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126 Commits

Author SHA1 Message Date
Daniel
80a48cef27 fix: support multiline 2025-12-06 23:07:23 +01:00
Daniel
d8329676ca update: add a function to manage row height on font increase 2025-12-06 23:07:23 +01:00
Nicolás Hatcher
f96612cf23 FIX: NOW test cases 2025-11-28 20:52:34 +01:00
Nicolás Hatcher
745435b950 FIX: Copilot requests 2025-11-28 20:52:34 +01:00
Nicolás Hatcher
4ca996cd3f UPDATE(easter egg): Add an argument for NOW
This shows the time in different timezones
2025-11-28 20:52:34 +01:00
Elsa Minsut
3fbb91c414 fix: deletes old xlsx test with failing cases 2025-11-28 20:26:34 +01:00
Elsa Minsut
93c9c42607 fix: uploads xlsx tests split per function 2025-11-28 20:26:34 +01:00
Elsa Minsut
11edc2378e fix: deletes old test file and replaces it with detailed one 2025-11-28 20:26:34 +01:00
Elsa Minsut
962e70c834 fix: adds new line at end of file 2025-11-28 20:26:34 +01:00
Elsa Minsut
f803dad0a3 fix: updates test to remove failing edge cases 2025-11-28 20:26:34 +01:00
Elsa Minsut
19580fc1ad update: warning message shows the function as implemented 2025-11-28 20:26:34 +01:00
Elsa Minsut
e760b2d08e update: sets status as available for implemented functions 2025-11-28 20:26:34 +01:00
Elsa Minsut
0e6ded7154 update: adds unit test for CELL, INFO, N and SHEETS 2025-11-28 20:26:34 +01:00
Elsa Minsut
db26403432 docs: available status for implemented functions 2025-11-28 20:23:52 +01:00
Elsa Minsut
9193479cce update: adds xlsx test for SUMSQ 2025-11-28 20:23:52 +01:00
Elsa Minsut
f814a75ae5 update: adds unit test for SUMSQ 2025-11-28 20:23:52 +01:00
Elsa Minsut
c8da5efb5f update: removes old xlsx test file 2025-11-28 20:23:52 +01:00
Daniel
522e734395 update: use different header styling for full column or row selection 2025-11-28 20:10:24 +01:00
tolgakaan12
2a7d59e512 FIX: Floating-point precision bug in FLOOR functions
Fixes #571

- Add EXCEL_PRECISION constant (15 significant digits)
- Fix FLOOR(7.1, 0.1) returning 7.0 instead of 7.1
- Apply to_excel_precision to ratio before floor/ceil operations
- Affects FLOOR, FLOOR.MATH, and FLOOR.PRECISE functions
- Add test_floor with 6 test cases
2025-11-28 20:05:31 +01:00
Nicolás Hatcher
c4142d4bf8 UPDATE: Adds 12 more statistical functions:
* GAUSS
* HARMEAN
* KURT
* MAXA
* MEDIAN
* MINA
* RANK.EQ
* RANK.AVG
* SKEW
* SKEW.P
* SMALL
* LARGE
2025-11-28 19:55:43 +01:00
Daniel González-Albo
885d344b5b Merge pull request #581 from blueboy93/column-documentation
Edited Column Documentation
2025-11-27 23:44:18 +01:00
Tom
bed6f007cd FIX: Typos adjusted. Thanks Elsa! 2025-11-27 20:26:28 +01:00
Tom
dbd1b2df60 FIX: Edits after Elsa's review and further tests 2025-11-27 18:49:32 +01:00
Nicolás Hatcher
8597d14a4e UPDATE: Implements CORREL, SLOPE, INTERCEPT, RSQ and STEYX
These are all functions that follow a very simmilar path code
2025-11-26 22:33:49 +01:00
Nicolás Hatcher
01b19b9c35 FIX: Add comments. Thank you copilot! 2025-11-26 20:09:58 +01:00
Nicolás Hatcher
4649a0c78c UPDATE: Adds SUMX2MY2, SUMX2PY2 and SUMXMY2 mathematical functions 2025-11-26 20:09:58 +01:00
Daniel González-Albo
cd0baf5ba7 Merge pull request #591 from ironcalc/dani/app/mobile-adjustments
fix: mobile issues in app
2025-11-26 00:51:08 +01:00
Daniel
167d169f1a chore: use a constant instead of a number 2025-11-26 00:44:06 +01:00
Nicolás Hatcher
080574b112 UPDATE: Implement FTEST function 2025-11-26 00:30:37 +01:00
Daniel
6056b8f122 fix: mobile issues 2025-11-26 00:01:12 +01:00
Nicolás Hatcher
e61b15655a UPDATE: Adds a bunch of tests 2025-11-25 01:20:03 +01:00
Nicolás Hatcher
6822505602 UPDATE: Adds 56 functions in the Statistical section
Uses statrs for numerical functions

REFACTOR: Put statistical functions on its own module

This might seem counter-intuitive but the wasm build after this refactor
is 1528 bytes smaller :)
2025-11-25 01:20:03 +01:00
Tom
25f7891343 FIX: added missing comma (Thanks copilot!) 2025-11-24 18:36:58 +01:00
Tom
bdd0af0a39 FIX: Fix mispelled word (Thanks Copilot) 2025-11-24 18:27:38 +01:00
Tom
261924396d Edited Column Documentation 2025-11-24 18:12:34 +01:00
Nicolás Hatcher
67ef3bcf87 FIX: Correct number of arguments for functions 2025-11-23 21:02:59 +01:00
Daniel González-Albo
9aac285964 Merge pull request #570 from ironcalc/dani/app/localstorage-warning
update: add data-storage warnings to the app
2025-11-23 13:12:35 +01:00
Daniel
ba40c3c673 update: copy 2025-11-23 13:04:32 +01:00
Daniel
cc01556387 fix: nicos suggestions 2025-11-23 13:03:47 +01:00
Daniel
35323df20e fix: copilot's suggestions 2025-11-23 13:03:47 +01:00
Daniel
19c115b32f update: allow to edit sheet anems directly from tab buttons 2025-11-23 13:03:47 +01:00
Daniel
6b60b339d6 update: show tab menu on right click 2025-11-23 13:03:47 +01:00
Nicolás Hatcher
41c8d88b80 UPDATE: Adds the rest of the DATABASE functions 2025-11-23 10:48:23 +01:00
Daniel
73e5c305cc update: add a dismissable alert to the left drawer 2025-11-21 00:26:51 +01:00
Elsa Minsut
774b447c84 update: adds xlsx test for these functions 2025-11-20 22:13:23 +01:00
Elsa Minsut
23b7333572 docs: available status for implemented functions 2025-11-20 22:13:23 +01:00
Elsa Minsut
ef47c26c50 update: adds unit test for the reciprocal trigonometric functions 2025-11-20 22:13:23 +01:00
Elsa Minsut
5cc61b0de4 update: adds unit test for EXP and SIGN 2025-11-20 22:12:29 +01:00
Elsa Minsut
42e8d44454 docs: available status for implemented functions 2025-11-20 22:12:29 +01:00
Elsa Minsut
f840806f94 docs: adds style guide page to sidebar 2025-11-20 22:11:45 +01:00
Elsa Minsut
4a21d4b03a docs: style guide clarity fix 2025-11-20 22:11:45 +01:00
Elsa Minsut
4cf162eb82 docs: documentation guide edits for clarity, readability and consistency 2025-11-20 22:11:45 +01:00
Nicolás Hatcher
2cab93be18 UPDATE: Also use erfc (thanks copilot!) 2025-11-20 22:01:00 +01:00
Nicolás Hatcher
fd34e46689 UPDATE: Uses statrs instead of our own erf
This adds 2630 bytes to the wasm build and a dependency.
It is ok-ish

The idea is that it will help us greatly with the statistical functions
2025-11-20 22:01:00 +01:00
Nicolás Hatcher
3bb49d1e8f FIX: Minor cleanups 2025-11-20 21:44:05 +01:00
Nicolás Hatcher
1391f196b5 UPDATE: Adds name validation and exposes it in wasm
We do a trick I am not proud of. Because all of our errors are Strings,
we don't have a way to separate a name error from an index error,
for instance. What I do in prepend the error with a string that indicates
where it comes from.
2025-11-20 21:44:05 +01:00
Nicolás Hatcher
3db094c956 FIX: Select range in worksheet when the name is selected if possible 2025-11-20 21:44:05 +01:00
Nicolás Hatcher
50941cb6ef FIX: Make properties not optional 2025-11-20 21:44:05 +01:00
Daniel
150b516863 update: add a warning tooltip next to the title 2025-11-20 00:55:32 +01:00
Nicolás Hatcher
dc49afa2c3 FIX: Format numbers a tad better
I still think there is some way to go, but this is closer to Excel
2025-11-19 23:53:07 +01:00
Nicolás Hatcher
acb90fbb9d FIX: Issues with trigonometric functions
* Right branch for ACOT for negative numbers
* correct error for ACOTH
* Correct approx for COTH for x > 20
2025-11-19 23:53:07 +01:00
Nicolás Hatcher
7676efca44 FIX: Issues with SIGN and EXP
Fixes #563
2025-11-19 04:24:23 +01:00
Daniel
8e15c623dd docs: add a guide for documenting functions 2025-11-17 22:45:53 +01:00
Nicolás Hatcher
eb76d8dd23 FIX: Issues with INT
Fixes #535
2025-11-16 20:34:25 +01:00
Nicolás Hatcher
1053d00d22 FIX: Copilot's suggestions 2025-11-16 19:45:18 +01:00
Nicolás Hatcher
5ff4774c5a FIX: Cast to string now checks for dates, currencies or percentages
Fixes part of #535
2025-11-16 19:45:18 +01:00
Nicolás Hatcher
7e966baa0d FIX: Copilot's catch 2025-11-16 11:29:57 +01:00
Nicolás Hatcher
c52c05aa8e FIX: Fixes several issues with DATABASE functions
Fixes #547
2025-11-16 11:29:57 +01:00
Elsa Minsut
129959137d update: adds testing for MROUND, TRUNC, and INT (#542)
* update: available status for implemented functions

* update: adds xlsx test for MROUND, TRUNC and INT

* update: adds unit test for MROUND, TRUNC and INT
2025-11-16 11:25:28 +01:00
Elsa Minsut
4d5af45711 fix: removes failing cases from xlsx test 2025-11-16 11:22:29 +01:00
Elsa Minsut
471f32f92a update: adds unit test for ARABIC and ROMAN 2025-11-16 11:22:29 +01:00
Elsa Minsut
7b5427196d update: updates docs to show ARABIC and ROMAN as implemented functions 2025-11-16 11:22:29 +01:00
Elsa Minsut
66b7586730 update: adds xlsx test for ARABIC and ROMAN 2025-11-16 11:22:29 +01:00
Nicolás Hatcher
630f0e1baf FIX: Biome automatic "unsafe" updates 2025-11-13 19:49:04 +01:00
Nicolás Hatcher
bc9fefcb70 FIX: Biome automatic updates 2025-11-13 19:49:04 +01:00
Nicolás Hatcher
3d970acc34 FIX: Make biome happy 2025-11-13 19:49:04 +01:00
Nicolás Hatcher
e0e566db76 UPDATE: Update frontend dependencies 2025-11-13 19:49:04 +01:00
Nicolás Hatcher
e3fc1d229a FIX: Disables telemetry for storybook 2025-11-13 19:49:04 +01:00
Nicolás Hatcher
78d1f6b4a4 UPDATE: Updates vite and dependencies 2025-11-13 19:49:04 +01:00
Nicolás Hatcher
45ee1c35fe UPDATE: Update dependencies 2025-11-13 19:49:04 +01:00
Nicolás Hatcher
671cfff619 UPDATE: Update React and Storybook 2025-11-13 19:49:04 +01:00
Nicolás Hatcher
7e2fcec4a3 FIX: Biome apply "unsafe" changes 2025-11-13 19:49:04 +01:00
Nicolás Hatcher
12342da649 FIX: Delete unused button 2025-11-13 19:49:04 +01:00
Nicolás Hatcher
4e9d7611a8 FIX: Update biome and apply automatic fixes 2025-11-13 19:49:04 +01:00
Elsa Minsut
e0339f641b UPDATE: updates test for TIME, HOUR, MINUTE, SECOND (#461)
* UPDATE: updates test for TIME, HOUR, MINUTE, SECOND

