM!");
-    assert_eq!(model._get_text("A3"), *"#NUM!");
-    assert_eq!(model._get_text("A4"), *"#ERROR!");
-}
-
-#[test]
-fn test_fn_negbinom_dist_smoke() {
-    let mut model = new_empty_model();
-
-    // Valid: PMF (non-cumulative) and CDF (cumulative)
-    model._set("A1", "=NEGBINOM.DIST(10, 5, 0.25, FALSE)");
-    model._set("A2", "=NEGBINOM.DIST(10, 5, 0.25, TRUE)");
-
-    // Wrong number of arguments -> #ERROR!
-    model._set("A3", "=NEGBINOM.DIST(10, 5, 0.25)");
-    model._set("A4", "=NEGBINOM.DIST(10, 5, 0.25, TRUE, FALSE)");
-
-    // Domain errors:
-    // p < 0 or p > 1 -> #NUM!
-    model._set("A5", "=NEGBINOM.DIST(10, 5, 1.5, TRUE)");
-    // number_f < 0 -> #NUM!
-    model._set("A6", "=NEGBINOM.DIST(-1, 5, 0.25, TRUE)");
-    // number_s < 1 -> #NUM!
-    model._set("A7", "=NEGBINOM.DIST(10, 0, 0.25, TRUE)");
-
-    model.evaluate();
-
-    assert_eq!(model._get_text("A1"), *"0.05504866");
-    assert_eq!(model._get_text("A2"), *"0.313514058");
-
-    assert_eq!(model._get_text("A3"), *"#ERROR!");
-    assert_eq!(model._get_text("A4"), *"#ERROR!");
-    assert_eq!(model._get_text("A5"), *"#NUM!");
-    assert_eq!(model._get_text("A6"), *"#NUM!");
-    assert_eq!(model._get_text("A7"), *"#NUM!");
-}

base/src/test/statistical/test_fn_chisq.rs

@@ -1,140 +0,0 @@
-#![allow(clippy::unwrap_used)]
-
-use crate::test::util::new_empty_model;
-
-#[test]
-fn test_fn_chisq_dist_smoke() {
-    let mut model = new_empty_model();
-
-    // Valid: CDF
-    model._set("A1", "=CHISQ.DIST(0.5, 4, TRUE)");
-
-    // Valid: PDF
-    model._set("A2", "=CHISQ.DIST(0.5, 4, FALSE)");
-
-    // Valid: CDF with numeric cumulative (1 -> TRUE)
-    model._set("A3", "=CHISQ.DIST(0.5, 4, 1)");
-
-    // Wrong number of args -> #ERROR!
-    model._set("A4", "=CHISQ.DIST(0.5, 4)");
-    model._set("A5", "=CHISQ.DIST(0.5, 4, TRUE, FALSE)");
-
-    // Domain errors
-    // x < 0 -> #NUM!
-    model._set("A6", "=CHISQ.DIST(-1, 4, TRUE)");
-    // deg_freedom < 1 -> #NUM!
-    model._set("A7", "=CHISQ.DIST(0.5, 0, TRUE)");
-
-    model.evaluate();
-
-    // Values for df = 4
-    // CDF(0.5) ≈ 0.026499021, PDF(0.5) ≈ 0.097350098
-    assert_eq!(model._get_text("A1"), *"0.026499021");
-    assert_eq!(model._get_text("A2"), *"0.097350098");
-    assert_eq!(model._get_text("A3"), *"0.026499021");
-
-    assert_eq!(model._get_text("A4"), *"#ERROR!");
-    assert_eq!(model._get_text("A5"), *"#ERROR!");
-    assert_eq!(model._get_text("A6"), *"#NUM!");
-    assert_eq!(model._get_text("A7"), *"#NUM!");
-}
-
-#[test]
-fn test_fn_chisq_dist_rt_smoke() {
-    let mut model = new_empty_model();
-
-    // Valid calls
-    model._set("A1", "=CHISQ.DIST.RT(0.5, 4)");
-    model._set("A2", "=CHISQ.DIST.RT(5, 4)");
-
-    // Too few / too many args -> #ERROR!
-    model._set("A3", "=CHISQ.DIST.RT(0.5)");
-    model._set("A4", "=CHISQ.DIST.RT(0.5, 4, 1)");
-
-    // Domain errors
-    // x < 0 -> #NUM!
-    model._set("A5", "=CHISQ.DIST.RT(-1, 4)");
-    // deg_freedom < 1 -> #NUM!
-    model._set("A6", "=CHISQ.DIST.RT(0.5, 0)");
-
-    model.evaluate();
-
-    // For df = 4:
-    // right tail at 0.5 ≈ 0.973500979
-    // right tail at 5.0 ≈ 0.287297495
-    assert_eq!(model._get_text("A1"), *"0.973500979");
-    assert_eq!(model._get_text("A2"), *"0.287297495");
-
-    assert_eq!(model._get_text("A3"), *"#ERROR!");
-    assert_eq!(model._get_text("A4"), *"#ERROR!");
-    assert_eq!(model._get_text("A5"), *"#NUM!");
-    assert_eq!(model._get_text("A6"), *"#NUM!");
-}
-
-#[test]
-fn test_fn_chisq_inv_smoke() {
-    let mut model = new_empty_model();
-
-    // Valid calls
-    model._set("A1", "=CHISQ.INV(0.95, 4)");
-    model._set("A2", "=CHISQ.INV(0.1, 10)");
-
-    // Wrong number of args -> #ERROR!
-    model._set("A3", "=CHISQ.INV(0.95)");
-    model._set("A4", "=CHISQ.INV(0.95, 4, 1)");
-
-    // Domain errors
-    // probability < 0 or > 1 -> #NUM!
-    model._set("A5", "=CHISQ.INV(-0.1, 4)");
-    model._set("A6", "=CHISQ.INV(1.1, 4)");
-    // deg_freedom < 1 -> #NUM!
-    model._set("A7", "=CHISQ.INV(0.5, 0)");
-
-    model.evaluate();
-
-    // Standard critical values:
-    // CHISQ.INV(0.95, 4) ≈ 9.487729037
-    // CHISQ.INV(0.1, 10) ≈ 4.865182052
-    assert_eq!(model._get_text("A1"), *"9.487729037");
-    assert_eq!(model._get_text("A2"), *"4.865182052");
-
-    assert_eq!(model._get_text("A3"), *"#ERROR!");
-    assert_eq!(model._get_text("A4"), *"#ERROR!");
-    assert_eq!(model._get_text("A5"), *"#NUM!");
-    assert_eq!(model._get_text("A6"), *"#NUM!");
-    assert_eq!(model._get_text("A7"), *"#NUM!");
-}
-
-#[test]
-fn test_fn_chisq_inv_rt_smoke() {
-    let mut model = new_empty_model();
-
-    // Valid calls
-    model._set("A1", "=CHISQ.INV.RT(0.05, 4)");
-    model._set("A2", "=CHISQ.INV.RT(0.9, 10)");
-
-    // Wrong number of args -> #ERROR!
-    model._set("A3", "=CHISQ.INV.RT(0.05)");
-    model._set("A4", "=CHISQ.INV.RT(0.05, 4, 1)");
-
-    // Domain errors
-    // probability < 0 or > 1 -> #NUM!
-    model._set("A5", "=CHISQ.INV.RT(-0.1, 4)");
-    model._set("A6", "=CHISQ.INV.RT(1.1, 4)");
-    // deg_freedom < 1 -> #NUM!
-    model._set("A7", "=CHISQ.INV.RT(0.5, 0)");
-
-    model.evaluate();
-
-    // For chi-square:
-    // CHISQ.INV.RT(0.05, 4) = CHISQ.INV(0.95, 4) ≈ 9.487729037
-    // CHISQ.INV.RT(0.9, 10)  = CHISQ.INV(0.1, 10) ≈ 4.865182052
-    assert_eq!(model._get_text("A1"), *"9.487729037");
-    assert_eq!(model._get_text("A2"), *"4.865182052");
-
-    assert_eq!(model._get_text("A3"), *"#ERROR!");
-    assert_eq!(model._get_text("A4"), *"#ERROR!");
-    assert_eq!(model._get_text("A5"), *"#NUM!");
-    assert_eq!(model._get_text("A6"), *"#NUM!");
-    assert_eq!(model._get_text("A7"), *"#NUM!");
-}