* fix: updates test to remove failing edge cases

* fix: xlsx file rename for compatibility
2025-11-13 18:15:34 +01:00
Nicolás Hatcher
aa953e1ece UPDATE: Add some DATABASE functions
DAVERAGE
DCOUNT
DGET
DMAX
DMIN
DSUM
2025-11-12 23:18:47 +01:00
Daniel Gonzalez Albo
cbf75c059b fix: nicos suggestions 2025-11-12 22:33:44 +01:00
Daniel Gonzalez Albo
b2744efeb5 fix: copilot and nicos comments 2025-11-12 22:33:44 +01:00
Daniel Gonzalez Albo
ef6849e822 fix: copilot suggestions 2025-11-12 22:33:44 +01:00
Daniel Gonzalez Albo
aa4dd598b1 chore: remove old name manager 2025-11-12 22:33:44 +01:00
Daniel Gonzalez Albo
8b3bd7943e update: mobile support 2025-11-12 22:33:44 +01:00
Daniel Gonzalez Albo
a1d1b64b76 update: add empty space 2025-11-12 22:33:44 +01:00
Daniel Gonzalez Albo
5094a7fe4d update: in toolbar, open drawer instead of dialog 2025-11-12 22:33:44 +01:00
Daniel Gonzalez Albo
c283fd7b60 update: improve error handling 2025-11-12 22:33:44 +01:00
Daniel Gonzalez Albo
36beccd4ae style: adjustments in scope select 2025-11-12 22:33:44 +01:00
Daniel Gonzalez Albo
a252f9c626 fix: footer, header, translation file 2025-11-12 22:33:44 +01:00
Daniel Gonzalez Albo
f8bd03d92c update: add actions, allow drawer resize 2025-11-12 22:33:44 +01:00
Daniel Gonzalez Albo
e44a2e8c3e update: styling and layout 2025-11-12 22:33:44 +01:00
Daniel Gonzalez Albo
4217c1455b update: move all functionalities from dialog to drawer 2025-11-12 22:33:44 +01:00
Daniel Gonzalez Albo
d8b3ba0dae update: populate drawer, styling 2025-11-12 22:33:44 +01:00
Daniel Gonzalez Albo
95a7782f22 update: move drawer to its own component 2025-11-12 22:33:44 +01:00
Nicolás Hatcher
087211ebc3 UPDATE: WIP 2025-11-12 22:33:44 +01:00
Elsa Minsut
46d766c85c update: warning message shows function as implemented 2025-11-12 20:44:08 +01:00
Elsa Minsut
2a14ee73c4 update: replaces warning text on doc pages 2025-11-12 20:44:08 +01:00
Elsa Minsut
401c7c4289 update: sets implemented functions as available 2025-11-12 20:44:08 +01:00
Elsa Minsut
3246137545 update: adds unit test for COMBIN and COMBINA 2025-11-12 20:44:08 +01:00
Elsa Minsut
b1f45511d0 update: adds xlsx test for COMBIN and COMBINA 2025-11-12 20:44:08 +01:00
Nicolás Hatcher
4b93174261 FIX: Value of SEC at 0 was incorrect
Also fixed imported errors of trigonometrical functions

Fixes #531
2025-11-11 22:25:10 +01:00
Nicolás Hatcher
3111a74530 FIX: Propagate name correctly 2025-11-11 08:28:50 +01:00
Nicolás Hatcher
ae3fcaf9e9 FIX: New workbooks are created in the users TZ falling back to UTC 2025-11-11 08:28:50 +01:00
Nicolás Hatcher
dd78db3d2b FIX: NOW shows now formatted output 2025-11-11 08:28:50 +01:00
Nicolás Hatcher
acf334074f FIX: Include misconfigured test file 2025-11-11 08:28:50 +01:00
Nicolás Hatcher
e48810d91b FIX: Removed some console.log lines 2025-11-11 08:28:50 +01:00
Nicolás Hatcher
18db1cf052 FIX: Two small fixes to YEARFRAC
* Takes abs value in between two dates
* Follows ODFv1.2 part 2 section 4.11.7.7
2025-11-08 22:40:18 +01:00
Elsa Minsut
ed40f79324 FIX: Skip numerical failure in windows 2025-11-08 17:56:07 +01:00
Elsa Minsut
10ee95c48f FIX: Badge type 2025-11-08 17:56:07 +01:00
Elsa Minsut
741a223f3d update: Math and Trigonometry main page links to new docs 2025-11-08 17:56:07 +01:00
Elsa Minsut
ba139d1b6c update: adds MOD and QUOTIENT doc pages 2025-11-08 17:56:07 +01:00
Elsa Minsut
e0306cb161 update: adds unit test for MOD and QUOTIENT 2025-11-08 17:56:07 +01:00
Elsa Minsut
cea1f67cd0 update: adds xlsx tests for MOD and QUOTIENT 2025-11-08 17:56:07 +01:00
Nicolás Hatcher Andrés
4a3eef5a81 FIX: TRUE/FALSE for QUOTIENT (#524)
Excel returns #VALUE! when arguments are boolean

NB: MOD is different!
2025-11-08 17:25:02 +01:00
Elsa Minsut
91299e3c0b update: fixes status for implemented functions (#520) 2025-11-08 08:54:38 +01:00
Nicolás Hatcher Andrés
1b38d79b81 FIX: Make clippy happy (#521) 2025-11-08 08:53:50 +01:00
Elsa Minsut
a2d11a42cc update: adds docs, unit tests and xlsx tests for EVEN and ODD functions (#517)
* update: adds unit test for EVEN and ODD functions

* update: adds xlsx test for EVEN and ODD functions

* update: adds EVEN and ODD doc pages

* update: Math and Trigonometry main page links to new functions

* update: changes to functions badge type in main Math and Trigonometry page
2025-11-07 04:26:01 +01:00
Elsa Minsut
480a2d1769 update: adds docs, unit tests and xlsx tests for DATEVALUE and TIMEVALUE functions (#506)
* update: adds documentation for DATEVALUE and TIMEVALUE functions

* update: adds DATEVALUE and TIMEVALUE unit tests

* update: adds DATEVALUE and TIMEVALUE xlsx tests

* update: Date and Time main page links

* update: adds testing for multiple arguments

* update: removes links to example files

* update: removes DATEVALUE and TIMEVALUE xlsx tests
2025-11-06 22:56:14 +01:00
Elsa Minsut
f30f6864e2 update: adds docs and xlsx tests for DEGREES and RADIANS functions (#507)
* update: adds DEGREES and RADIANS documentation pages

* update: adds DEGREES and RADIANS xlsx tests

* update: Math and Trigonometry main page links

* update: removes links to missing example file
2025-11-06 22:55:28 +01:00
264 changed files with 16143 additions and 7148 deletions

20
Cargo.lock generated
View File

@@ -43,6 +43,15 @@ dependencies = [
"libc",
]
[[package]]
name = "approx"
version = "0.5.1"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "cab112f0a86d568ea0e627cc1d6be74a1e9cd55214684db5561995f6dad897c6"
dependencies = [
"num-traits",
]
[[package]]
name = "arrayvec"
version = "0.7.6"
@@ -443,6 +452,7 @@ dependencies = [
"ryu",
"serde",
"serde_json",
"statrs",
]
[[package]]
@@ -965,6 +975,16 @@ version = "0.3.11"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "38b58827f4464d87d377d175e90bf58eb00fd8716ff0a62f80356b5e61555d0d"
[[package]]
name = "statrs"
version = "0.18.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "2a3fe7c28c6512e766b0874335db33c94ad7b8f9054228ae1c2abd47ce7d335e"
dependencies = [
"approx",
"num-traits",
]
[[package]]
name = "subtle"
version = "2.5.0"

View File

@@ -19,6 +19,7 @@ regex = { version = "1.0", optional = true}
regex-lite = { version = "0.1.6", optional = true}
bitcode = "0.6.3"
csv = "1.3.0"
statrs = { version = "0.18.0", default-features = false, features = [] }
[features]
default = ["use_regex_full"]

View File

@@ -5,6 +5,7 @@ use crate::{
token::Error,
types::CellReferenceIndex,
},
formatter::format::parse_formatted_number,
model::Model,
};
@@ -14,6 +15,23 @@ pub(crate) enum NumberOrArray {
}
impl Model {
pub(crate) fn cast_number(&self, s: &str) -> Option<f64> {
match s.trim().parse::<f64>() {
Ok(f) => Some(f),
_ => {
let currency = &self.locale.currency.symbol;
let mut currencies = vec!["$", ""];
if !currencies.iter().any(|e| *e == currency) {
currencies.push(currency);
}
// Try to parse as a formatted number (e.g., dates, currencies, percentages)
if let Ok((v, _number_format)) = parse_formatted_number(s, &currencies) {
return Some(v);
}
None
}
}
}
pub(crate) fn get_number_or_array(
&mut self,
node: &Node,
@@ -21,9 +39,9 @@ impl Model {
) -> Result<NumberOrArray, CalcResult> {
match self.evaluate_node_in_context(node, cell) {
CalcResult::Number(f) => Ok(NumberOrArray::Number(f)),
CalcResult::String(s) => match s.parse::<f64>() {
Ok(f) => Ok(NumberOrArray::Number(f)),
_ => Err(CalcResult::new_error(
CalcResult::String(s) => match self.cast_number(&s) {
Some(f) => Ok(NumberOrArray::Number(f)),
None => Err(CalcResult::new_error(
Error::VALUE,
cell,
"Expecting number".to_string(),
@@ -89,16 +107,16 @@ impl Model {
self.cast_to_number(result, cell)
}
fn cast_to_number(
pub(crate) fn cast_to_number(
&mut self,
result: CalcResult,
cell: CellReferenceIndex,
) -> Result<f64, CalcResult> {
match result {
CalcResult::Number(f) => Ok(f),
CalcResult::String(s) => match s.parse::<f64>() {
Ok(f) => Ok(f),
_ => Err(CalcResult::new_error(
CalcResult::String(s) => match self.cast_number(&s) {
Some(f) => Ok(f),
None => Err(CalcResult::new_error(
Error::VALUE,
cell,
"Expecting number".to_string(),

View File

@@ -12,6 +12,9 @@ pub(crate) const DEFAULT_WINDOW_WIDTH: i64 = 800;
pub(crate) const LAST_COLUMN: i32 = 16_384;
pub(crate) const LAST_ROW: i32 = 1_048_576;
// Excel uses 15 significant digits of precision for all numeric calculations.
pub(crate) const EXCEL_PRECISION: usize = 15;
// 693_594 is computed as:
// NaiveDate::from_ymd(1900, 1, 1).num_days_from_ce() - 2
// The 2 days offset is because of Excel 1900 bug

View File

@@ -471,6 +471,20 @@ impl Parser {
Node::NumberKind(s) => ArrayNode::Number(s),
Node::StringKind(s) => ArrayNode::String(s),
Node::ErrorKind(kind) => ArrayNode::Error(kind),
Node::UnaryKind {
kind: OpUnary::Minus,
right,
} => {
if let Node::NumberKind(n) = *right {
ArrayNode::Number(-n)
} else {
return Err(Node::ParseErrorKind {
formula: self.lexer.get_formula(),
message: "Invalid value in array".to_string(),
position: self.lexer.get_position() as usize,
});
}
}
error @ Node::ParseErrorKind { .. } => return Err(error),
_ => {
return Err(Node::ParseErrorKind {
@@ -490,6 +504,20 @@ impl Parser {
Node::NumberKind(s) => ArrayNode::Number(s),
Node::StringKind(s) => ArrayNode::String(s),
Node::ErrorKind(kind) => ArrayNode::Error(kind),
Node::UnaryKind {
kind: OpUnary::Minus,
right,
} => {
if let Node::NumberKind(n) = *right {
ArrayNode::Number(-n)
} else {
return Err(Node::ParseErrorKind {
formula: self.lexer.get_formula(),
message: "Invalid value in array".to_string(),
position: self.lexer.get_position() as usize,
});
}
}
error @ Node::ParseErrorKind { .. } => return Err(error),
_ => {
return Err(Node::ParseErrorKind {

View File

@@ -550,14 +550,6 @@ fn args_signature_irr(arg_count: usize) -> Vec<Signature> {
}
}
fn args_signature_fvschedule(arg_count: usize) -> Vec<Signature> {
if arg_count == 2 {
vec![Signature::Scalar, Signature::Vector]
} else {
vec![Signature::Error; arg_count]
}
}
fn args_signature_xirr(arg_count: usize) -> Vec<Signature> {
if arg_count == 2 {
vec![Signature::Vector; arg_count]
@@ -719,6 +711,7 @@ 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],
@@ -760,7 +753,6 @@ fn get_function_args_signature(kind: &Function, arg_count: usize) -> Vec<Signatu
Function::Dollarfr => args_signature_scalars(arg_count, 2, 0),
Function::Effect => args_signature_scalars(arg_count, 2, 0),
Function::Fv => args_signature_scalars(arg_count, 3, 2),
Function::Fvschedule => args_signature_fvschedule(arg_count),
Function::Ipmt => args_signature_scalars(arg_count, 4, 2),
Function::Irr => args_signature_irr(arg_count),
Function::Ispmt => args_signature_scalars(arg_count, 4, 0),
@@ -768,20 +760,9 @@ fn get_function_args_signature(kind: &Function, arg_count: usize) -> Vec<Signatu
Function::Nominal => args_signature_scalars(arg_count, 2, 0),
Function::Nper => args_signature_scalars(arg_count, 3, 2),
Function::Npv => args_signature_npv(arg_count),
Function::Duration => args_signature_scalars(arg_count, 5, 1),
Function::Mduration => args_signature_scalars(arg_count, 5, 1),
Function::Pduration => args_signature_scalars(arg_count, 3, 0),
Function::Accrint => args_signature_scalars(arg_count, 6, 2),
Function::Accrintm => args_signature_scalars(arg_count, 4, 1),
Function::Coupdaybs => args_signature_scalars(arg_count, 3, 1),
Function::Coupdays => args_signature_scalars(arg_count, 3, 1),
Function::Coupdaysnc => args_signature_scalars(arg_count, 3, 1),
Function::Coupncd => args_signature_scalars(arg_count, 3, 1),
Function::Coupnum => args_signature_scalars(arg_count, 3, 1),
Function::Couppcd => args_signature_scalars(arg_count, 3, 1),
Function::Pmt => args_signature_scalars(arg_count, 3, 2),
Function::Ppmt => args_signature_scalars(arg_count, 4, 2),
Function::Price => args_signature_scalars(arg_count, 6, 1),
Function::Pv => args_signature_scalars(arg_count, 3, 2),
Function::Rate => args_signature_scalars(arg_count, 3, 3),
Function::Rri => args_signature_scalars(arg_count, 3, 0),
@@ -790,14 +771,6 @@ fn get_function_args_signature(kind: &Function, arg_count: usize) -> Vec<Signatu
Function::Tbilleq => args_signature_scalars(arg_count, 3, 0),
Function::Tbillprice => args_signature_scalars(arg_count, 3, 0),
Function::Tbillyield => args_signature_scalars(arg_count, 3, 0),
Function::Yield => args_signature_scalars(arg_count, 6, 1),
Function::Pricedisc => args_signature_scalars(arg_count, 4, 1),
Function::Pricemat => args_signature_scalars(arg_count, 5, 1),
Function::Yielddisc => args_signature_scalars(arg_count, 4, 1),
Function::Yieldmat => args_signature_scalars(arg_count, 5, 1),
Function::Disc => args_signature_scalars(arg_count, 4, 1),
Function::Received => args_signature_scalars(arg_count, 4, 1),
Function::Intrate => args_signature_scalars(arg_count, 4, 1),
Function::Xirr => args_signature_xirr(arg_count),
Function::Xnpv => args_signature_xnpv(arg_count),
Function::Besseli => args_signature_scalars(arg_count, 2, 0),
@@ -899,11 +872,141 @@ fn get_function_args_signature(kind: &Function, arg_count: usize) -> Vec<Signatu
Function::Combin => args_signature_scalars(arg_count, 2, 0),
Function::Combina => args_signature_scalars(arg_count, 2, 0),
Function::Sumsq => vec![Signature::Vector; arg_count],
Function::N => args_signature_scalars(arg_count, 1, 0),
Function::Sheets => args_signature_scalars(arg_count, 0, 1),
Function::Cell => args_signature_scalars(arg_count, 1, 1),
Function::Info => args_signature_scalars(arg_count, 1, 1),
Function::Daverage => vec![Signature::Vector, Signature::Scalar, Signature::Vector],
Function::Dcount => vec![Signature::Vector, Signature::Scalar, Signature::Vector],
Function::Dget => vec![Signature::Vector, Signature::Scalar, Signature::Vector],
Function::Dmax => vec![Signature::Vector, Signature::Scalar, Signature::Vector],
Function::Dmin => vec![Signature::Vector, Signature::Scalar, Signature::Vector],
Function::Dsum => vec![Signature::Vector, Signature::Scalar, Signature::Vector],
Function::Dcounta => vec![Signature::Vector, Signature::Scalar, Signature::Vector],
Function::Dproduct => vec![Signature::Vector, Signature::Scalar, Signature::Vector],
Function::Dstdev => vec![Signature::Vector, Signature::Scalar, Signature::Vector],
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::FTest => vec![Signature::Vector; 2],
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]
}
}
Function::Sumx2my2 => vec![Signature::Vector; 2],
Function::Sumx2py2 => vec![Signature::Vector; 2],
Function::Sumxmy2 => vec![Signature::Vector; 2],
Function::Correl => vec![Signature::Vector; 2],
Function::Rsq => vec![Signature::Vector; 2],
Function::Intercept => vec![Signature::Vector; 2],
Function::Slope => vec![Signature::Vector; 2],
Function::Steyx => vec![Signature::Vector; 2],
Function::Gauss => args_signature_scalars(arg_count, 1, 0),
Function::Harmean => vec![Signature::Vector; arg_count],
Function::Kurt => vec![Signature::Vector; arg_count],
Function::Large => vec![Signature::Vector, Signature::Scalar],
Function::MaxA => vec![Signature::Vector; arg_count],
Function::Median => vec![Signature::Vector; arg_count],
Function::MinA => vec![Signature::Vector; arg_count],
Function::RankAvg => vec![Signature::Scalar, Signature::Vector, Signature::Scalar],
Function::RankEq => vec![Signature::Scalar, Signature::Vector, Signature::Scalar],
Function::Skew => vec![Signature::Vector; arg_count],
Function::SkewP => vec![Signature::Vector; arg_count],
Function::Small => vec![Signature::Vector, Signature::Scalar],
}
}
@@ -929,7 +1032,7 @@ fn static_analysis_on_function(kind: &Function, args: &[Node]) -> StaticResult {
Function::Atan => scalar_arguments(args),
Function::Atan2 => scalar_arguments(args),
Function::Atanh => scalar_arguments(args),
Function::Choose => scalar_arguments(args), // static_analysis_choose(args, cell),
Function::Choose => scalar_arguments(args),
Function::Column => not_implemented(args),
Function::Columns => not_implemented(args),
Function::Cos => scalar_arguments(args),
@@ -976,7 +1079,6 @@ fn static_analysis_on_function(kind: &Function, args: &[Node]) -> StaticResult {
Function::Lookup => not_implemented(args),
Function::Match => not_implemented(args),
Function::Offset => static_analysis_offset(args),
// FIXME: Row could return an array
Function::Row => StaticResult::Scalar,
Function::Rows => not_implemented(args),
Function::Vlookup => not_implemented(args),
@@ -1005,6 +1107,7 @@ 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),
@@ -1044,7 +1147,6 @@ fn static_analysis_on_function(kind: &Function, args: &[Node]) -> StaticResult {
Function::Dollarfr => not_implemented(args),
Function::Effect => not_implemented(args),
Function::Fv => not_implemented(args),
Function::Fvschedule => not_implemented(args),
Function::Ipmt => not_implemented(args),
Function::Irr => not_implemented(args),
Function::Ispmt => not_implemented(args),
@@ -1052,20 +1154,9 @@ fn static_analysis_on_function(kind: &Function, args: &[Node]) -> StaticResult {
Function::Nominal => not_implemented(args),
Function::Nper => not_implemented(args),
Function::Npv => not_implemented(args),
Function::Duration => not_implemented(args),
Function::Mduration => not_implemented(args),
Function::Pduration => not_implemented(args),
Function::Accrint => not_implemented(args),
Function::Accrintm => not_implemented(args),
Function::Coupdaybs => not_implemented(args),
Function::Coupdays => not_implemented(args),
Function::Coupdaysnc => not_implemented(args),
Function::Coupncd => not_implemented(args),
Function::Coupnum => not_implemented(args),
Function::Couppcd => not_implemented(args),
Function::Pmt => not_implemented(args),
Function::Ppmt => not_implemented(args),
Function::Price => not_implemented(args),
Function::Pv => not_implemented(args),
Function::Rate => not_implemented(args),
Function::Rri => not_implemented(args),
@@ -1074,14 +1165,6 @@ fn static_analysis_on_function(kind: &Function, args: &[Node]) -> StaticResult {
Function::Tbilleq => not_implemented(args),
Function::Tbillprice => not_implemented(args),
Function::Tbillyield => not_implemented(args),
Function::Yield => not_implemented(args),
Function::Pricedisc => not_implemented(args),
Function::Pricemat => not_implemented(args),
Function::Yielddisc => not_implemented(args),
Function::Yieldmat => not_implemented(args),
Function::Disc => not_implemented(args),
Function::Received => not_implemented(args),
Function::Intrate => not_implemented(args),
Function::Xirr => not_implemented(args),
Function::Xnpv => not_implemented(args),
Function::Besseli => scalar_arguments(args),
@@ -1187,5 +1270,93 @@ fn static_analysis_on_function(kind: &Function, args: &[Node]) -> StaticResult {
Function::Sheets => scalar_arguments(args),
Function::Cell => scalar_arguments(args),
Function::Info => scalar_arguments(args),
Function::Dget => not_implemented(args),
Function::Dmax => not_implemented(args),
Function::Dmin => not_implemented(args),
Function::Dcount => not_implemented(args),
Function::Daverage => not_implemented(args),
Function::Dsum => not_implemented(args),
Function::Dcounta => not_implemented(args),
Function::Dproduct => not_implemented(args),
Function::Dstdev => not_implemented(args),
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::FTest => 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,
Function::Sumx2my2 => StaticResult::Scalar,
Function::Sumx2py2 => StaticResult::Scalar,
Function::Sumxmy2 => StaticResult::Scalar,
Function::Correl => StaticResult::Scalar,
Function::Rsq => StaticResult::Scalar,
Function::Intercept => StaticResult::Scalar,
Function::Slope => StaticResult::Scalar,
Function::Steyx => StaticResult::Scalar,
Function::Gauss => StaticResult::Scalar,
Function::Harmean => StaticResult::Scalar,
Function::Kurt => StaticResult::Scalar,
Function::Large => StaticResult::Scalar,
Function::MaxA => StaticResult::Scalar,
Function::Median => StaticResult::Scalar,
Function::MinA => StaticResult::Scalar,
Function::RankAvg => StaticResult::Scalar,
Function::RankEq => StaticResult::Scalar,
Function::Skew => StaticResult::Scalar,
Function::SkewP => StaticResult::Scalar,
Function::Small => StaticResult::Scalar,
}
}