base/src/test/statistical/test_fn_chisq_test.rs

@@ -1,127 +0,0 @@
-#![allow(clippy::unwrap_used)]
-
-use crate::test::util::new_empty_model;
-
-#[test]
-fn test_fn_chisq_test_smoke() {
-    let mut model = new_empty_model();
-    model._set("A2", "48");
-    model._set("A3", "32");
-    model._set("A4", "12");
-    model._set("A5", "1");
-    model._set("A6", "'13");
-    model._set("A7", "TRUE");
-    model._set("A8", "1");
-    model._set("A9", "13");
-    model._set("A10", "15");
-
-    model._set("B2", "55");
-    model._set("B3", "34");
-    model._set("B4", "13");
-    model._set("B5", "blah");
-    model._set("B6", "13");
-    model._set("B7", "1");
-    model._set("B8", "TRUE");
-    model._set("B9", "'14");
-    model._set("B10", "16");
-
-    model._set("C1", "=CHISQ.TEST(A2:A10, B2:B10)");
-    model.evaluate();
-    assert_eq!(model._get_text("C1"), *"0.997129538");
-}
-
-#[test]
-fn arrays() {
-    let mut model = new_empty_model();
-    model._set("A2", "TRUE");
-    model._set("A3", "4");
-    model._set("A4", "'3");
-    model._set("B2", "2");
-    model._set("B3", "2");
-    model._set("B4", "2");
-    model._set("C1", "=CHISQ.TEST(A2:A4, B2:B4)");
-
-    model._set("G5", "=CHISQ.TEST({TRUE,4,\"3\"}, {2,2,2})");
-
-    // 1D arrays with different shapes
-    model._set("G6", "=CHISQ.TEST({1,2,3}, {3;3;4})");
-
-    // 2D array
-    model._set("G7", "=CHISQ.TEST({1,2;3,4},{2,3;2,2})");
-
-    // 1D arrays with same shape
-    model._set("G8", "=CHISQ.TEST({1,2,3,4}, {2,3,4,5})");
-
-    model.evaluate();
-    assert_eq!(model._get_text("C1"), *"0.367879441");
-    assert_eq!(model._get_text("G5"), *"0.367879441");
-
-    assert_eq!(model._get_text("G6"), *"0.383531573");
-
-    assert_eq!(model._get_text("G7"), *"0.067889155");
-
-    assert_eq!(model._get_text("G8"), *"0.733094495");
-}
-
-#[test]
-fn more_arrays() {
-    let mut model = new_empty_model();
-    model._set("V20", "2");
-    model._set("V21", "4");
-    model._set("W20", "3");
-    model._set("W21", "5");
-    model._set("C1", "=CHISQ.TEST({1,2;3,4},V20:W21)");
-    model._set("C2", "=CHISQ.TEST({1,2;3,4}, {2,3;4,5})");
-    model.evaluate();
-    assert_eq!(model._get_text("C1"), *"0.257280177");
-    assert_eq!(model._get_text("C2"), *"0.257280177");
-}
-
-#[test]
-fn array_ranges() {
-    let mut model = new_empty_model();
-    model._set("A2", "TRUE");
-    model._set("A3", "4");
-    model._set("A4", "'3");
-    model._set("B2", "2");
-    model._set("B3", "2");
-    model._set("B4", "2");
-    model._set("C1", "=CHISQ.TEST(A2:A4, {2;2;2})");
-
-    model._set("G5", "=CHISQ.TEST({TRUE;4;\"3\"}, B2:B4)");
-    model.evaluate();
-
-    assert_eq!(model._get_text("C1"), *"0.367879441");
-    assert_eq!(model._get_text("G5"), *"0.367879441");
-}
-
-#[test]
-fn array_2d_ranges() {
-    let mut model = new_empty_model();
-    model._set("A2", "2");
-    model._set("B2", "3");
-    model._set("C2", "4");
-    model._set("A3", "5");
-    model._set("B3", "6");
-    model._set("C3", "7");
-    model._set("G1", "=CHISQ.TEST({1,2,3;4,2,6}, A2:C3)");
-    model.evaluate();
-    assert_eq!(model._get_text("G1"), *"0.129195493");
-}
-
-#[test]
-fn ranges_1d() {
-    let mut model = new_empty_model();
-    model._set("A2", "1");
-    model._set("A3", "2");
-    model._set("A4", "3");
-    model._set("B2", "4");
-    model._set("C2", "5");
-    model._set("D2", "6");
-    model._set("G1", "=CHISQ.TEST(A2:A4, B2:D2)");
-    model._set("G2", "=CHISQ.TEST(B2:D2, A2:A4)");
-
-    model.evaluate();
-    assert_eq!(model._get_text("G1"), *"0.062349477");
-    assert_eq!(model._get_text("G2"), *"0.000261259");
-}

base/src/test/statistical/test_fn_confidence.rs

@@ -1,51 +0,0 @@
-#![allow(clippy::unwrap_used)]
-
-use crate::test::util::new_empty_model;
-
-#[test]
-fn test_fn_confidence_norm_smoke() {
-    let mut model = new_empty_model();
-
-    model._set("A1", "=CONFIDENCE.NORM(0.05, 2.5, 50)");
-
-    // Some edge/error cases
-    model._set("A2", "=CONFIDENCE.NORM(0, 2.5, 50)"); // alpha <= 0  -> #NUM!
-    model._set("A3", "=CONFIDENCE.NORM(1, 2.5, 50)"); // alpha >= 1  -> #NUM!
-    model._set("A4", "=CONFIDENCE.NORM(0.05, -1, 50)"); // std_dev <=0 -> #NUM!
-    model._set("A5", "=CONFIDENCE.NORM(0.05, 2.5, 1)");
-    model._set("A6", "=CONFIDENCE.NORM(0.05, 2.5, 0.99)"); // size < 1 -> #NUM!
-
-    model.evaluate();
-
-    assert_eq!(model._get_text("A1"), *"0.692951912");
-
-    assert_eq!(model._get_text("A2"), *"#NUM!");
-    assert_eq!(model._get_text("A3"), *"#NUM!");
-    assert_eq!(model._get_text("A4"), *"#NUM!");
-    assert_eq!(model._get_text("A5"), *"4.899909961");
-    assert_eq!(model._get_text("A6"), *"#NUM!");
-}
-
-#[test]
-fn test_fn_confidence_t_smoke() {
-    let mut model = new_empty_model();
-
-    model._set("A1", "=CONFIDENCE.T(0.05, 50000, 100)");
-
-    // Some edge/error cases
-    model._set("A2", "=CONFIDENCE.T(0, 50000, 100)"); // alpha <= 0 -> #NUM!
-    model._set("A3", "=CONFIDENCE.T(1, 50000, 100)"); // alpha >= 1 -> #NUM!
-    model._set("A4", "=CONFIDENCE.T(0.05, -1, 100)");
-    model._set("A5", "=CONFIDENCE.T(0.05, 50000, 1)");
-    model._set("A6", "=CONFIDENCE.T(0.05, 50000, 1.7)");
-
-    model.evaluate();
-
-    assert_eq!(model._get_text("A1"), *"9921.08475793");
-
-    assert_eq!(model._get_text("A2"), *"#NUM!");
-    assert_eq!(model._get_text("A3"), *"#NUM!");
-    assert_eq!(model._get_text("A4"), *"#NUM!");
-    assert_eq!(model._get_text("A5"), *"#DIV/0!");
-    assert_eq!(model._get_text("A6"), *"#DIV/0!");
-}

base/src/test/statistical/test_fn_covariance.rs

@@ -1,57 +0,0 @@
-#![allow(clippy::unwrap_used)]
-
-use crate::test::util::new_empty_model;
-
-#[test]
-fn test_fn_covariance_smoke() {
-    let mut model = new_empty_model();
-    model._set("A1", "3");
-    model._set("A2", "9");
-    model._set("A3", "2");
-    model._set("A4", "7");
-    model._set("A5", "4");
-    model._set("A6", "12");
-
-    model._set("B1", "5");
-    model._set("B2", "15");
-    model._set("B3", "6");
-    model._set("B4", "17");
-    model._set("B5", "8");
-    model._set("B6", "20");
-
-    model._set("C1", "=COVARIANCE.P(A1:A6, B1:B6)");
-    model._set("C2", "=COVARIANCE.S(A1:A6, B1:B6)");
-    model.evaluate();
-
-    assert_eq!(model._get_text("C1"), *"19.194444444");
-    assert_eq!(model._get_text("C2"), *"23.033333333");
-}
-
-#[test]
-fn arrays_mixed() {
-    let mut model = new_empty_model();
-
-    model._set("A2", "2");
-    model._set("A3", "4");
-    model._set("A4", "6");
-    model._set("A5", "8");
-
-    model._set("B2", "1");
-    model._set("B3", "3");
-    model._set("B4", "5");
-    model._set("B5", "7");
-
-    model._set("C1", "=COVARIANCE.P(A2:A5, {1,3,5,7})");
-    model._set("C2", "=COVARIANCE.S(A2:A5, {1,3,5,7})");
-    model._set("C3", "=COVARIANCE.P(A2:A5, B2:B5)");
-    model._set("C4", "=COVARIANCE.S(A2:A5, B2:B5)");
-    model._set("C5", "=COVARIANCE.P({2,4,6,8}, B2:B5)");
-    model._set("C6", "=COVARIANCE.S({2,4,6,8}, B2:B5)");
-    model._set("C7", "=COVARIANCE.P({2,4,6,8}, {1,3,5,7})");
-    model._set("C8", "=COVARIANCE.S({2,4,6,8}, {1,3,5,7})");
-
-    model.evaluate();
-
-    assert_eq!(model._get_text("C1"), *"5");
-    assert_eq!(model._get_text("C2"), *"6.666666667");
-}

base/src/test/statistical/test_fn_devsq.rs

@@ -1,50 +0,0 @@
-#![allow(clippy::unwrap_used)]
-
-use crate::test::util::new_empty_model;
-
-#[test]
-fn arguments_smoke_test() {
-    let mut model = new_empty_model();
-    model._set("A1", "=DEVSQ()");
-    model._set("A2", "=DEVSQ(1, 2, 3)");
-    model._set("A3", "=DEVSQ(1, )");
-    model._set("A4", "=DEVSQ(1,   , 3)");
-
-    model.evaluate();
-
-    assert_eq!(model._get_text("A1"), *"#ERROR!");
-    assert_eq!(model._get_text("A2"), *"2");
-    assert_eq!(model._get_text("A3"), *"0");
-    assert_eq!(model._get_text("A4"), *"2");
-}
-
-#[test]
-fn ranges() {
-    let mut model = new_empty_model();
-    model._set("A1", "=DEVSQ(A2:A8)");
-    model._set("A2", "4");
-    model._set("A3", "5");
-    model._set("A4", "8");
-    model._set("A5", "7");
-    model._set("A6", "11");
-    model._set("A7", "4");
-    model._set("A8", "3");
-    model.evaluate();
-    assert_eq!(model._get_text("A1"), *"48");
-}
-
-#[test]
-fn arrays() {
-    let mut model = new_empty_model();
-    model._set("A1", "=DEVSQ({1, 2, 3})");
-    model._set("A2", "=DEVSQ({1; 2; 3})");
-    model._set("A3", "=DEVSQ({1, 2; 3, 4})");
-    model._set("A4", "=DEVSQ({1, 2; 3, 4; 5, 6})");
-
-    model.evaluate();
-
-    assert_eq!(model._get_text("A1"), *"2");
-    assert_eq!(model._get_text("A2"), *"2");
-    assert_eq!(model._get_text("A3"), *"5");
-    assert_eq!(model._get_text("A4"), *"17.5");
-}