View File

@@ -211,15 +211,19 @@ pub fn parse_reference_a1(r: &str) -> Option<ParsedReference> {
pub fn is_valid_identifier(name: &str) -> bool {
// https://support.microsoft.com/en-us/office/names-in-formulas-fc2935f9-115d-4bef-a370-3aa8bb4c91f1
// https://github.com/MartinTrummer/excel-names/
// NOTE: We are being much more restrictive than Excel.
// In particular we do not support non ascii characters.
let upper = name.to_ascii_uppercase();
let bytes = upper.as_bytes();
let len = bytes.len();
// length of chars
let len = upper.chars().count();
let mut chars = upper.chars();
if len > 255 || len == 0 {
return false;
}
let first = bytes[0] as char;
let first = match chars.next() {
Some(ch) => ch,
None => return false,
};
// The first character of a name must be a letter, an underscore character (_), or a backslash (\).
if !(first.is_ascii_alphabetic() || first == '_' || first == '\\') {
return false;
@@ -237,20 +241,10 @@ pub fn is_valid_identifier(name: &str) -> bool {
if parse_reference_r1c1(name).is_some() {
return false;
}
let mut i = 1;
while i < len {
let ch = bytes[i] as char;
match ch {
'a'..='z' => {}
'A'..='Z' => {}
'0'..='9' => {}
'_' => {}
'.' => {}
_ => {
return false;
}
for ch in chars {
if !(ch.is_alphanumeric() || ch == '_' || ch == '.') {
return false;
}
i += 1;
}
true

View File

@@ -196,6 +196,7 @@ fn test_names() {
assert!(is_valid_identifier("_."));
assert!(is_valid_identifier("_1"));
assert!(is_valid_identifier("\\."));
assert!(is_valid_identifier("truñe"));
// invalid
assert!(!is_valid_identifier("true"));
@@ -209,7 +210,6 @@ fn test_names() {
assert!(!is_valid_identifier("1true"));
assert!(!is_valid_identifier("test€"));
assert!(!is_valid_identifier("truñe"));
assert!(!is_valid_identifier("tr&ue"));
assert!(!is_valid_identifier("LOG10"));

View File

@@ -15,7 +15,7 @@ pub struct Formatted {
/// Returns the vector of chars of the fractional part of a *positive* number:
/// 3.1415926 ==> ['1', '4', '1', '5', '9', '2', '6']
fn get_fract_part(value: f64, precision: i32) -> Vec<char> {
fn get_fract_part(value: f64, precision: i32, int_len: usize) -> Vec<char> {
let b = format!("{:.1$}", value.fract(), precision as usize)
.chars()
.collect::<Vec<char>>();
@@ -30,6 +30,12 @@ fn get_fract_part(value: f64, precision: i32) -> Vec<char> {
if last_non_zero < 2 {
return vec![];
}
let max_len = if int_len > 15 {
2_usize
} else {
15_usize - int_len + 1
};
let last_non_zero = usize::min(last_non_zero, max_len + 1);
b[2..last_non_zero].to_vec()
}
@@ -423,7 +429,7 @@ pub fn format_number(value_original: f64, format: &str, locale: &Locale) -> Form
if value_abs as i64 == 0 {
int_part = vec![];
}
let fract_part = get_fract_part(value_abs, p.precision);
let fract_part = get_fract_part(value_abs, p.precision, int_part.len());
// ln is the number of digits of the integer part of the value
let ln = int_part.len() as i32;
// digit count is the number of digit tokens ('0', '?' and '#') to the left of the decimal point
@@ -744,10 +750,10 @@ fn parse_date(value: &str) -> Result<(i32, String), String> {
/// "30.34%" => (0.3034, "0.00%")
/// 100€ => (100, "100€")
pub(crate) fn parse_formatted_number(
value: &str,
original: &str,
currencies: &[&str],
) -> Result<(f64, Option<String>), String> {
let value = value.trim();
let value = original.trim();
let scientific_format = "0.00E+00";
// Check if it is a percentage
@@ -799,7 +805,8 @@ pub(crate) fn parse_formatted_number(
}
}
if let Ok((serial_number, format)) = parse_date(value) {
// check if it is a date. NOTE: we don't trim the original here
if let Ok((serial_number, format)) = parse_date(original) {
return Ok((serial_number as f64, Some(format)));
}

View File

@@ -0,0 +1,946 @@
use chrono::Datelike;
use crate::{
calc_result::CalcResult,
expressions::{parser::Node, token::Error, types::CellReferenceIndex},
formatter::dates::date_to_serial_number,
Model,
};
use super::util::{compare_values, from_wildcard_to_regex, result_matches_regex};
impl Model {
// =DAVERAGE(database, field, criteria)
pub(crate) fn fn_daverage(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
if args.len() != 3 {
return CalcResult::new_args_number_error(cell);
}
let (db_left, db_right) = match self.get_reference(&args[0], cell) {
Ok(r) => (r.left, r.right),
Err(e) => return e,
};
let field_col = match self.resolve_db_field_column(db_left, db_right, &args[1], cell) {
Ok(c) => c,
Err(e) => return e,
};
let criteria = match self.get_reference(&args[2], cell) {
Ok(r) => (r.left, r.right),
Err(e) => return e,
};
if db_right.row <= db_left.row {
// no data rows
return CalcResult::Error {
error: Error::VALUE,
origin: cell,
message: "No data rows in database".to_string(),
};
}
let mut sum = 0.0f64;
let mut count = 0usize;
let mut row = db_left.row + 1; // skip header
while row <= db_right.row {
if self.db_row_matches_criteria(db_left, db_right, row, criteria) {
let v = self.evaluate_cell(CellReferenceIndex {
sheet: db_left.sheet,
row,
column: field_col,
});
if let CalcResult::Number(n) = v {
if n.is_finite() {
sum += n;
count += 1;
}
}
}
row += 1;
}
if count == 0 {
return CalcResult::Error {
error: Error::DIV,
origin: cell,
message: "No numeric values matched criteria".to_string(),
};
}
CalcResult::Number(sum / count as f64)
}
// =DCOUNT(database, field, criteria)
// Counts numeric entries in the field for rows that match criteria
pub(crate) fn fn_dcount(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
if args.len() != 3 {
return CalcResult::new_args_number_error(cell);
}
let (db_left, db_right) = match self.get_reference(&args[0], cell) {
Ok(r) => (r.left, r.right),
Err(e) => return e,
};
let field_col = match self.resolve_db_field_column(db_left, db_right, &args[1], cell) {
Ok(c) => c,
Err(e) => return e,
};
let criteria = match self.get_reference(&args[2], cell) {
Ok(r) => (r.left, r.right),
Err(e) => return e,
};
if db_right.row <= db_left.row {
// no data rows
return CalcResult::Error {
error: Error::VALUE,
origin: cell,
message: "No data rows in database".to_string(),
};
}
let mut count = 0usize;
let mut row = db_left.row + 1; // skip header
while row <= db_right.row {
if self.db_row_matches_criteria(db_left, db_right, row, criteria) {
let v = self.evaluate_cell(CellReferenceIndex {
sheet: db_left.sheet,
row,
column: field_col,
});
if matches!(v, CalcResult::Number(_)) {
count += 1;
}
}
row += 1;
}
CalcResult::Number(count as f64)
}
// =DGET(database, field, criteria)
// Returns the (single) field value for the unique matching row
pub(crate) fn fn_dget(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
if args.len() != 3 {
return CalcResult::new_args_number_error(cell);
}
let (db_left, db_right) = match self.get_reference(&args[0], cell) {
Ok(r) => (r.left, r.right),
Err(e) => return e,
};
let field_col = match self.resolve_db_field_column(db_left, db_right, &args[1], cell) {
Ok(c) => c,
Err(e) => return e,
};
let criteria = match self.get_reference(&args[2], cell) {
Ok(r) => (r.left, r.right),
Err(e) => return e,
};
if db_right.row <= db_left.row {
// no data rows
return CalcResult::Error {
error: Error::VALUE,
origin: cell,
message: "No data rows in database".to_string(),
};
}
let mut result: Option<CalcResult> = None;
let mut matches = 0usize;
let mut row = db_left.row + 1;
while row <= db_right.row {
if self.db_row_matches_criteria(db_left, db_right, row, criteria) {
matches += 1;
if matches > 1 {
return CalcResult::Error {
error: Error::NUM,
origin: cell,
message: "More than one matching record".to_string(),
};
}
result = Some(self.evaluate_cell(CellReferenceIndex {
sheet: db_left.sheet,
row,
column: field_col,
}));
}
row += 1;
}
match (matches, result) {
(0, _) | (_, None) => CalcResult::Error {
error: Error::VALUE,
origin: cell,
message: "No matching record".to_string(),
},
(_, Some(v)) => v,
}
}
// =DMAX(database, field, criteria)
pub(crate) fn fn_dmax(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
self.db_extreme(args, cell, true)
}
// =DMIN(database, field, criteria)
pub(crate) fn fn_dmin(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
self.db_extreme(args, cell, false)
}
// =DSUM(database, field, criteria)
pub(crate) fn fn_dsum(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
if args.len() != 3 {
return CalcResult::new_args_number_error(cell);
}
let (db_left, db_right) = match self.get_reference(&args[0], cell) {
Ok(r) => (r.left, r.right),
Err(e) => return e,
};
let field_col = match self.resolve_db_field_column(db_left, db_right, &args[1], cell) {
Ok(c) => c,
Err(e) => return e,
};
let criteria = match self.get_reference(&args[2], cell) {
Ok(r) => (r.left, r.right),
Err(e) => return e,
};
if db_right.row <= db_left.row {
// no data rows
return CalcResult::Error {
error: Error::VALUE,
origin: cell,
message: "No data rows in database".to_string(),
};
}
let mut sum = 0.0;
// skip header
let mut row = db_left.row + 1;
while row <= db_right.row {
if self.db_row_matches_criteria(db_left, db_right, row, criteria) {
let v = self.evaluate_cell(CellReferenceIndex {
sheet: db_left.sheet,
row,
column: field_col,
});
if let CalcResult::Number(n) = v {
if n.is_finite() {
sum += n;
}
}
}
row += 1;
}
CalcResult::Number(sum)
}
// =DCOUNTA(database, field, criteria)
// Counts non-empty entries (any type) in the field for rows that match criteria
pub(crate) fn fn_dcounta(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
if args.len() != 3 {
return CalcResult::new_args_number_error(cell);
}
let (db_left, db_right) = match self.get_reference(&args[0], cell) {
Ok(r) => (r.left, r.right),
Err(e) => return e,
};
let field_col = match self.resolve_db_field_column(db_left, db_right, &args[1], cell) {
Ok(c) => c,
Err(e) => return e,
};
let criteria = match self.get_reference(&args[2], cell) {
Ok(r) => (r.left, r.right),
Err(e) => return e,
};
if db_right.row <= db_left.row {
// no data rows
return CalcResult::Error {
error: Error::VALUE,
origin: cell,
message: "No data rows in database".to_string(),
};
}
let mut count = 0;
for row in (db_left.row + 1)..=db_right.row {
if self.db_row_matches_criteria(db_left, db_right, row, criteria) {
let v = self.evaluate_cell(CellReferenceIndex {
sheet: db_left.sheet,
row,
column: field_col,
});
if !matches!(v, CalcResult::EmptyCell | CalcResult::EmptyArg) {
count += 1;
}
}
}
CalcResult::Number(count as f64)
}
// =DPRODUCT(database, field, criteria)
pub(crate) fn fn_dproduct(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
if args.len() != 3 {
return CalcResult::new_args_number_error(cell);
}
let (db_left, db_right) = match self.get_reference(&args[0], cell) {
Ok(r) => (r.left, r.right),
Err(e) => return e,
};
let field_col = match self.resolve_db_field_column(db_left, db_right, &args[1], cell) {
Ok(c) => c,
Err(e) => return e,
};
let criteria = match self.get_reference(&args[2], cell) {
Ok(r) => (r.left, r.right),
Err(e) => return e,
};
if db_right.row <= db_left.row {
// no data rows
return CalcResult::Error {
error: Error::VALUE,
origin: cell,
message: "No data rows in database".to_string(),
};
}
let mut product = 1.0f64;
let mut has_numeric = false;
let mut row = db_left.row + 1; // skip header
while row <= db_right.row {
if self.db_row_matches_criteria(db_left, db_right, row, criteria) {
let v = self.evaluate_cell(CellReferenceIndex {
sheet: db_left.sheet,
row,
column: field_col,
});
if let CalcResult::Number(n) = v {
if n.is_finite() {
product *= n;
has_numeric = true;
}
}
}
row += 1;
}
// Excel returns 0 when no rows / no numeric values match for DPRODUCT
if has_numeric {
CalcResult::Number(product)
} else {
CalcResult::Number(0.0)
}
}
// Small internal helper for DSTDEV / DVAR
// Collects sum, sum of squares, and count of numeric values in the field
// for rows that match the criteria.
fn db_numeric_stats(
&mut self,
args: &[Node],
cell: CellReferenceIndex,
) -> Result<(f64, f64, usize), CalcResult> {
if args.len() != 3 {
return Err(CalcResult::new_args_number_error(cell));
}
let (db_left, db_right) = match self.get_reference(&args[0], cell) {
Ok(r) => (r.left, r.right),
Err(e) => return Err(e),
};
let field_col = self.resolve_db_field_column(db_left, db_right, &args[1], cell)?;
let criteria = match self.get_reference(&args[2], cell) {
Ok(r) => (r.left, r.right),
Err(e) => return Err(e),
};
if db_right.row <= db_left.row {
// no data rows
return Err(CalcResult::Error {
error: Error::VALUE,
origin: cell,
message: "No data rows in database".to_string(),
});
}
let mut sum = 0.0f64;
let mut sumsq = 0.0f64;
let mut count = 0usize;
let mut row = db_left.row + 1; // skip header
while row <= db_right.row {
if self.db_row_matches_criteria(db_left, db_right, row, criteria) {
let v = self.evaluate_cell(CellReferenceIndex {
sheet: db_left.sheet,
row,
column: field_col,
});
if let CalcResult::Number(n) = v {
if n.is_finite() {
sum += n;
sumsq += n * n;
count += 1;
}
}
}
row += 1;
}
Ok((sum, sumsq, count))
}
// =DSTDEV(database, field, criteria)
// Sample standard deviation of matching numeric values
pub(crate) fn fn_dstdev(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
let (sum, sumsq, count) = match self.db_numeric_stats(args, cell) {
Ok(stats) => stats,
Err(e) => return e,
};
// Excel behaviour: #DIV/0! if 0 or 1 numeric values match
if count < 2 {
return CalcResult::Error {
error: Error::DIV,
origin: cell,
message: "Not enough numeric values matched criteria".to_string(),
};
}
let n = count as f64;
let var = (sumsq - (sum * sum) / n) / (n - 1.0);
let var = if var < 0.0 { 0.0 } else { var };
CalcResult::Number(var.sqrt())
}
// =DVAR(database, field, criteria)
// Sample variance of matching numeric values
pub(crate) fn fn_dvar(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
let (sum, sumsq, count) = match self.db_numeric_stats(args, cell) {
Ok(stats) => stats,
Err(e) => return e,
};
// Excel behaviour: #DIV/0! if 0 or 1 numeric values match
if count < 2 {
return CalcResult::Error {
error: Error::DIV,
origin: cell,
message: "Not enough numeric values matched criteria".to_string(),
};
}
let n = count as f64;
let var = (sumsq - (sum * sum) / n) / (n - 1.0);
let var = if var < 0.0 { 0.0 } else { var };
CalcResult::Number(var)
}
// =DSTDEVP(database, field, criteria)
// Population standard deviation of matching numeric values
pub(crate) fn fn_dstdevp(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
let (sum, sumsq, count) = match self.db_numeric_stats(args, cell) {
Ok(stats) => stats,
Err(e) => return e,
};
// Excel behaviour: #DIV/0! if no numeric values match
if count == 0 {
return CalcResult::Error {
error: Error::DIV,
origin: cell,
message: "No numeric values matched criteria".to_string(),
};
}
let n = count as f64;
let var = (sumsq - (sum * sum) / n) / n;
let var = if var < 0.0 { 0.0 } else { var };
CalcResult::Number(var.sqrt())
}
// =DVARP(database, field, criteria)
// Population variance of matching numeric values
pub(crate) fn fn_dvarp(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
let (sum, sumsq, count) = match self.db_numeric_stats(args, cell) {
Ok(stats) => stats,
Err(e) => return e,
};
// Excel behaviour: #DIV/0! if no numeric values match
if count == 0 {
return CalcResult::Error {
error: Error::DIV,
origin: cell,
message: "No numeric values matched criteria".to_string(),
};
}
let n = count as f64;
let var = (sumsq - (sum * sum) / n) / n;
let var = if var < 0.0 { 0.0 } else { var };
CalcResult::Number(var)
}
/// Resolve the "field" (2nd arg) to an absolute column index (i32) within the sheet.
/// Field can be a number (1-based index) or a header name (case-insensitive).
/// Returns the absolute column index, not a 1-based offset within the database range.
fn resolve_db_field_column(
&mut self,
db_left: CellReferenceIndex,
db_right: CellReferenceIndex,
field_arg: &Node,
cell: CellReferenceIndex,
) -> Result<i32, CalcResult> {
let field_column_name = match self.evaluate_node_in_context(field_arg, cell) {
CalcResult::String(s) => s.to_lowercase(),
CalcResult::Number(index) => {
let index = index.floor() as i32;
if index < 1 || db_left.column + index - 1 > db_right.column {
return Err(CalcResult::Error {
error: Error::VALUE,
origin: cell,
message: "Field index out of range".to_string(),
});
}
return Ok(db_left.column + index - 1);
}
CalcResult::Boolean(b) => {
return if b {
Ok(db_left.column)
} else {
// Index 0 is out of range
Err(CalcResult::Error {
error: Error::VALUE,
origin: cell,
message: "Invalid field specifier".to_string(),
})
};
}
error @ CalcResult::Error { .. } => {
return Err(error);
}
CalcResult::Range { .. } => {
return Err(CalcResult::Error {
error: Error::NIMPL,
origin: cell,
message: "Arrays not supported yet".to_string(),
})
}
CalcResult::EmptyCell | CalcResult::EmptyArg => "".to_string(),
CalcResult::Array(_) => {
return Err(CalcResult::Error {
error: Error::NIMPL,
origin: cell,
message: "Arrays not supported yet".to_string(),
})
}
};
// We search in the database a column whose header matches field_column_name
for column in db_left.column..=db_right.column {
let v = self.evaluate_cell(CellReferenceIndex {
sheet: db_left.sheet,
row: db_left.row,
column,
});
match &v {
CalcResult::String(s) => {
if s.to_lowercase() == field_column_name {
return Ok(column);
}
}
CalcResult::Number(n) => {
if field_column_name == n.to_string() {
return Ok(column);
}
}
CalcResult::Boolean(b) => {
if field_column_name == b.to_string() {
return Ok(column);
}
}
CalcResult::Error { .. }
| CalcResult::Range { .. }
| CalcResult::EmptyCell
| CalcResult::EmptyArg
| CalcResult::Array(_) => {}
}
}
Err(CalcResult::Error {
error: Error::VALUE,
origin: cell,
message: "Field header not found".to_string(),
})
}
/// Check whether a database row matches the criteria range.
/// Criteria logic: OR across criteria rows; AND across columns within a row.
fn db_row_matches_criteria(
&mut self,
db_left: CellReferenceIndex,
db_right: CellReferenceIndex,
row: i32,
criteria: (CellReferenceIndex, CellReferenceIndex),
) -> bool {
let (c_left, c_right) = criteria;
// Read criteria headers (first row of criteria range)
// Map header name (lowercased) -> db column (if exists)
let mut crit_cols: Vec<i32> = Vec::new();
let mut header_count = 0;
// We cover the criteria table:
// headerA | headerB | ...
// critA1 | critA2 | ...
// critB1 | critB2 | ...
// ...
for column in c_left.column..=c_right.column {
let cell = CellReferenceIndex {
sheet: c_left.sheet,
row: c_left.row,
column,
};
let criteria_header = self.evaluate_cell(cell);
if let Ok(s) = self.cast_to_string(criteria_header, cell) {
// Non-empty string header. If the header is non string we skip it
header_count += 1;
let wanted = s.to_lowercase();
// Find corresponding Database column
let mut found = false;
for db_column in db_left.column..=db_right.column {
let db_header = self.evaluate_cell(CellReferenceIndex {
sheet: db_left.sheet,
row: db_left.row,
column: db_column,
});
if let Ok(hs) = self.cast_to_string(db_header, cell) {
if hs.to_lowercase() == wanted {
crit_cols.push(db_column);
found = true;
break;
}
}
}
if !found {
// that means the criteria column has no matching DB column
// If the criteria condition is empty then we remove this condition
// otherwise this condition can never be satisfied
// We evaluate all criteria rows to see if any is non-empty
let mut has_non_empty = false;
for r in (c_left.row + 1)..=c_right.row {
let ccell = self.evaluate_cell(CellReferenceIndex {
sheet: c_left.sheet,
row: r,
column,
});
if !matches!(ccell, CalcResult::EmptyCell | CalcResult::EmptyArg) {
has_non_empty = true;
break;
}
}
if has_non_empty {
// This criteria column can never be satisfied
header_count -= 1;
}
}
};
}
if c_right.row <= c_left.row {
// If no criteria rows (only headers), everything matches
return true;
}
if header_count == 0 {
// If there are not "String" headers, nothing matches
// NB: There might be String headers that do not match any DB columns,
// in that case everything matches.
return false;
}
// Evaluate each criteria row (OR)
for r in (c_left.row + 1)..=c_right.row {
// AND across columns for this criteria row
let mut and_ok = true;
for (offset, db_col) in crit_cols.iter().enumerate() {
// Criteria cell
let ccell = self.evaluate_cell(CellReferenceIndex {
sheet: c_left.sheet,
row: r,
column: c_left.column + offset as i32,
});
// Empty criteria cell -> ignored
if matches!(ccell, CalcResult::EmptyCell | CalcResult::EmptyArg) {
continue;
}
// Database value for this row/column
let db_val = self.evaluate_cell(CellReferenceIndex {
sheet: db_left.sheet,
row,
column: *db_col,
});
if !self.criteria_cell_matches(&db_val, &ccell) {
and_ok = false;
break;
}
}
if and_ok {
// This criteria row satisfied (OR)
return true;
}
}
// none matched
false
}
/// Implements Excel-like criteria matching for a single value.
/// Supports prefixes: <>, >=, <=, >, <, = ; wildcards * and ? for string equals.
fn criteria_cell_matches(&self, db_val: &CalcResult, crit_cell: &CalcResult) -> bool {
// Convert the criteria cell to a string for operator parsing if possible,
// otherwise fall back to equality via compare_values.
let mut criteria = match crit_cell {
CalcResult::String(s) => s.trim().to_string(),
CalcResult::Number(n) => {
// treat as equality with number
return match db_val {
CalcResult::Number(v) => (*v - *n).abs() <= f64::EPSILON,
_ => false,
};
}
CalcResult::Boolean(b) => {
// check equality with boolean
return match db_val {
CalcResult::Boolean(v) => *v == *b,
_ => false,
};
}
CalcResult::EmptyCell | CalcResult::EmptyArg => "".to_string(),
CalcResult::Error { .. } => return false,
CalcResult::Range { .. } | CalcResult::Array(_) => return false,
};
// Detect operator prefix
let mut op = "="; // default equality (with wildcard semantics for strings)
let prefixes = ["<>", ">=", "<=", ">", "<", "="];
for p in prefixes.iter() {
if criteria.starts_with(p) {
op = p;
criteria = criteria[p.len()..].trim().to_string();
break;
}
}
// Is it a number?
let rhs_num = criteria.parse::<f64>().ok();
// Is it a date?
// FIXME: We should parse dates according to locale settings
let rhs_date = criteria.parse::<chrono::NaiveDate>().ok();
match op {
">" | ">=" | "<" | "<=" => {
if let Some(d) = rhs_date {
// date comparison
let serial = match date_to_serial_number(d.day(), d.month(), d.year()) {
Ok(sn) => sn as f64,
Err(_) => return false,
};
if let CalcResult::Number(n) = db_val {
match op {
">" => *n > serial,
">=" => *n >= serial,
"<" => *n < serial,
"<=" => *n <= serial,
_ => false,
}
} else {
false
}
} else if let Some(t) = rhs_num {
// numeric comparison
if let CalcResult::Number(n) = db_val {
match op {
">" => *n > t,
">=" => *n >= t,
"<" => *n < t,
"<=" => *n <= t,
_ => false,
}
} else {
false
}
} else {
// string comparison (case-insensitive) using compare_values semantics
let rhs = CalcResult::String(criteria.to_lowercase());
let lhs = match db_val {
CalcResult::String(s) => CalcResult::String(s.to_lowercase()),
x => x.clone(),
};
let c = compare_values(&lhs, &rhs);
match op {
">" => c > 0,
">=" => c >= 0,
"<" => c < 0,
"<=" => c <= 0,
_ => false,
}
}
}
"<>" => {
// not equal (with wildcard semantics for strings)
// If rhs has wildcards and db_val is string, do regex; else use compare_values != 0
if let CalcResult::String(s) = db_val {
if criteria.contains('*') || criteria.contains('?') {
if let Ok(re) = from_wildcard_to_regex(&criteria.to_lowercase(), true) {
return !result_matches_regex(
&CalcResult::String(s.to_lowercase()),
&re,
);
}
}
}
let rhs = if let Some(n) = rhs_num {
CalcResult::Number(n)
} else {
CalcResult::String(criteria.to_lowercase())
};
let lhs = match db_val {
CalcResult::String(s) => CalcResult::String(s.to_lowercase()),
x => x.clone(),
};
compare_values(&lhs, &rhs) != 0
}
_ => {
// equality. For strings, support wildcards (*, ?)
if let Some(n) = rhs_num {
// numeric equals
if let CalcResult::Number(m) = db_val {
(*m - n).abs() <= f64::EPSILON
} else {
compare_values(db_val, &CalcResult::Number(n)) == 0
}
} else {
// textual/boolean equals (case-insensitive), wildcard-enabled for strings
if let CalcResult::String(s) = db_val {
if criteria.contains('*') || criteria.contains('?') {
if let Ok(re) = from_wildcard_to_regex(&criteria.to_lowercase(), true) {
return result_matches_regex(
&CalcResult::String(s.to_lowercase()),
&re,
);
}
}
// This is weird but we only need to check if "starts with" for equality
return s.to_lowercase().starts_with(&criteria.to_lowercase());
}
// Fallback: compare_values equality
compare_values(db_val, &CalcResult::String(criteria.to_lowercase())) == 0
}
}
}
}
/// Shared implementation for DMAX/DMIN
fn db_extreme(
&mut self,
args: &[Node],
cell: CellReferenceIndex,
want_max: bool,
) -> CalcResult {
if args.len() != 3 {
return CalcResult::new_args_number_error(cell);
}
let (db_left, db_right) = match self.get_reference(&args[0], cell) {
Ok(r) => (r.left, r.right),
Err(e) => return e,
};
let field_col = match self.resolve_db_field_column(db_left, db_right, &args[1], cell) {
Ok(c) => c,
Err(e) => return e,
};
let criteria = match self.get_reference(&args[2], cell) {
Ok(r) => (r.left, r.right),
Err(e) => return e,
};
if db_right.row <= db_left.row {
// no data rows
return CalcResult::Error {
error: Error::VALUE,
origin: cell,
message: "No data rows in database".to_string(),
};
}
let mut best: Option<f64> = None;
let mut row = db_left.row + 1;
while row <= db_right.row {
if self.db_row_matches_criteria(db_left, db_right, row, criteria) {
let v = self.evaluate_cell(CellReferenceIndex {
sheet: db_left.sheet,
row,
column: field_col,
});
if let CalcResult::Number(value) = v {
if value.is_finite() {
best = Some(match best {
None => value,
Some(cur) => {
if want_max {
value.max(cur)
} else {
value.min(cur)
}
}
});
}
}
}
row += 1;
}
match best {
Some(v) => CalcResult::Number(v),
None => CalcResult::Number(0.0),
}
}
}