base/src/test/statistical/test_fn_expon_dist.rs

@@ -1,32 +0,0 @@
-#![allow(clippy::unwrap_used)]
-
-use crate::test::util::new_empty_model;
-
-#[test]
-fn test_fn_expon_dist_smoke() {
-    let mut model = new_empty_model();
-
-    // λ = 1, x = 0.5
-    // CDF = 1 - e^-0.5 ≈ 0.393469340
-    // PDF = e^-0.5 ≈ 0.606530660
-    model._set("A1", "=EXPON.DIST(0.5, 1, TRUE)");
-    model._set("A2", "=EXPON.DIST(0.5, 1, FALSE)");
-
-    // Wrong number of args
-    model._set("A3", "=EXPON.DIST(0.5, 1)");
-    model._set("A4", "=EXPON.DIST(0.5, 1, TRUE, FALSE)");
-
-    // Domain errors
-    model._set("A5", "=EXPON.DIST(-1, 1, TRUE)"); // x < 0
-    model._set("A6", "=EXPON.DIST(0.5, 0, TRUE)"); // lambda <= 0
-
-    model.evaluate();
-
-    assert_eq!(model._get_text("A1"), *"0.39346934");
-    assert_eq!(model._get_text("A2"), *"0.60653066");
-
-    assert_eq!(model._get_text("A3"), *"#ERROR!");
-    assert_eq!(model._get_text("A4"), *"#ERROR!");
-    assert_eq!(model._get_text("A5"), *"#NUM!");
-    assert_eq!(model._get_text("A6"), *"#NUM!");
-}

base/src/test/statistical/test_fn_f.rs

@@ -1,75 +0,0 @@
-#![allow(clippy::unwrap_used)]
-
-use crate::test::util::new_empty_model;
-
-#[test]
-fn test_fn_f_dist_sanity() {
-    let mut model = new_empty_model();
-    model._set("A1", "=F.DIST(15, 6, 4, TRUE)");
-    model._set("A2", "=F.DIST(15, 6, 4, FALSE)");
-    model._set("A3", "=F.DIST(15, 6, 4)");
-    model._set("A4", "=F.DIST(15, 6, 4, TRUE, FALSE)");
-    model.evaluate();
-    assert_eq!(model._get_text("A1"), *"0.989741952");
-    assert_eq!(model._get_text("A2"), *"0.001271447");
-    assert_eq!(model._get_text("A3"), *"#ERROR!");
-    assert_eq!(model._get_text("A4"), *"#ERROR!");
-}
-
-#[test]
-fn test_fn_f_dist_rt_sanity() {
-    let mut model = new_empty_model();
-
-    // Valid call
-    model._set("A1", "=F.DIST.RT(15, 6, 4)");
-    // Too few args
-    model._set("A2", "=F.DIST.RT(15, 6)");
-    // Too many args
-    model._set("A3", "=F.DIST.RT(15, 6, 4, 1)");
-
-    model.evaluate();
-
-    assert_eq!(model._get_text("A1"), *"0.010258048");
-    assert_eq!(model._get_text("A2"), *"#ERROR!");
-    assert_eq!(model._get_text("A3"), *"#ERROR!");
-}
-
-#[test]
-fn test_fn_f_inv_sanity() {
-    let mut model = new_empty_model();
-
-    // Valid call: left-tail inverse
-    model._set("A1", "=F.INV(0.9897419523940, 6, 4)");
-
-    // Too many args
-    model._set("A2", "=F.INV(0.5, 6, 4, 2)");
-
-    // Too few args
-    model._set("A3", "=F.INV(0.5, 6)");
-
-    model.evaluate();
-
-    assert_eq!(model._get_text("A1"), *"15");
-    assert_eq!(model._get_text("A2"), *"#ERROR!");
-    assert_eq!(model._get_text("A3"), *"#ERROR!");
-}
-
-#[test]
-fn test_fn_f_inv_rt_sanity() {
-    let mut model = new_empty_model();
-
-    // Valid call: left-tail inverse
-    model._set("A1", "=F.INV.RT(0.0102580476059808, 6, 4)");
-
-    // Too many args
-    model._set("A2", "=F.INV.RT(0.5, 6, 4, 2)");
-
-    // Too few args
-    model._set("A3", "=F.INV.RT(0.5, 6)");
-
-    model.evaluate();
-
-    assert_eq!(model._get_text("A1"), *"15");
-    assert_eq!(model._get_text("A2"), *"#ERROR!");
-    assert_eq!(model._get_text("A3"), *"#ERROR!");
-}

base/src/test/statistical/test_fn_fisher.rs

@@ -1,53 +0,0 @@
-#![allow(clippy::unwrap_used)]
-
-use crate::test::util::new_empty_model;
-#[test]
-fn test_fn_fisher_smoke() {
-    let mut model = new_empty_model();
-
-    // Valid inputs
-    model._set("A1", "=FISHER(0.1)");
-    model._set("A2", "=FISHER(-0.5)");
-    model._set("A3", "=FISHER(0.8)");
-
-    // Domain errors: x <= -1 or x >= 1 -> #NUM!
-    model._set("A4", "=FISHER(1)");
-    model._set("A5", "=FISHER(-1)");
-    model._set("A6", "=FISHER(2)");
-
-    // Wrong number of arguments -> #ERROR!
-    model._set("A7", "=FISHER(0.1, 2)");
-
-    model.evaluate();
-
-    assert_eq!(model._get_text("A1"), *"0.100335348");
-    assert_eq!(model._get_text("A2"), *"-0.549306144");
-    assert_eq!(model._get_text("A3"), *"1.098612289");
-
-    assert_eq!(model._get_text("A4"), *"#NUM!");
-    assert_eq!(model._get_text("A5"), *"#NUM!");
-    assert_eq!(model._get_text("A6"), *"#NUM!");
-
-    assert_eq!(model._get_text("A7"), *"#ERROR!");
-}
-
-#[test]
-fn test_fn_fisher_inv_smoke() {
-    let mut model = new_empty_model();
-
-    // Valid inputs
-    model._set("A1", "=FISHERINV(-1.5)");
-    model._set("A2", "=FISHERINV(0.5)");
-    model._set("A3", "=FISHERINV(2)");
-
-    // Wrong number of arguments -> #ERROR!
-    model._set("A4", "=FISHERINV(0.5, 1)");
-
-    model.evaluate();
-
-    assert_eq!(model._get_text("A1"), *"-0.905148254");
-    assert_eq!(model._get_text("A2"), *"0.462117157");
-    assert_eq!(model._get_text("A3"), *"0.96402758");
-
-    assert_eq!(model._get_text("A4"), *"#ERROR!");
-}

base/src/test/statistical/test_fn_hyp_geom_dist.rs

@@ -1,42 +0,0 @@
-#![allow(clippy::unwrap_used)]
-
-use crate::test::util::new_empty_model;
-
-#[test]
-fn test_fn_hyp_geom_dist_smoke() {
-    let mut model = new_empty_model();
-
-    // Valid: PDF (non-cumulative)
-    model._set("A1", "=HYPGEOM.DIST(1, 4, 12, 20, FALSE)");
-
-    // Valid: CDF (cumulative)
-    model._set("A2", "=HYPGEOM.DIST(1, 4, 12, 20, TRUE)");
-
-    // Wrong number of arguments -> #ERROR!
-    model._set("A3", "=HYPGEOM.DIST(1, 4, 12, 20)");
-    model._set("A4", "=HYPGEOM.DIST(1, 4, 12, 20, TRUE, FALSE)");
-
-    // Domain errors:
-    // sample_s > number_sample -> #NUM!
-    model._set("A5", "=HYPGEOM.DIST(5, 4, 12, 20, TRUE)");
-
-    // population_s > number_pop -> #NUM!
-    model._set("A6", "=HYPGEOM.DIST(1, 4, 25, 20, TRUE)");
-
-    // number_sample > number_pop -> #NUM!
-    model._set("A7", "=HYPGEOM.DIST(1, 25, 12, 20, TRUE)");
-
-    model.evaluate();
-
-    // PDF: P(X = 1)
-    assert_eq!(model._get_text("A1"), *"0.13869969");
-
-    // CDF: P(X <= 1)
-    assert_eq!(model._get_text("A2"), *"0.153147575");
-
-    assert_eq!(model._get_text("A3"), *"#ERROR!");
-    assert_eq!(model._get_text("A4"), *"#ERROR!");
-    assert_eq!(model._get_text("A5"), *"#NUM!");
-    assert_eq!(model._get_text("A6"), *"#NUM!");
-    assert_eq!(model._get_text("A7"), *"#NUM!");
-}

base/src/test/statistical/test_fn_log_norm.rs

@@ -1,61 +0,0 @@
-#![allow(clippy::unwrap_used)]
-
-use crate::test::util::new_empty_model;
-
-#[test]
-fn test_fn_log_norm_dist_smoke() {
-    let mut model = new_empty_model();
-
-    // Valid: CDF and PDF
-    model._set("A1", "=LOGNORM.DIST(4, 3.5, 1.2, TRUE)");
-    model._set("A2", "=LOGNORM.DIST(4, 3.5, 1.2, FALSE)");
-
-    // Wrong number of arguments -> #ERROR!
-    model._set("A3", "=LOGNORM.DIST(4, 3.5, 1.2)");
-    model._set("A4", "=LOGNORM.DIST(4, 3.5, 1.2, TRUE, FALSE)");
-
-    // Domain errors:
-    // x <= 0 -> #NUM!
-    model._set("A5", "=LOGNORM.DIST(0, 3.5, 1.2, TRUE)");
-    // std_dev <= 0 -> #NUM!
-    model._set("A6", "=LOGNORM.DIST(4, 3.5, 0, TRUE)");
-
-    model.evaluate();
-
-    assert_eq!(model._get_text("A1"), *"0.039083556");
-    assert_eq!(model._get_text("A2"), *"0.017617597");
-
-    assert_eq!(model._get_text("A3"), *"#ERROR!");
-    assert_eq!(model._get_text("A4"), *"#ERROR!");
-    assert_eq!(model._get_text("A5"), *"#NUM!");
-    assert_eq!(model._get_text("A6"), *"#NUM!");
-}
-
-#[test]
-fn test_fn_log_norm_inv_smoke() {
-    let mut model = new_empty_model();
-
-    // Valid call
-    model._set("A1", "=LOGNORM.INV(0.5, 3.5, 1.2)");
-
-    // Wrong number of arguments -> #ERROR!
-    model._set("A2", "=LOGNORM.INV(0.5, 3.5)");
-    model._set("A3", "=LOGNORM.INV(0.5, 3.5, 1.2, 0)");
-
-    // Domain errors:
-    // probability <= 0 or >= 1 -> #NUM!
-    model._set("A4", "=LOGNORM.INV(0, 3.5, 1.2)");
-    model._set("A5", "=LOGNORM.INV(1, 3.5, 1.2)");
-    // std_dev <= 0 -> #NUM!
-    model._set("A6", "=LOGNORM.INV(0.5, 3.5, 0)");
-
-    model.evaluate();
-
-    assert_eq!(model._get_text("A1"), *"33.115451959");
-
-    assert_eq!(model._get_text("A2"), *"#ERROR!");
-    assert_eq!(model._get_text("A3"), *"#ERROR!");
-    assert_eq!(model._get_text("A4"), *"#NUM!");
-    assert_eq!(model._get_text("A5"), *"#NUM!");
-    assert_eq!(model._get_text("A6"), *"#NUM!");
-}

base/src/test/statistical/test_fn_norm_dist.rs

@@ -1,119 +0,0 @@
-#![allow(clippy::unwrap_used)]
-
-use crate::test::util::new_empty_model;
-
-#[test]
-fn test_fn_norm_dist_smoke() {
-    let mut model = new_empty_model();
-
-    // Valid: standard normal as a special case
-    model._set("A1", "=NORM.DIST(1, 0, 1, TRUE)");
-    model._set("A2", "=NORM.DIST(1, 0, 1, FALSE)");
-
-    // Wrong number of arguments -> #ERROR!
-    model._set("A3", "=NORM.DIST(1, 0, 1)");
-    model._set("A4", "=NORM.DIST(1, 0, 1, TRUE, FALSE)");
-
-    // Domain errors: standard_dev <= 0 -> #NUM!
-    model._set("A5", "=NORM.DIST(1, 0, 0, TRUE)");
-    model._set("A6", "=NORM.DIST(1, 0, -1, TRUE)");
-
-    model.evaluate();
-
-    assert_eq!(model._get_text("A1"), *"0.841344746");
-    assert_eq!(model._get_text("A2"), *"0.241970725");
-
-    assert_eq!(model._get_text("A3"), *"#ERROR!");
-    assert_eq!(model._get_text("A4"), *"#ERROR!");
-    assert_eq!(model._get_text("A5"), *"#NUM!");
-    assert_eq!(model._get_text("A6"), *"#NUM!");
-}
-
-#[test]
-fn test_fn_norm_inv_smoke() {
-    let mut model = new_empty_model();
-
-    // Valid: median of standard normal
-    model._set("A1", "=NORM.INV(0.5, 0, 1)");
-
-    // Wrong number of arguments -> #ERROR!
-    model._set("A2", "=NORM.INV(0.5, 0)");
-    model._set("A3", "=NORM.INV(0.5, 0, 1, 0)");
-
-    // Domain errors:
-    // probability <= 0 or >= 1 -> #NUM!
-    model._set("A4", "=NORM.INV(0, 0, 1)");
-    model._set("A5", "=NORM.INV(1, 0, 1)");
-    // standard_dev <= 0 -> #NUM!
-    model._set("A6", "=NORM.INV(0.5, 0, 0)");
-
-    model._set("A7", "=NORM.INV(0.7, 0.2, 1)");
-    model._set("A8", "=NORM.INV(0.7, 0.2, 5)");
-
-    model.evaluate();
-
-    assert_eq!(model._get_text("A1"), *"0");
-
-    assert_eq!(model._get_text("A2"), *"#ERROR!");
-    assert_eq!(model._get_text("A3"), *"#ERROR!");
-    assert_eq!(model._get_text("A4"), *"#NUM!");
-    assert_eq!(model._get_text("A5"), *"#NUM!");
-    assert_eq!(model._get_text("A6"), *"#NUM!");
-    assert_eq!(model._get_text("A7"), *"0.724400513");
-    assert_eq!(model._get_text("A8"), *"2.822002564");
-}
-
-#[test]
-fn test_fn_norm_s_dist_smoke() {
-    let mut model = new_empty_model();
-
-    // Valid: CDF and PDF at z = 0
-    model._set("A1", "=NORM.S.DIST(0, TRUE)");
-    model._set("A2", "=NORM.S.DIST(0, FALSE)");
-
-    // Wrong number of arguments -> #ERROR!
-    model._set("A3", "=NORM.S.DIST(0)");
-    model._set("A4", "=NORM.S.DIST(0, TRUE, FALSE)");
-
-    model._set("A5", "=NORM.S.DIST(0.2, FALSE)");
-    model._set("A6", "=NORM.S.DIST(2.2, TRUE)");
-
-    model.evaluate();
-
-    assert_eq!(model._get_text("A1"), *"0.5");
-    assert_eq!(model._get_text("A2"), *"0.39894228");
-
-    assert_eq!(model._get_text("A3"), *"#ERROR!");
-    assert_eq!(model._get_text("A4"), *"#ERROR!");
-
-    assert_eq!(model._get_text("A5"), *"0.391042694");
-    assert_eq!(model._get_text("A6"), *"0.986096552");
-}
-
-#[test]
-fn test_fn_norm_s_inv_smoke() {
-    let mut model = new_empty_model();
-
-    // Valid: symmetric points
-    model._set("A1", "=NORM.S.INV(0.5)");
-    model._set("A2", "=NORM.S.INV(0.841344746)");
-
-    // Wrong number of arguments -> #ERROR!
-    model._set("A3", "=NORM.S.INV()");
-    model._set("A4", "=NORM.S.INV(0.5, 0)");
-
-    // Domain errors: probability <= 0 or >= 1 -> #NUM!
-    model._set("A5", "=NORM.S.INV(0)");
-    model._set("A6", "=NORM.S.INV(1)");
-
-    model.evaluate();
-
-    assert_eq!(model._get_text("A1"), *"0");
-    // Approximately 1
-    assert_eq!(model._get_text("A2"), *"1");
-
-    assert_eq!(model._get_text("A3"), *"#ERROR!");
-    assert_eq!(model._get_text("A4"), *"#ERROR!");
-    assert_eq!(model._get_text("A5"), *"#NUM!");
-    assert_eq!(model._get_text("A6"), *"#NUM!");
-}

base/src/test/statistical/test_fn_pearson.rs

@@ -1,31 +0,0 @@
-#![allow(clippy::unwrap_used)]
-
-use crate::test::util::new_empty_model;
-
-#[test]
-fn test_fn_chisq_test_smoke() {
-    let mut model = new_empty_model();
-    model._set("A2", "48");
-    model._set("A3", "32");
-    model._set("A4", "12");
-    model._set("A5", "1");
-    model._set("A6", "'13");
-    model._set("A7", "TRUE");
-    model._set("A8", "1");
-    model._set("A9", "13");
-    model._set("A10", "15");
-
-    model._set("B2", "55");
-    model._set("B3", "34");
-    model._set("B4", "13");
-    model._set("B5", "blah");
-    model._set("B6", "13");
-    model._set("B7", "1");
-    model._set("B8", "TRUE");
-    model._set("B9", "'14");
-    model._set("B10", "16");
-
-    model._set("C1", "=PEARSON(A2:A10, B2:B10)");
-    model.evaluate();
-    assert_eq!(model._get_text("C1"), *"0.998381439");
-}

base/src/test/statistical/test_fn_phi.rs

@@ -1,26 +0,0 @@
-#![allow(clippy::unwrap_used)]
-
-use crate::test::util::new_empty_model;
-
-#[test]
-fn test_fn_phi_smoke() {
-    let mut model = new_empty_model();
-
-    model._set("A1", "=PHI(0)");
-    model._set("A2", "=PHI(1)");
-    model._set("A3", "=PHI(-1)");
-
-    // Wrong number of arguments -> #ERROR!
-    model._set("A4", "=PHI()");
-    model._set("A5", "=PHI(0, 1)");
-
-    model.evaluate();
-
-    // Standard values
-    assert_eq!(model._get_text("A1"), *"0.39894228");
-    assert_eq!(model._get_text("A2"), *"0.241970725");
-    assert_eq!(model._get_text("A3"), *"0.241970725");
-
-    assert_eq!(model._get_text("A4"), *"#ERROR!");
-    assert_eq!(model._get_text("A5"), *"#ERROR!");
-}