View File

@@ -4,10 +4,31 @@ use chrono::Months;
use chrono::NaiveDateTime;
use chrono::NaiveTime;
use chrono::Timelike;
use chrono_tz::Tz;
const SECONDS_PER_DAY: i32 = 86_400;
const SECONDS_PER_DAY_F64: f64 = SECONDS_PER_DAY as f64;
fn is_leap_year(year: i32) -> bool {
(year % 4 == 0) && (year % 100 != 0 || year % 400 == 0)
}
fn is_feb_29_between_dates(start: chrono::NaiveDate, end: chrono::NaiveDate) -> bool {
let start_year = start.year();
let end_year = end.year();
for year in start_year..=end_year {
if is_leap_year(year)
&& (year < end_year
|| (year == end_year && end.month() > 2)
&& (year > start_year || (year == start_year && start.month() <= 2)))
{
return true;
}
}
false
}
// ---------------------------------------------------------------------------
// Helper macros to eliminate boilerplate in date/time component extraction
// functions (DAY, MONTH, YEAR, HOUR, MINUTE, SECOND).
@@ -750,12 +771,12 @@ impl Model {
Ok(values)
}
// Returns the current date/time as an Excel serial number in the model's configured timezone.
// Returns the current date/time as an Excel serial number in the given timezone.
// Used by TODAY() and NOW().
fn current_excel_serial(&self) -> Option<f64> {
pub(crate) fn current_excel_serial_with_timezone(&self, tz: Tz) -> Option<f64> {
let seconds = get_milliseconds_since_epoch() / 1000;
DateTime::from_timestamp(seconds, 0).map(|dt| {
let local_time = dt.with_timezone(&self.tz);
let local_time = dt.with_timezone(&tz);
let days_from_1900 = local_time.num_days_from_ce() - EXCEL_DATE_BASE;
let fraction = (local_time.num_seconds_from_midnight() as f64) / (60.0 * 60.0 * 24.0);
days_from_1900 as f64 + fraction
@@ -958,7 +979,7 @@ impl Model {
message: "Wrong number of arguments".to_string(),
};
}
match self.current_excel_serial() {
match self.current_excel_serial_with_timezone(self.tz) {
Some(serial) => CalcResult::Number(serial.floor()),
None => CalcResult::Error {
error: Error::ERROR,
@@ -969,14 +990,35 @@ impl Model {
}
pub(crate) fn fn_now(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
if !args.is_empty() {
if args.len() > 1 {
return CalcResult::Error {
error: Error::ERROR,
origin: cell,
message: "Wrong number of arguments".to_string(),
};
}
match self.current_excel_serial() {
let tz = match args.first() {
Some(arg0) => {
// Parse timezone argument
let tz_str = match self.get_string(arg0, cell) {
Ok(s) => s,
Err(e) => return e,
};
let tz: Tz = match tz_str.parse() {
Ok(tz) => tz,
Err(_) => {
return CalcResult::Error {
error: Error::VALUE,
origin: cell,
message: format!("Invalid timezone: {}", &tz_str),
}
}
};
tz
}
None => self.tz,
};
match self.current_excel_serial_with_timezone(tz) {
Some(serial) => CalcResult::Number(serial),
None => CalcResult::Error {
error: Error::ERROR,
@@ -1567,18 +1609,44 @@ impl Model {
}
}
1 => {
let year_days = if start_date.year() == end_date.year() {
if (start_date.year() % 4 == 0 && start_date.year() % 100 != 0)
|| start_date.year() % 400 == 0
{
366.0
} else {
365.0
// Procedure E
let start_year = start_date.year();
let end_year = end_date.year();
let step_a = start_year != end_year;
let step_b = start_year + 1 != end_year;
let step_c = start_date.month() < end_date.month();
let step_d = start_date.month() == end_date.month();
let step_e = start_date.day() <= end_date.day();
let step_f = step_a && (step_b || step_c || (step_d && step_e));
if step_f {
// 7.
// return average of days in year between start_year and end_year, inclusive
let mut total_days = 0;
for year in start_year..=end_year {
if is_leap_year(year) {
total_days += 366;
} else {
total_days += 365;
}
}
days / (total_days as f64 / (end_year - start_year + 1) as f64)
} else if step_a && is_leap_year(start_year) {
// 8.
days / 366.0
} else if is_feb_29_between_dates(start_date, end_date) {
// 9. If a February 29 occurs between date1 and date2 then return 366
days / 366.0
} else if end_date.month() == 2 && end_date.day() == 29 {
// 10. If date2 is February 29 then return 366
days / 366.0
} else if !step_a && is_leap_year(start_year) {
days / 366.0
} else {
365.0
};
days / year_days
// 11.
days / 365.0
}
}
2 => days / 360.0,
3 => days / 365.0,
@@ -1595,6 +1663,34 @@ impl Model {
}
_ => return CalcResult::new_error(Error::NUM, cell, "Invalid basis".to_string()),
};
CalcResult::Number(result)
CalcResult::Number(result.abs())
}
}
#[cfg(test)]
mod tests {
#![allow(clippy::unwrap_used)]
use super::*;
#[test]
fn test_is_leap_year() {
assert!(is_leap_year(2000));
assert!(!is_leap_year(1900));
assert!(is_leap_year(2004));
assert!(!is_leap_year(2001));
}
#[test]
fn test_is_feb_29_between_dates() {
let d1 = chrono::NaiveDate::from_ymd_opt(2020, 2, 28).unwrap();
let d2 = chrono::NaiveDate::from_ymd_opt(2020, 3, 1).unwrap();
assert!(is_feb_29_between_dates(d1, d2));
}
#[test]
fn test_is_feb_29_between_dates_false() {
let d1 = chrono::NaiveDate::from_ymd_opt(2021, 2, 28).unwrap();
let d2 = chrono::NaiveDate::from_ymd_opt(2021, 3, 1).unwrap();
assert!(!is_feb_29_between_dates(d1, d2));
}
}

View File

@@ -1,10 +1,12 @@
use statrs::function::erf::{erf, erfc};
use crate::{
calc_result::CalcResult,
expressions::{parser::Node, token::Error, types::CellReferenceIndex},
model::Model,
};
use super::transcendental::{bessel_i, bessel_j, bessel_k, bessel_y, erf};
use super::transcendental::{bessel_i, bessel_j, bessel_k, bessel_y};
// https://root.cern/doc/v610/TMath_8cxx_source.html
// Notice that the parameters for Bessel functions in Excel and here have inverted order
@@ -160,7 +162,7 @@ impl Model {
Ok(f) => f,
Err(s) => return s,
};
CalcResult::Number(1.0 - erf(x))
CalcResult::Number(erfc(x))
}
pub(crate) fn fn_erfcprecise(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
@@ -171,6 +173,6 @@ impl Model {
Ok(f) => f,
Err(s) => return s,
};
CalcResult::Number(1.0 - erf(x))
CalcResult::Number(erfc(x))
}
}

View File

@@ -1,53 +0,0 @@
pub(crate) fn erf(x: f64) -> f64 {
let cof = vec![
-1.3026537197817094,
6.419_697_923_564_902e-1,
1.9476473204185836e-2,
-9.561_514_786_808_63e-3,
-9.46595344482036e-4,
3.66839497852761e-4,
4.2523324806907e-5,
-2.0278578112534e-5,
-1.624290004647e-6,
1.303655835580e-6,
1.5626441722e-8,
-8.5238095915e-8,
6.529054439e-9,
5.059343495e-9,
-9.91364156e-10,
-2.27365122e-10,
9.6467911e-11,
2.394038e-12,
-6.886027e-12,
8.94487e-13,
3.13092e-13,
-1.12708e-13,
3.81e-16,
7.106e-15,
-1.523e-15,
-9.4e-17,
1.21e-16,
-2.8e-17,
];
let mut d = 0.0;
let mut dd = 0.0;
let x_abs = x.abs();
let t = 2.0 / (2.0 + x_abs);
let ty = 4.0 * t - 2.0;
for j in (1..=cof.len() - 1).rev() {
let tmp = d;
d = ty * d - dd + cof[j];
dd = tmp;
}
let res = t * f64::exp(-x_abs * x_abs + 0.5 * (cof[0] + ty * d) - dd);
if x < 0.0 {
res - 1.0
} else {
1.0 - res
}
}

View File

@@ -4,7 +4,6 @@ mod bessel_j1_y1;
mod bessel_jn_yn;
mod bessel_k;
mod bessel_util;
mod erf;
#[cfg(test)]
mod test_bessel;
@@ -13,4 +12,3 @@ pub(crate) use bessel_i::bessel_i;
pub(crate) use bessel_jn_yn::jn as bessel_j;
pub(crate) use bessel_jn_yn::yn as bessel_y;
pub(crate) use bessel_k::bessel_k;
pub(crate) use erf::erf;