base/src/test/statistical/test_fn_poisson.rs

@@ -1,41 +0,0 @@
-#![allow(clippy::unwrap_used)]
-
-use crate::test::util::new_empty_model;
-
-#[test]
-fn test_fn_poisson_dist_smoke() {
-    let mut model = new_empty_model();
-
-    // λ = 2, x = 3
-    // P(X = 3)  ≈ 0.180447045
-    // P(X <= 3) ≈ 0.857123461
-    model._set("A1", "=POISSON.DIST(3, 2, FALSE)");
-    model._set("A2", "=POISSON.DIST(3, 2, TRUE)");
-
-    // Wrong arg count
-    model._set("A3", "=POISSON.DIST(3, 2)");
-    model._set("A4", "=POISSON.DIST(3, 2, TRUE, FALSE)");
-
-    // Domain errors
-    model._set("A5", "=POISSON.DIST(-1, 2, TRUE)"); // x < 0
-    model._set("A6", "=POISSON.DIST(3, -2, TRUE)"); // mean < 0
-
-    // λ = 0 special cases
-    model._set("A7", "=POISSON.DIST(0, 0, FALSE)"); // 1
-    model._set("A8", "=POISSON.DIST(1, 0, FALSE)"); // 0
-    model._set("A9", "=POISSON.DIST(5, 0, TRUE)"); // 1
-
-    model.evaluate();
-
-    assert_eq!(model._get_text("A1"), *"0.180447044");
-    assert_eq!(model._get_text("A2"), *"0.85712346");
-
-    assert_eq!(model._get_text("A3"), *"#ERROR!");
-    assert_eq!(model._get_text("A4"), *"#ERROR!");
-    assert_eq!(model._get_text("A5"), *"#NUM!");
-    assert_eq!(model._get_text("A6"), *"#NUM!");
-
-    assert_eq!(model._get_text("A7"), *"1");
-    assert_eq!(model._get_text("A8"), *"0");
-    assert_eq!(model._get_text("A9"), *"1");
-}

base/src/test/statistical/test_fn_stdev.rs

@@ -1,46 +0,0 @@
-#![allow(clippy::unwrap_used)]
-
-use crate::test::util::new_empty_model;
-
-#[test]
-fn smoke_test() {
-    let mut model = new_empty_model();
-    model._set("A1", "=STDEV.P(10, 12, 23, 23, 16, 23, 21)");
-    model._set("A2", "=STDEV.S(10, 12, 23, 23, 16, 23, 21)");
-    model.evaluate();
-
-    assert_eq!(model._get_text("A1"), *"5.174505793");
-
-    assert_eq!(model._get_text("A2"), *"5.589105048");
-}
-
-#[test]
-fn numbers() {
-    let mut model = new_empty_model();
-
-    model._set("A2", "24");
-    model._set("A3", "25");
-    model._set("A4", "27");
-    model._set("A5", "23");
-    model._set("A6", "45");
-    model._set("A7", "23.5");
-    model._set("A8", "34");
-    model._set("A9", "23");
-    model._set("A10", "23");
-    model._set("A11", "TRUE");
-    model._set("A12", "'23");
-    model._set("A13", "Text");
-    model._set("A14", "FALSE");
-    model._set("A15", "45");
-
-    model._set("B1", "=STDEV.P(A2:A15)");
-    model._set("B2", "=STDEV.S(A2:A15)");
-    model._set("B3", "=STDEVA(A2:A15)");
-    model._set("B4", "=STDEVPA(A2:A15)");
-    model.evaluate();
-
-    assert_eq!(model._get_text("B1"), *"8.483071378");
-    assert_eq!(model._get_text("B2"), *"8.941942369");
-    assert_eq!(model._get_text("B3"), *"15.499955689");
-    assert_eq!(model._get_text("B4"), *"14.936131032");
-}

base/src/test/statistical/test_fn_t_dist.rs

@@ -1,160 +0,0 @@
-#![allow(clippy::unwrap_used)]
-
-use crate::test::util::new_empty_model;
-
-#[test]
-fn test_fn_t_dist_smoke() {
-    let mut model = new_empty_model();
-
-    // Valid: cumulative (left-tail CDF)
-    model._set("A1", "=T.DIST(2, 10, TRUE)");
-    // Valid: probability density function (PDF)
-    model._set("B1", "=T.DIST(2, 10, FALSE)");
-
-    // Wrong number of arguments
-    model._set("A2", "=T.DIST(2, 10)");
-    model._set("A3", "=T.DIST(2, 10, TRUE, FALSE)");
-
-    // Domain error: df < 1 -> #NUM!
-    model._set("A4", "=T.DIST(2, 0, TRUE)");
-    model._set("A5", "=T.DIST(2, -1, TRUE)");
-
-    model.evaluate();
-
-    assert_eq!(model._get_text("A1"), *"0.963305983");
-    assert_eq!(model._get_text("B1"), *"0.061145766");
-
-    assert_eq!(model._get_text("A2"), *"#ERROR!");
-    assert_eq!(model._get_text("A3"), *"#ERROR!");
-    assert_eq!(model._get_text("A4"), *"#NUM!");
-    assert_eq!(model._get_text("A5"), *"#NUM!");
-}
-
-#[test]
-fn test_fn_t_dist_rt_smoke() {
-    let mut model = new_empty_model();
-
-    // Valid: right tail probability
-    model._set("A1", "=T.DIST.RT(2, 10)");
-
-    // Wrong number of arguments
-    model._set("A2", "=T.DIST.RT(2)");
-    model._set("A3", "=T.DIST.RT(2, 10, TRUE)");
-
-    // Domain error: df < 1
-    model._set("A4", "=T.DIST.RT(2, 0)");
-    model._set("A5", "=T.DIST.RT(2, -1)");
-
-    model.evaluate();
-
-    assert_eq!(model._get_text("A1"), *"0.036694017");
-
-    assert_eq!(model._get_text("A2"), *"#ERROR!");
-    assert_eq!(model._get_text("A3"), *"#ERROR!");
-    assert_eq!(model._get_text("A4"), *"#NUM!");
-    assert_eq!(model._get_text("A5"), *"#NUM!");
-}
-
-#[test]
-fn test_fn_t_dist_2t_smoke() {
-    let mut model = new_empty_model();
-
-    // Valid: two-tailed probability
-    model._set("A1", "=T.DIST.2T(2, 10)");
-
-    // In the limit case of x = 0, the two-tailed probability is 1.0
-    model._set("A4", "=T.DIST.2T(0, 10)");
-
-    // Wrong number of arguments
-    model._set("A2", "=T.DIST.2T(2)");
-    model._set("A3", "=T.DIST.2T(2, 10, TRUE)");
-
-    // Domain errors:
-    // x < 0 -> #NUM!
-    model._set("A5", "=T.DIST.2T(-0.001, 10)");
-    // df < 1 -> #NUM!
-    model._set("A6", "=T.DIST.2T(2, 0)");
-
-    model.evaluate();
-
-    assert_eq!(model._get_text("A1"), *"0.073388035");
-    assert_eq!(model._get_text("A4"), *"1");
-
-    assert_eq!(model._get_text("A2"), *"#ERROR!");
-    assert_eq!(model._get_text("A3"), *"#ERROR!");
-    assert_eq!(model._get_text("A5"), *"#NUM!");
-    assert_eq!(model._get_text("A6"), *"#NUM!");
-}
-
-#[test]
-fn test_fn_t_inv_smoke() {
-    let mut model = new_empty_model();
-
-    // Valid: upper and lower tail
-    model._set("A1", "=T.INV(0.95, 10)");
-    model._set("A2", "=T.INV(0.05, 10)");
-    // limit case:
-    model._set("B2", "=T.INV(0.95, 1)");
-
-    // Wrong number of arguments
-    model._set("A3", "=T.INV(0.95)");
-    model._set("A4", "=T.INV(0.95, 10, 1)");
-
-    // Domain errors:
-    // p <= 0 or >= 1
-    model._set("A5", "=T.INV(0, 10)");
-    model._set("A6", "=T.INV(1, 10)");
-    // df < 1
-    model._set("A7", "=T.INV(0.95, 0)");
-
-    model.evaluate();
-
-    assert_eq!(model._get_text("A1"), *"1.812461123");
-    assert_eq!(model._get_text("A2"), *"-1.812461123");
-    assert_eq!(model._get_text("B2"), *"6.313751515");
-
-    assert_eq!(model._get_text("A3"), *"#ERROR!");
-    assert_eq!(model._get_text("A4"), *"#ERROR!");
-    assert_eq!(model._get_text("A5"), *"#NUM!");
-    assert_eq!(model._get_text("A6"), *"#NUM!");
-    assert_eq!(model._get_text("A7"), *"#NUM!");
-}
-
-#[test]
-fn test_fn_t_inv_2t_smoke() {
-    let mut model = new_empty_model();
-
-    // Valid: two-tailed critical values
-    model._set("A1", "=T.INV.2T(0.1, 10)");
-    model._set("A2", "=T.INV.2T(0.05, 10)");
-
-    // p = 1 should give t = 0 (both tails outside are 1.0, so cut at the mean)
-    model._set("A3", "=T.INV.2T(1, 10)");
-
-    model._set("A7", "=T.INV.2T(1.5, 10)");
-
-    // Wrong number of arguments
-    model._set("A4", "=T.INV.2T(0.1)");
-    model._set("A5", "=T.INV.2T(0.1, 10, 1)");
-
-    // Domain errors:
-    // p <= 0 or p > 1
-    model._set("A6", "=T.INV.2T(0, 10)");
-    // df < 1
-    model._set("A8", "=T.INV.2T(0.1, 0)");
-
-    model.evaluate();
-
-    assert_eq!(model._get_text("A1"), *"1.812461123");
-    assert_eq!(model._get_text("A2"), *"2.228138852");
-    assert_eq!(model._get_text("A3"), *"0");
-
-    // NB: Excel returns -0.699812061 for T.INV.2T(1.5, 10)
-    // which seems inconsistent with its documented behavior
-    assert_eq!(model._get_text("A7"), *"#NUM!");
-
-    assert_eq!(model._get_text("A4"), *"#ERROR!");
-    assert_eq!(model._get_text("A5"), *"#ERROR!");
-    assert_eq!(model._get_text("A6"), *"#NUM!");
-    assert_eq!(model._get_text("A8"), *"#NUM!");
-}

base/src/test/statistical/test_fn_t_test.rs

@@ -1,41 +0,0 @@
-#![allow(clippy::unwrap_used)]
-use crate::test::util::new_empty_model;
-#[test]
-fn test_fn_t_test_smoke() {
-    let mut model = new_empty_model();
-    model._set("A2", "3");
-    model._set("A3", "4");
-    model._set("A4", "5");
-    model._set("A5", "6");
-    model._set("A6", "10");
-    model._set("A7", "3");
-    model._set("A8", "2");
-    model._set("A9", "4");
-    model._set("A10", "7");
-
-    model._set("B2", "6");
-    model._set("B3", "19");
-    model._set("B4", "3");
-    model._set("B5", "2");
-    model._set("B6", "13");
-    model._set("B7", "4");
-    model._set("B8", "5");
-    model._set("B9", "17");
-    model._set("B10", "3");
-
-    model._set("C1", "=T.TEST(A2:A10, B2:B10, 1, 1)");
-    model._set("C2", "=T.TEST(A2:A10, B2:B10, 1, 2)");
-    model._set("C3", "=T.TEST(A2:A10, B2:B10, 1, 3)");
-    model._set("C4", "=T.TEST(A2:A10, B2:B10, 2, 1)");
-    model._set("C5", "=T.TEST(A2:A10, B2:B10, 2, 2)");
-    model._set("C6", "=T.TEST(A2:A10, B2:B10, 2, 3)");
-
-    model.evaluate();
-
-    assert_eq!(model._get_text("C1"), *"0.103836888");
-    assert_eq!(model._get_text("C2"), *"0.100244599");
-    assert_eq!(model._get_text("C3"), *"0.105360319");
-    assert_eq!(model._get_text("C4"), *"0.207673777");
-    assert_eq!(model._get_text("C5"), *"0.200489197");
-    assert_eq!(model._get_text("C6"), *"0.210720639");
-}

base/src/test/statistical/test_fn_var.rs

@@ -1,46 +0,0 @@
-#![allow(clippy::unwrap_used)]
-
-use crate::test::util::new_empty_model;
-
-#[test]
-fn smoke_test() {
-    let mut model = new_empty_model();
-    model._set("A1", "=STDEV.P(10, 12, 23, 23, 16, 23, 21)");
-    model._set("A2", "=STDEV.S(10, 12, 23, 23, 16, 23, 21)");
-    model.evaluate();
-
-    assert_eq!(model._get_text("A1"), *"5.174505793");
-
-    assert_eq!(model._get_text("A2"), *"5.589105048");
-}
-
-#[test]
-fn numbers() {
-    let mut model = new_empty_model();
-
-    model._set("A2", "24");
-    model._set("A3", "25");
-    model._set("A4", "27");
-    model._set("A5", "23");
-    model._set("A6", "45");
-    model._set("A7", "23.5");
-    model._set("A8", "34");
-    model._set("A9", "23");
-    model._set("A10", "23");
-    model._set("A11", "TRUE");
-    model._set("A12", "'23");
-    model._set("A13", "Text");
-    model._set("A14", "FALSE");
-    model._set("A15", "45");
-
-    model._set("B1", "=VAR.P(A2:A15)");
-    model._set("B2", "=VAR.S(A2:A15)");
-    model._set("B3", "=VARA(A2:A15)");
-    model._set("B4", "=VARPA(A2:A15)");
-    model.evaluate();
-
-    assert_eq!(model._get_text("B1"), *"71.9625");
-    assert_eq!(model._get_text("B2"), *"79.958333333");
-    assert_eq!(model._get_text("B3"), *"240.248626374");
-    assert_eq!(model._get_text("B4"), *"223.088010204");
-}

base/src/test/statistical/test_fn_weibull.rs

@@ -1,41 +0,0 @@
-#![allow(clippy::unwrap_used)]
-
-use crate::test::util::new_empty_model;
-
-#[test]
-fn test_fn_weibull_dist_smoke() {
-    let mut model = new_empty_model();
-
-    // Valid: CDF and PDF for x = 1, alpha = 2, beta = 1
-    model._set("A1", "=WEIBULL.DIST(1, 2, 1, TRUE)");
-    model._set("A2", "=WEIBULL.DIST(1, 2, 1, FALSE)");
-
-    // Wrong number of arguments -> #ERROR!
-    model._set("A3", "=WEIBULL.DIST(1, 2, 1)");
-    model._set("A4", "=WEIBULL.DIST(1, 2, 1, TRUE, FALSE)");
-
-    // Domain errors:
-    // x < 0  -> #NUM!
-    model._set("A5", "=WEIBULL.DIST(-1, 2, 1, TRUE)");
-    // alpha <= 0 -> #NUM!
-    model._set("A6", "=WEIBULL.DIST(1, 0, 1, TRUE)");
-    model._set("A7", "=WEIBULL.DIST(1, -1, 1, TRUE)");
-    // beta <= 0 -> #NUM!
-    model._set("A8", "=WEIBULL.DIST(1, 2, 0, TRUE)");
-    model._set("A9", "=WEIBULL.DIST(1, 2, -1, TRUE)");
-
-    model.evaluate();
-
-    // 1 - e^-1
-    assert_eq!(model._get_text("A1"), *"0.632120559");
-    // 2 * e^-1
-    assert_eq!(model._get_text("A2"), *"0.735758882");
-
-    assert_eq!(model._get_text("A3"), *"#ERROR!");
-    assert_eq!(model._get_text("A4"), *"#ERROR!");
-    assert_eq!(model._get_text("A5"), *"#NUM!");
-    assert_eq!(model._get_text("A6"), *"#NUM!");
-    assert_eq!(model._get_text("A7"), *"#NUM!");
-    assert_eq!(model._get_text("A8"), *"#NUM!");
-    assert_eq!(model._get_text("A9"), *"#NUM!");
-}

base/src/test/statistical/test_fn_z_test.rs

@@ -1,36 +0,0 @@
-#![allow(clippy::unwrap_used)]
-
-use crate::test::util::new_empty_model;
-
-#[test]
-fn test_fn_z_test_smoke() {
-    let mut model = new_empty_model();
-    model._set("A2", "3");
-    model._set("A3", "6");
-    model._set("A4", "7");
-    model._set("A5", "8");
-    model._set("A6", "6");
-    model._set("A7", "5");
-    model._set("A8", "4");
-    model._set("A9", "2");
-    model._set("A10", "1");
-    model._set("A11", "9");
-
-    model._set("G1", "=Z.TEST(A2:A11, 4)");
-    model._set("G2", "=Z.TEST(A2:A11, 6)");
-    model.evaluate();
-
-    assert_eq!(model._get_text("G1"), *"0.090574197");
-    assert_eq!(model._get_text("G2"), *"0.863043389");
-}
-
-#[test]
-fn arrays() {
-    let mut model = new_empty_model();
-    model._set("D1", "=Z.TEST({5,2,3,4}, 4, 123)");
-    model._set("D2", "=Z.TEST({5,2,3,4}, 4)");
-    model.evaluate();
-
-    assert_eq!(model._get_text("D1"), *"0.503243397");
-    assert_eq!(model._get_text("D2"), *"0.780710987");
-}

base/src/test/test_combin_combina

@@ -11,8 +11,8 @@ fn arguments() {
     model._set("A4", "=COMBINA()");
     model._set("A5", "=COMBIN(2)");
     model._set("A6", "=COMBINA(2)");
-    model._set("A7", "=COMBIN(1, 2, 3)");
-    model._set("A8", "=COMBINA(1, 2, 3)");
+    model._set("A5", "=COMBIN(1, 2, 3)");
+    model._set("A6", "=COMBINA(1, 2, 3)");
 
     model.evaluate();
 

base/src/test/test_fn_datevalue_timevalue.rs

@@ -7,8 +7,8 @@ fn datevalue_timevalue_arguments() {
     let mut model = new_empty_model();
     model._set("A1", "=DATEVALUE()");
     model._set("A2", "=TIMEVALUE()");
-    model._set("A3", "=DATEVALUE(\"2000-01-01\")");
-    model._set("A4", "=TIMEVALUE(\"12:00:00\")");
+    model._set("A3", "=DATEVALUE("2000-01-01")")
+    model._set("A4", "=TIMEVALUE("12:00:00")")
     model._set("A5", "=DATEVALUE(1,2)");
     model._set("A6", "=TIMEVALUE(1,2)");
     model.evaluate();
@@ -20,3 +20,5 @@ fn datevalue_timevalue_arguments() {
     assert_eq!(model._get_text("A5"), *"#ERROR!");
     assert_eq!(model._get_text("A6"), *"#ERROR!");
 }
+
+