File diff suppressed because it is too large Load Diff

View File

@@ -68,14 +68,14 @@ macro_rules! single_number_fn {
},
// If String, parse to f64 then apply or #VALUE! error
ArrayNode::String(s) => {
let node = match s.parse::<f64>() {
Ok(f) => match $op(f) {
let node = match self.cast_number(&s) {
Some(f) => match $op(f) {
Ok(x) => ArrayNode::Number(x),
Err(Error::DIV) => ArrayNode::Error(Error::DIV),
Err(Error::VALUE) => ArrayNode::Error(Error::VALUE),
Err(e) => ArrayNode::Error(e),
},
Err(_) => ArrayNode::Error(Error::VALUE),
None => ArrayNode::Error(Error::VALUE),
};
data_row.push(node);
}

View File

@@ -1,9 +1,9 @@
use crate::cast::NumberOrArray;
use crate::constants::{LAST_COLUMN, LAST_ROW};
use crate::constants::{EXCEL_PRECISION, LAST_COLUMN, LAST_ROW};
use crate::expressions::parser::ArrayNode;
use crate::expressions::types::CellReferenceIndex;
use crate::functions::math_util::{from_roman, to_roman_with_form};
use crate::number_format::to_precision;
use crate::number_format::{to_excel_precision, to_precision};
use crate::single_number_fn;
use crate::{
calc_result::CalcResult, expressions::parser::Node, expressions::token::Error, model::Model,
@@ -934,11 +934,11 @@ impl Model {
if args.len() != 2 {
return CalcResult::new_args_number_error(cell);
}
let value = match self.get_number(&args[0], cell) {
let value = match self.get_number_no_bools(&args[0], cell) {
Ok(f) => f,
Err(s) => return s,
};
let divisor = match self.get_number(&args[1], cell) {
let divisor = match self.get_number_no_bools(&args[1], cell) {
Ok(f) => f,
Err(s) => return s,
};
@@ -984,7 +984,9 @@ impl Model {
};
}
let result = f64::floor(value / significance) * significance;
// Apply Excel precision to the ratio to handle floating-point rounding errors
let ratio = to_excel_precision(value / significance, EXCEL_PRECISION);
let result = f64::floor(ratio) * significance;
CalcResult::Number(result)
}
@@ -1022,7 +1024,7 @@ impl Model {
cell: CellReferenceIndex,
) -> CalcResult {
let arg_count = args.len();
if arg_count > 3 {
if !(1..=3).contains(&arg_count) {
return CalcResult::new_args_number_error(cell);
}
let value = match self.get_number(&args[0], cell) {
@@ -1063,7 +1065,7 @@ impl Model {
cell: CellReferenceIndex,
) -> CalcResult {
let arg_count = args.len();
if arg_count > 2 {
if !(1..=2).contains(&arg_count) {
return CalcResult::new_args_number_error(cell);
}
let value = match self.get_number(&args[0], cell) {
@@ -1093,7 +1095,7 @@ impl Model {
pub(crate) fn fn_floor_math(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
let arg_count = args.len();
if arg_count > 3 {
if !(1..=3).contains(&arg_count) {
return CalcResult::new_args_number_error(cell);
}
let value = match self.get_number(&args[0], cell) {
@@ -1121,10 +1123,14 @@ impl Model {
}
let significance = significance.abs();
if value < 0.0 && mode != 0.0 {
let result = f64::ceil(value / significance) * significance;
// Apply Excel precision to handle floating-point rounding errors
let ratio = to_excel_precision(value / significance, EXCEL_PRECISION);
let result = f64::ceil(ratio) * significance;
CalcResult::Number(result)
} else {
let result = f64::floor(value / significance) * significance;
// Apply Excel precision to handle floating-point rounding errors
let ratio = to_excel_precision(value / significance, EXCEL_PRECISION);
let result = f64::floor(ratio) * significance;
CalcResult::Number(result)
}
}
@@ -1135,7 +1141,7 @@ impl Model {
cell: CellReferenceIndex,
) -> CalcResult {
let arg_count = args.len();
if arg_count > 2 {
if !(1..=2).contains(&arg_count) {
return CalcResult::new_args_number_error(cell);
}
let value = match self.get_number(&args[0], cell) {
@@ -1154,7 +1160,9 @@ impl Model {
return CalcResult::Number(0.0);
}
let result = f64::floor(value / significance) * significance;
// Apply Excel precision to handle floating-point rounding errors
let ratio = to_excel_precision(value / significance, EXCEL_PRECISION);
let result = f64::floor(ratio) * significance;
CalcResult::Number(result)
}
@@ -1163,11 +1171,34 @@ impl Model {
if args.len() != 2 {
return CalcResult::new_args_number_error(cell);
}
let value = match self.get_number(&args[0], cell) {
let value = self.evaluate_node_in_context(&args[0], cell);
let multiple = self.evaluate_node_in_context(&args[1], cell);
// if either is empty => #N/A
if matches!(value, CalcResult::EmptyArg) || matches!(multiple, CalcResult::EmptyArg) {
return CalcResult::Error {
error: Error::NA,
origin: cell,
message: "Bad argument for MROUND".to_string(),
};
}
// Booleans are not cast
if matches!(value, CalcResult::Boolean(_)) {
return CalcResult::new_error(Error::VALUE, cell, "Expecting number".to_string());
}
if matches!(multiple, CalcResult::Boolean(_)) {
return CalcResult::new_error(Error::VALUE, cell, "Expecting number".to_string());
}
let value = match self.cast_to_number(value, cell) {
Ok(f) => f,
Err(s) => return s,
};
let multiple = match self.get_number(&args[1], cell) {
let multiple = match self.cast_to_number(multiple, cell) {
Ok(f) => f,
Err(s) => return s,
};
@@ -1186,7 +1217,7 @@ impl Model {
}
pub(crate) fn fn_trunc(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
if args.len() > 2 {
if !(1..=2).contains(&args.len()) {
return CalcResult::new_args_number_error(cell);
}
let value = match self.get_number(&args[0], cell) {
@@ -1210,11 +1241,15 @@ impl Model {
if !(-15.0..=15.0).contains(&num_digits) {
return CalcResult::Number(value);
}
CalcResult::Number(if value >= 0.0 {
let v = if value >= 0.0 {
f64::floor(value * 10f64.powf(num_digits)) / 10f64.powf(num_digits)
} else {
f64::ceil(value * 10f64.powf(num_digits)) / 10f64.powf(num_digits)
})
};
if value.is_finite() && v.is_infinite() {
return CalcResult::Number(value);
}
CalcResult::Number(v)
}
single_number_fn!(fn_log10, |f| if f <= 0.0 {
@@ -1250,13 +1285,19 @@ impl Model {
} else {
Ok((f * PI).sqrt())
});
single_number_fn!(fn_acot, |f| if f == 0.0 {
Err(Error::DIV)
} else {
Ok(f64::atan(1.0 / f))
single_number_fn!(fn_acot, |f| {
let v = f64::atan(1.0 / f);
if f >= 0.0 {
Ok(v)
} else {
// To be compatible with Excel we need a different branch
// when f < 0
Ok(v + PI)
}
});
single_number_fn!(fn_acoth, |f: f64| if f.abs() == 1.0 {
Err(Error::DIV)
Err(Error::NUM)
} else {
Ok(0.5 * (f64::ln((f + 1.0) / (f - 1.0))))
});
@@ -1265,8 +1306,11 @@ impl Model {
} else {
Ok(f64::cos(f) / f64::sin(f))
});
single_number_fn!(fn_coth, |f| if f == 0.0 {
single_number_fn!(fn_coth, |f: f64| if f == 0.0 {
Err(Error::DIV)
} else if f.abs() > 20.0 {
// for values > 20.0 this is exact in f64
Ok(f.signum())
} else {
Ok(f64::cosh(f) / f64::sinh(f))
});
@@ -1280,16 +1324,8 @@ impl Model {
} else {
Ok(1.0 / f64::sinh(f))
});
single_number_fn!(fn_sec, |f| if f == 0.0 {
Err(Error::DIV)
} else {
Ok(1.0 / f64::cos(f))
});
single_number_fn!(fn_sech, |f| if f == 0.0 {
Err(Error::DIV)
} else {
Ok(1.0 / f64::cosh(f))
});
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();
@@ -1320,7 +1356,13 @@ impl Model {
}
Ok(acc)
});
single_number_fn!(fn_sign, |f| Ok(f64::signum(f)));
single_number_fn!(fn_sign, |f| {
if f == 0.0 {
Ok(0.0)
} else {
Ok(f64::signum(f))
}
});
single_number_fn!(fn_degrees, |f| Ok(f * (180.0 / PI)));
single_number_fn!(fn_radians, |f| Ok(f * (PI / 180.0)));
single_number_fn!(fn_odd, |f| {

View File

@@ -0,0 +1,230 @@
use crate::expressions::types::CellReferenceIndex;
use crate::{
calc_result::CalcResult, expressions::parser::Node, expressions::token::Error, model::Model,
};
type TwoMatricesResult = (i32, i32, Vec<Option<f64>>, Vec<Option<f64>>);
// Helper to check if two shapes are the same or compatible 1D shapes
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 {
// SUMX2MY2(array_x, array_y) - Returns the sum of the difference of squares
pub(crate) fn fn_sumx2my2(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
let result = match self.fn_get_two_matrices(args, cell) {
Ok(s) => s,
Err(s) => return s,
};
let (_, _, values_left, values_right) = result;
let mut sum = 0.0;
for (x_opt, y_opt) in values_left.into_iter().zip(values_right.into_iter()) {
let x = x_opt.unwrap_or(0.0);
let y = y_opt.unwrap_or(0.0);
sum += x * x - y * y;
}
CalcResult::Number(sum)
}
// SUMX2PY2(array_x, array_y) - Returns the sum of the sum of squares
pub(crate) fn fn_sumx2py2(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
let result = match self.fn_get_two_matrices(args, cell) {
Ok(s) => s,
Err(s) => return s,
};
let (_rows, _cols, values_left, values_right) = result;
let mut sum = 0.0;
for (x_opt, y_opt) in values_left.into_iter().zip(values_right.into_iter()) {
let x = x_opt.unwrap_or(0.0);
let y = y_opt.unwrap_or(0.0);
sum += x * x + y * y;
}
CalcResult::Number(sum)
}
// SUMXMY2(array_x, array_y) - Returns the sum of squares of differences
pub(crate) fn fn_sumxmy2(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
let result = match self.fn_get_two_matrices(args, cell) {
Ok(s) => s,
Err(s) => return s,
};
let (_, _, values_left, values_right) = result;
let mut sum = 0.0;
for (x_opt, y_opt) in values_left.into_iter().zip(values_right.into_iter()) {
let x = x_opt.unwrap_or(0.0);
let y = y_opt.unwrap_or(0.0);
let diff = x - y;
sum += diff * diff;
}
CalcResult::Number(sum)
}
// Helper function to extract and validate two matrices (ranges or arrays) with compatible shapes.
// Returns (rows, cols, values_left, values_right) or an error.
pub(crate) fn fn_get_two_matrices(
&mut self,
args: &[Node],
cell: CellReferenceIndex,
) -> Result<TwoMatricesResult, CalcResult> {
if args.len() != 2 {
return Err(CalcResult::new_args_number_error(cell));
}
let x_range = self.evaluate_node_in_context(&args[0], cell);
let y_range = self.evaluate_node_in_context(&args[1], cell);
let result = match (x_range, y_range) {
(
CalcResult::Range {
left: l1,
right: r1,
},
CalcResult::Range {
left: l2,
right: r2,
},
) => {
if l1.sheet != l2.sheet {
return Err(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 Err(CalcResult::new_error(
Error::VALUE,
cell,
"Ranges must be of the same shape".to_string(),
));
}
let values_left = self.values_from_range(l1, r1)?;
let values_right = self.values_from_range(l2, r2)?;
(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 Err(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 Err(CalcResult::new_error(
Error::VALUE,
cell,
format!("Error in first array: {:?}", error),
));
}
Ok(v) => v,
};
let values_right = self.values_from_range(l2, r2)?;
(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 Err(CalcResult::new_error(
Error::VALUE,
cell,
"Range and array must be of the same shape".to_string(),
));
}
let values_left = self.values_from_range(l1, r1)?;
let values_right = match self.values_from_array(right) {
Err(error) => {
return Err(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 Err(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 Err(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 Err(CalcResult::new_error(
Error::VALUE,
cell,
format!("Error in second array: {:?}", error),
));
}
Ok(v) => v,
};
(rows1, cols1, values_left, values_right)
}
_ => {
return Err(CalcResult::new_error(
Error::VALUE,
cell,
"Both arguments must be ranges or arrays".to_string(),
));
}
};
Ok(result)
}
}