base/src/test/test_fn_fact.rs

@@ -1,29 +0,0 @@
-#![allow(clippy::unwrap_used)]
-
-use crate::test::util::new_empty_model;
-
-#[test]
-fn large_numbers() {
-    let mut model = new_empty_model();
-    model._set("A1", "=FACT(170)");
-    model._set("A2", "=FACTDOUBLE(36)");
-
-    model._set("B1", "=FACT(6)");
-    model._set("B2", "=FACTDOUBLE(6)");
-
-    model._set("C3", "=FACTDOUBLE(15)");
-
-    model._set("F3", "=FACT(-0.1)");
-    model._set("F4", "=FACT(0)");
-
-    model.evaluate();
-
-    assert_eq!(model._get_text("A1"), *"7.25742E+306");
-    assert_eq!(model._get_text("A2"), *"1.67834E+21");
-    assert_eq!(model._get_text("B1"), *"720");
-    assert_eq!(model._get_text("B2"), *"48");
-    assert_eq!(model._get_text("C3"), *"2027025");
-
-    assert_eq!(model._get_text("F3"), *"#NUM!");
-    assert_eq!(model._get_text("F4"), *"1");
-}

webapp/IronCalc/src/components/SheetTabBar/SheetTabBar.tsx

@@ -1,11 +1,12 @@
 import { styled, Tooltip } from "@mui/material";
-import { Menu, Plus } from "lucide-react";
+import { EllipsisVertical, Menu, Plus } from "lucide-react";
 import { useState } from "react";
 import { useTranslation } from "react-i18next";
 import { IronCalcLogo } from "../../icons";
 import { theme } from "../../theme";
 import { NAVIGATION_HEIGHT } from "../constants";
 import { StyledButton } from "../Toolbar/Toolbar";
+import WorkbookSettingsDialog from "../WorkbookSettings/WorkbookSettingsDialog";
 import type { WorkbookState } from "../workbookState";
 import SheetListMenu from "./SheetListMenu";
 import SheetTab from "./SheetTab";
@@ -21,12 +22,16 @@ export interface SheetTabBarProps {
   onSheetRenamed: (name: string) => void;
   onSheetDeleted: () => void;
   onHideSheet: () => void;
+  onOpenWorkbookSettings: () => void;
+  initialLocale: string;
+  initialTimezone: string;
 }
 
 function SheetTabBar(props: SheetTabBarProps) {
   const { t } = useTranslation();
   const { workbookState, onSheetSelected, sheets, selectedIndex } = props;
   const [anchorEl, setAnchorEl] = useState<null | HTMLButtonElement>(null);
+  const [workbookSettingsOpen, setWorkbookSettingsOpen] = useState(false);
   const open = Boolean(anchorEl);
   const handleClick = (event: React.MouseEvent<HTMLButtonElement>) => {
     setAnchorEl(event.currentTarget);
@@ -95,6 +100,17 @@ function SheetTabBar(props: SheetTabBarProps) {
             <IronCalcLogo />
           </LogoLink>
         </Tooltip>
+        <Tooltip title={t("workbook_settings.open_settings")}>
+          <StyledButton
+            $pressed={false}
+            onClick={() => {
+              setWorkbookSettingsOpen(true);
+              props.onOpenWorkbookSettings();
+            }}
+          >
+            <EllipsisVertical />
+          </StyledButton>
+        </Tooltip>
       </RightContainer>
       <SheetListMenu
         anchorEl={anchorEl}
@@ -107,6 +123,12 @@ function SheetTabBar(props: SheetTabBarProps) {
         }}
         selectedIndex={selectedIndex}
       />
+      <WorkbookSettingsDialog
+        open={workbookSettingsOpen}
+        onClose={() => setWorkbookSettingsOpen(false)}
+        initialLocale={props.initialLocale}
+        initialTimezone={props.initialTimezone}
+      />
     </Container>
   );
 }
@@ -170,22 +192,28 @@ const RightContainer = styled("a")`
   color: ${theme.palette.primary.main};
   height: 100%;
   padding: 0px 8px;
-  @media (max-width: 769px) {
-    display: none;
-  }
+  gap: 4px;
 `;
 
 const LogoLink = styled("div")`
   display: flex;
   align-items: center;
-  padding: 8px;
+  padding: 0px 4px;
   border-radius: 4px;
+  max-height: 24px;
+  min-height: 24px;
+  cursor: pointer;
   svg {
     height: 14px;
     width: auto;
   }
   &:hover {
     background-color: ${theme.palette.grey["100"]};
+    transition: "all 0.2s";
+    outline: 1px solid ${theme.palette.grey["200"]};
+  }
+  @media (max-width: 769px) {
+    display: none;
   }
 `;
 

webapp/IronCalc/src/components/WorkbookSettings/WorkbookSettingsDialog.tsx

@@ -0,0 +1,429 @@
+import styled from "@emotion/styled";
+import {
+  Autocomplete,
+  Box,
+  Dialog,
+  FormControl,
+  MenuItem,
+  Select,
+  TextField,
+} from "@mui/material";
+import { Check, X } from "lucide-react";
+import { useState } from "react";
+import { useTranslation } from "react-i18next";
+import { theme } from "../../theme";
+
+type WorkbookSettingsDialogProps = {
+  open: boolean;
+  onClose: () => void;
+  initialLocale: string;
+  initialTimezone: string;
+  onSave?: (locale: string, timezone: string) => void;
+};
+
+const WorkbookSettingsDialog = (properties: WorkbookSettingsDialogProps) => {
+  const { t } = useTranslation();
+  const locales = ["en-US", "en-GB", "de-DE", "fr-FR", "es-ES"];
+  const timezones = [
+    "Berlin, Germany (GMT+1)",
+    "New York, USA (GMT-5)",
+    "Tokyo, Japan (GMT+9)",
+    "London, UK (GMT+0)",
+    "Sydney, Australia (GMT+10)",
+  ];
+  const [selectedLocale, setSelectedLocale] = useState<string>(
+    properties.initialLocale && locales.includes(properties.initialLocale)
+      ? properties.initialLocale
+      : locales[0],
+  );
+  const [selectedTimezone, setSelectedTimezone] = useState<string>(
+    properties.initialTimezone && timezones.includes(properties.initialTimezone)
+      ? properties.initialTimezone
+      : timezones[0],
+  );
+
+  const handleSave = () => {
+    if (properties.onSave && selectedLocale && selectedTimezone) {
+      properties.onSave(selectedLocale, selectedTimezone);
+    }
+    properties.onClose();
+  };
+
+  // Ensure selectedLocale is always a valid locale
+  const validSelectedLocale =
+    selectedLocale && locales.includes(selectedLocale)
+      ? selectedLocale
+      : locales[0];
+
+  // Ensure selectedTimezone is always a valid timezone
+  const validSelectedTimezone =
+    selectedTimezone && timezones.includes(selectedTimezone)
+      ? selectedTimezone
+      : timezones[0];
+
+  return (
+    <StyledDialog
+      open={properties.open}
+      onClose={(_event, reason) => {
+        if (reason === "backdropClick" || reason === "escapeKeyDown") {
+          properties.onClose();
+        }
+      }}
+    >
+      <StyledDialogTitle>
+        {t("workbook_settings.title")}
+        <Cross
+          onClick={properties.onClose}
+          tabIndex={0}
+          onKeyDown={(event) => {
+            if (event.key === "Enter") {
+              properties.onClose();
+            }
+          }}
+        >
+          <X />
+        </Cross>
+      </StyledDialogTitle>
+
+      <StyledDialogContent
+        onClick={(event) => event.stopPropagation()}
+        onMouseDown={(event) => event.stopPropagation()}
+      >
+        <StyledSectionTitle>
+          {t("workbook_settings.locale_and_timezone.title")}
+        </StyledSectionTitle>
+        <FieldWrapper>
+          <StyledLabel htmlFor="locale">
+            {t("workbook_settings.locale_and_timezone.locale_label")}
+          </StyledLabel>
+          <FormControl fullWidth>
+            <StyledSelect
+              id="locale"
+              value={validSelectedLocale}
+              onChange={(event) => {
+                setSelectedLocale(event.target.value as string);
+              }}
+              MenuProps={{
+                PaperProps: {
+                  sx: menuPaperStyles,
+                },
+                TransitionProps: {
+                  timeout: 0,
+                },
+              }}
+            >
+              {locales.map((locale) => (
+                <StyledMenuItem
+                  key={locale}
+                  value={locale}
+                  $isSelected={locale === selectedLocale}
+                >
+                  {locale}
+                </StyledMenuItem>
+              ))}
+            </StyledSelect>
+            <HelperBox>
+              <Row>
+                {t("workbook_settings.locale_and_timezone.locale_example1")}
+                <RowValue>1,234.56</RowValue>
+              </Row>
+              <Row>
+                {t("workbook_settings.locale_and_timezone.locale_example2")}
+                <RowValue>12/31/2025</RowValue>
+              </Row>
+              <Row>
+                {t("workbook_settings.locale_and_timezone.locale_example3")}
+                <RowValue>11/23/2025 09:21:06 PM</RowValue>
+              </Row>
+              <Row>
+                {t("workbook_settings.locale_and_timezone.locale_example4")}
+                <RowValue>Monday</RowValue>
+              </Row>
+            </HelperBox>
+          </FormControl>
+        </FieldWrapper>
+        <FieldWrapper>
+          <StyledLabel htmlFor="timezone">
+            {t("workbook_settings.locale_and_timezone.timezone_label")}
+          </StyledLabel>
+          <FormControl fullWidth>
+            <StyledAutocomplete
+              id="timezone"
+              value={validSelectedTimezone}
+              onChange={(_event, newValue) => {
+                setSelectedTimezone((newValue as string) || "");
+              }}
+              options={timezones}
+              renderInput={(params) => <TextField {...params} />}
+              renderOption={(props, option) => (
+                <StyledMenuItem
+                  {...props}
+                  key={option as string}
+                  $isSelected={option === validSelectedTimezone}
+                >
+                  {option as string}
+                </StyledMenuItem>
+              )}
+              disableClearable
+              slotProps={{
+                paper: {
+                  sx: menuPaperStyles,
+                },
+                popper: {
+                  sx: {
+                    "& .MuiAutocomplete-paper": {
+                      transition: "none !important",
+                    },
+                  },
+                },
+                popupIndicator: {
+                  disableRipple: true,
+                },
+              }}
+            />
+            <HelperBox>
+              <Row>
+                {t("workbook_settings.locale_and_timezone.timezone_example1")}
+                <RowValue>23/11/2025</RowValue>
+              </Row>
+              <Row>
+                {t("workbook_settings.locale_and_timezone.timezone_example2")}
+                <RowValue>11/23/2025 09:21:06 PM</RowValue>
+              </Row>
+            </HelperBox>
+          </FormControl>
+        </FieldWrapper>
+      </StyledDialogContent>
+
+      <DialogFooter>
+        <StyledButton onClick={handleSave} tabIndex={0}>
+          <Check
+            style={{ width: "16px", height: "16px", marginRight: "8px" }}
+          />
+          {t("num_fmt.save")}
+        </StyledButton>
+      </DialogFooter>
+    </StyledDialog>
+  );
+};
+
+const StyledDialog = styled(Dialog)`
+  & .MuiPaper-root {
+    max-width: 320px;
+    width: 320px;
+    min-width: 280px;
+    border-radius: 8px;
+    padding: 0px;
+  }
+`;
+
+const StyledDialogTitle = styled("div")`
+  display: flex;
+  align-items: center;
+  height: 44px;
+  font-size: 14px;
+  font-weight: 500;
+  font-family: Inter;
+  padding: 0px 12px;
+  justify-content: space-between;
+  border-bottom: 1px solid ${theme.palette.grey["300"]};
+`;
+
+const Cross = styled("div")`
+  &:hover {
+    background-color: ${theme.palette.grey["50"]};
+  }
+  display: flex;
+  border-radius: 4px;
+  height: 24px;
+  width: 24px;
+  cursor: pointer;
+  align-items: center;
+  justify-content: center;
+  svg {
+    width: 16px;
+    height: 16px;
+    stroke-width: 1.5;
+  }
+`;
+
+const StyledDialogContent = styled("div")`
+  display: flex;
+  flex-direction: column;
+  gap: 12px;
+  font-size: 12px;
+  margin: 12px;
+`;
+
+const StyledSectionTitle = styled("h1")`
+  font-size: 14px;
+  font-weight: 600;
+  font-family: Inter;
+  margin: 0px;
+  color: ${theme.palette.text.primary};
+`;
+
+const StyledSelect = styled(Select)`
+  font-size: 12px;
+  height: 32px;
+  & .MuiInputBase-root {
+    padding: 0px !important;
+  }
+  & .MuiInputBase-input {
+    font-size: 12px;
+    height: 20px;
+    padding-right: 0px !important;
+    margin: 0px;
+  }
+  & .MuiSelect-select {
+    padding: 8px 32px 8px 8px !important;
+    font-size: 12px;
+  }
+  & .MuiSvgIcon-root {
+    right: 4px !important;
+  }
+`;
+
+const HelperBox = styled("div")`
+  display: flex;
+  flex-direction: column;
+  align-items: start;
+  justify-content: center;
+  gap: 2px;
+  box-sizing: border-box;
+  border: 1px solid ${theme.palette.grey["300"]};
+  font-family: Inter;
+  width: 100%;
+  height: 100%;
+  margin-top: 8px;
+  background-color: ${theme.palette.grey["100"]};
+  border-radius: 4px;
+  padding: 8px;
+`;
+
+const Row = styled("div")`
+  display: flex;
+  flex-direction: row;
+  gap: 4px;
+  width: 100%;
+  justify-content: space-between;
+  color: ${theme.palette.grey[700]};
+`;
+
+const RowValue = styled("span")`
+  font-size: 12px;
+  font-family: Inter;
+  font-weight: normal;
+  color: ${theme.palette.grey[500]};
+`;
+
+const StyledAutocomplete = styled(Autocomplete)`
+  & .MuiInputBase-root {
+    padding: 0px !important;
+    height: 32px;
+  }
+  & .MuiInputBase-input {
+    font-size: 12px;
+    height: 20px;
+    padding: 0px;
+    padding-right: 0px !important;
+    margin: 0px;
+  }
+  & .MuiAutocomplete-popupIndicator:hover {
+    background-color: transparent !important;
+  }
+  & .MuiAutocomplete-popupIndicator {
+    & .MuiTouchRipple-root {
+      display: none;
+    }
+  }
+  & .MuiOutlinedInput-root .MuiAutocomplete-endAdornment {
+    right: 4px;
+  }
+  & .MuiOutlinedInput-root .MuiAutocomplete-input {
+    padding: 8px !important;
+  }
+`;
+
+const menuPaperStyles = {
+  boxSizing: "border-box",
+  marginTop: "4px",
+  padding: "4px",
+  borderRadius: "8px",
+  transition: "none !important",
+  "& .MuiList-padding": {
+    padding: 0,
+  },
+  "& .MuiList-root": {
+    padding: 0,
+  },
+  "& .MuiAutocomplete-noOptions": {
+    padding: "8px",
+    fontSize: "12px",
+    fontFamily: "Inter",
+  },
+  "& .MuiMenuItem-root": {
+    height: "32px !important",
+    padding: "8px !important",
+    minHeight: "32px !important",
+  },
+};
+
+const StyledMenuItem = styled(MenuItem)<{ $isSelected?: boolean }>`
+  padding: 8px !important;
+  height: 32px !important;
+  min-height: 32px !important;
+  border-radius: 4px;
+  display: flex;
+  align-items: center;
+  font-size: 12px;
+  background-color: ${({ $isSelected }) =>
+    $isSelected ? theme.palette.grey[50] : "transparent"} !important;
+  &:hover {
+    background-color: ${theme.palette.grey[50]} !important;
+  }
+`;
+
+const FieldWrapper = styled(Box)`
+  display: flex;
+  flex-direction: column;
+  width: 100%;
+  gap: 6px;
+`;
+
+const StyledLabel = styled("label")`
+  font-size: 12px;
+  font-family: "Inter";
+  font-weight: 500;
+  color: ${theme.palette.text.primary};
+  display: block;
+`;
+
+const DialogFooter = styled("div")`
+  color: ${theme.palette.grey[700]};
+  display: flex;
+  align-items: center;
+  border-top: 1px solid ${theme.palette.grey["300"]};
+  font-family: Inter;
+  justify-content: flex-end;
+  padding: 12px;
+`;
+
+const StyledButton = styled("div")`
+  cursor: pointer;
+  color: ${theme.palette.common.white};
+  background: ${theme.palette.primary.main};
+  padding: 0px 10px;
+  height: 36px;
+  line-height: 36px;
+  border-radius: 4px;
+  display: flex;
+  align-items: center;
+  font-family: "Inter";
+  font-size: 14px;
+  &:hover {
+    background: ${theme.palette.primary.dark};
+  }
+`;
+
+export default WorkbookSettingsDialog;

webapp/IronCalc/src/locale/en_us.json

@@ -164,5 +164,21 @@
   "right_drawer": {
     "close": "Close",
     "resize_drawer": "Resize drawer"
+  },
+  "workbook_settings": {
+    "open_settings": "Open settings",
+    "title": "Workbook Settings",
+    "close": "Close dialog",
+    "locale_and_timezone": {
+      "title": "Locale & Timezone",
+      "locale_label": "Locale",
+      "locale_example1": "Number",
+      "locale_example2": "Date",
+      "locale_example3": "Date and Time",
+      "locale_example4": "First day of the week",
+      "timezone_label": "Timezone",
+      "timezone_example1": "TODAY()",
+      "timezone_example2": "NOW()"
+    }
   }
 }

xlsx/tests/test.rs

@@ -373,45 +373,6 @@ fn test_xlsx() {
     );
 }
 
-#[test]
-fn test_statistical_xlsx() {
-    let mut entries = fs::read_dir("tests/statistical/")
-        .unwrap()
-        .map(|res| res.map(|e| e.path()))
-        .collect::<Result<Vec<_>, io::Error>>()
-        .unwrap();
-    entries.sort();
-    let temp_folder = env::temp_dir();
-    let path = format!("{}", Uuid::new_v4());
-    let dir = temp_folder.join(path);
-    fs::create_dir(&dir).unwrap();
-    let mut is_error = false;
-    for file_path in entries {
-        let file_name_str = file_path.file_name().unwrap().to_str().unwrap();
-        let file_path_str = file_path.to_str().unwrap();
-        println!("Testing file: {file_path_str}");
-        if file_name_str.ends_with(".xlsx") && !file_name_str.starts_with('~') {
-            if let Err(message) = test_file(file_path_str) {
-                println!("Error with file: '{file_path_str}'");
-                println!("{message}");
-                is_error = true;
-            }
-            let t = test_load_and_saving(file_path_str, &dir);
-            if t.is_err() {
-                println!("Error while load and saving file: {file_path_str}");
-                is_error = true;
-            }
-        } else {
-            println!("skipping");
-        }
-    }
-    fs::remove_dir_all(&dir).unwrap();
-    assert!(
-        !is_error,
-        "Models were evaluated inconsistently with XLSX data."
-    );
-}
-
 #[test]
 fn no_export() {
     let mut entries = fs::read_dir("tests/calc_test_no_export/")