View File

@@ -8,6 +8,7 @@ use crate::{
};
pub(crate) mod binary_search;
mod database;
mod date_and_time;
mod engineering;
mod financial;
@@ -18,6 +19,7 @@ mod lookup_and_reference;
mod macros;
mod math_util;
mod mathematical;
mod mathematical_sum;
mod statistical;
mod subtotal;
mod text;
@@ -75,6 +77,9 @@ pub enum Function {
Sum,
Sumif,
Sumifs,
Sumx2my2,
Sumx2py2,
Sumxmy2,
Tan,
Tanh,
Acot,
@@ -189,6 +194,92 @@ pub enum Function {
Minifs,
Geomean,
Avedev,
BetaDist,
BetaInv,
BinomDist,
BinomDistRange,
BinomInv,
ChisqDist,
ChisqDistRT,
ChisqInv,
ChisqInvRT,
ChisqTest,
ConfidenceNorm,
ConfidenceT,
CovarianceP,
CovarianceS,
Devsq,
ExponDist,
FDist,
FDistRT,
FInv,
FInvRT,
FTest,
Fisher,
FisherInv,
// Forecast,
Gamma,
GammaDist,
GammaInv,
GammaLn,
GammaLnPrecise,
Gauss,
Harmean,
HypGeomDist,
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,
Skew,
SkewP,
Small,
Standardize,
StDevP,
StDevS,
Stdeva,
Stdevpa,
TDist,
TDist2T,
TDistRT,
TInv,
TInv2T,
TTest,
// Trend,
// Trimmean,
VarP,
VarS,
VarpA,
VarA,
WeibullDist,
ZTest,
// Date and time
Date,
Datedif,
@@ -217,14 +308,6 @@ pub enum Function {
Isoweeknum,
// Financial
Accrint,
Accrintm,
Coupdaybs,
Coupdays,
Coupdaysnc,
Coupncd,
Coupnum,
Couppcd,
Cumipmt,
Cumprinc,
Db,
@@ -233,7 +316,6 @@ pub enum Function {
Dollarfr,
Effect,
Fv,
Fvschedule,
Ipmt,
Irr,
Ispmt,
@@ -241,12 +323,9 @@ pub enum Function {
Nominal,
Nper,
Npv,
Duration,
Mduration,
Pduration,
Pmt,
Ppmt,
Price,
Pv,
Rate,
Rri,
@@ -255,16 +334,8 @@ pub enum Function {
Tbilleq,
Tbillprice,
Tbillyield,
Pricedisc,
Pricemat,
Yielddisc,
Yieldmat,
Disc,
Received,
Intrate,
Xirr,
Xnpv,
Yield,
// Engineering: Bessel and transcendental functions
Besseli,
@@ -330,10 +401,30 @@ pub enum Function {
Delta,
Gestep,
Subtotal,
// Database
Daverage,
Dcount,
Dget,
Dmax,
Dmin,
Dsum,
Dcounta,
Dproduct,
Dstdev,
Dvar,
Dvarp,
Dstdevp,
Correl,
Rsq,
Intercept,
Slope,
Steyx,
}
impl Function {
pub fn into_iter() -> IntoIter<Function, 276> {
pub fn into_iter() -> IntoIter<Function, 345> {
[
Function::And,
Function::False,
@@ -410,6 +501,9 @@ impl Function {
Function::Sum,
Function::Sumif,
Function::Sumifs,
Function::Sumx2my2,
Function::Sumx2py2,
Function::Sumxmy2,
Function::Choose,
Function::Column,
Function::Columns,
@@ -458,6 +552,7 @@ impl Function {
Function::Type,
Function::Sheet,
Function::Average,
Function::Avedev,
Function::Averagea,
Function::Averageif,
Function::Averageifs,
@@ -494,23 +589,18 @@ impl Function {
Function::WorkdayIntl,
Function::Yearfrac,
Function::Isoweeknum,
Function::Accrint,
Function::Accrintm,
Function::Pmt,
Function::Pv,
Function::Rate,
Function::Nper,
Function::Fv,
Function::Fvschedule,
Function::Ppmt,
Function::Price,
Function::Ipmt,
Function::Npv,
Function::Mirr,
Function::Irr,
Function::Xirr,
Function::Xnpv,
Function::Yield,
Function::Rept,
Function::Textafter,
Function::Textbefore,
@@ -522,25 +612,10 @@ impl Function {
Function::Syd,
Function::Nominal,
Function::Effect,
Function::Duration,
Function::Mduration,
Function::Pduration,
Function::Coupdaybs,
Function::Coupdays,
Function::Coupdaysnc,
Function::Coupncd,
Function::Coupnum,
Function::Couppcd,
Function::Tbillyield,
Function::Tbillprice,
Function::Tbilleq,
Function::Pricedisc,
Function::Pricemat,
Function::Yielddisc,
Function::Yieldmat,
Function::Disc,
Function::Received,
Function::Intrate,
Function::Dollarde,
Function::Dollarfr,
Function::Ddb,
@@ -611,6 +686,91 @@ impl Function {
Function::Cell,
Function::Info,
Function::Sheets,
Function::Daverage,
Function::Dcount,
Function::Dget,
Function::Dmax,
Function::Dmin,
Function::Dsum,
Function::Dcounta,
Function::Dproduct,
Function::Dstdev,
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::FTest,
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,
Function::Correl,
Function::Rsq,
Function::Intercept,
Function::Slope,
Function::Steyx,
Function::Large,
Function::Median,
Function::Small,
Function::RankAvg,
Function::RankEq,
Function::Skew,
Function::SkewP,
Function::Harmean,
Function::Gauss,
Function::Kurt,
Function::MaxA,
Function::MinA,
]
.into_iter()
}
@@ -664,6 +824,78 @@ impl Function {
Function::Arabic => "_xlfn.ARABIC".to_string(),
Function::Combina => "_xlfn.COMBINA".to_string(),
Function::Sheets => "_xlfn.SHEETS".to_string(),
Function::Acoth => "_xlfn.ACOTH".to_string(),
Function::Cot => "_xlfn.COT".to_string(),
Function::Coth => "_xlfn.COTH".to_string(),
Function::Csc => "_xlfn.CSC".to_string(),
Function::Csch => "_xlfn.CSCH".to_string(),
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::FTest => "_xlfn.F.TEST".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(),
Function::SkewP => "_xlfn.SKEW.P".to_string(),
Function::RankAvg => "_xlfn.RANK.AVG".to_string(),
Function::RankEq => "_xlfn.RANK.EQ".to_string(),
_ => self.to_string(),
}
@@ -699,14 +931,14 @@ impl Function {
"ASINH" => Some(Function::Asinh),
"ACOSH" => Some(Function::Acosh),
"ATANH" => Some(Function::Atanh),
"ACOT" => Some(Function::Acot),
"COTH" => Some(Function::Coth),
"COT" => Some(Function::Cot),
"CSC" => Some(Function::Csc),
"CSCH" => Some(Function::Csch),
"SEC" => Some(Function::Sec),
"SECH" => Some(Function::Sech),
"ACOTH" => Some(Function::Acoth),
"ACOT" | "_XLFN.ACOT" => Some(Function::Acot),
"COTH" | "_XLFN.COTH" => Some(Function::Coth),
"COT" | "_XLFN.COT" => Some(Function::Cot),
"CSC" | "_XLFN.CSC" => Some(Function::Csc),
"CSCH" | "_XLFN.CSCH" => Some(Function::Csch),
"SEC" | "_XLFN.SEC" => Some(Function::Sec),
"SECH" | "_XLFN.SECH" => Some(Function::Sech),
"ACOTH" | "_XLFN.ACOTH" => Some(Function::Acoth),
"FACT" => Some(Function::Fact),
"FACTDOUBLE" => Some(Function::Factdouble),
"EXP" => Some(Function::Exp),
@@ -816,6 +1048,7 @@ 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),
@@ -853,20 +1086,15 @@ impl Function {
"YEARFRAC" => Some(Function::Yearfrac),
"ISOWEEKNUM" | "_XLFN.ISOWEEKNUM" => Some(Function::Isoweeknum),
// Financial
"ACCRINT" => Some(Function::Accrint),
"ACCRINTM" => Some(Function::Accrintm),
"PMT" => Some(Function::Pmt),
"PV" => Some(Function::Pv),
"RATE" => Some(Function::Rate),
"NPER" => Some(Function::Nper),
"FV" => Some(Function::Fv),
"FVSCHEDULE" => Some(Function::Fvschedule),
"PPMT" => Some(Function::Ppmt),
"PRICE" => Some(Function::Price),
"IPMT" => Some(Function::Ipmt),
"NPV" => Some(Function::Npv),
"XNPV" => Some(Function::Xnpv),
"YIELD" => Some(Function::Yield),
"MIRR" => Some(Function::Mirr),
"IRR" => Some(Function::Irr),
"XIRR" => Some(Function::Xirr),
@@ -877,27 +1105,11 @@ impl Function {
"SYD" => Some(Function::Syd),
"NOMINAL" => Some(Function::Nominal),
"EFFECT" => Some(Function::Effect),
"DURATION" => Some(Function::Duration),
"MDURATION" => Some(Function::Mduration),
"PDURATION" | "_XLFN.PDURATION" => Some(Function::Pduration),
"COUPDAYBS" => Some(Function::Coupdaybs),
"COUPDAYS" => Some(Function::Coupdays),
"COUPDAYSNC" => Some(Function::Coupdaysnc),
"COUPNCD" => Some(Function::Coupncd),
"COUPNUM" => Some(Function::Coupnum),
"COUPPCD" => Some(Function::Couppcd),
"TBILLYIELD" => Some(Function::Tbillyield),
"TBILLPRICE" => Some(Function::Tbillprice),
"TBILLEQ" => Some(Function::Tbilleq),
"PRICEDISC" => Some(Function::Pricedisc),
"PRICEMAT" => Some(Function::Pricemat),
"YIELDDISC" => Some(Function::Yielddisc),
"YIELDMAT" => Some(Function::Yieldmat),
"DISC" => Some(Function::Disc),
"RECEIVED" => Some(Function::Received),
"INTRATE" => Some(Function::Intrate),
"DOLLARDE" => Some(Function::Dollarde),
"DOLLARFR" => Some(Function::Dollarfr),
@@ -970,6 +1182,98 @@ impl Function {
"INFO" => Some(Function::Info),
"SHEETS" | "_XLFN.SHEETS" => Some(Function::Sheets),
"DAVERAGE" => Some(Function::Daverage),
"DCOUNT" => Some(Function::Dcount),
"DGET" => Some(Function::Dget),
"DMAX" => Some(Function::Dmax),
"DMIN" => Some(Function::Dmin),
"DSUM" => Some(Function::Dsum),
"DCOUNTA" => Some(Function::Dcounta),
"DPRODUCT" => Some(Function::Dproduct),
"DSTDEV" => Some(Function::Dstdev),
"DVAR" => Some(Function::Dvar),
"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),
"F.TEST" | "_XLFN.F.TEST" => Some(Function::FTest),
"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),
"SUMX2MY2" => Some(Function::Sumx2my2),
"SUMX2PY2" => Some(Function::Sumx2py2),
"SUMXMY2" => Some(Function::Sumxmy2),
"CORREL" => Some(Function::Correl),
"RSQ" => Some(Function::Rsq),
"INTERCEPT" => Some(Function::Intercept),
"SLOPE" => Some(Function::Slope),
"STEYX" => Some(Function::Steyx),
"SKEW.P" | "_XLFN.SKEW.P" => Some(Function::SkewP),
"SKEW" => Some(Function::Skew),
"KURT" => Some(Function::Kurt),
"HARMEAN" => Some(Function::Harmean),
"MEDIAN" => Some(Function::Median),
"GAUSS" => Some(Function::Gauss),
"MINA" => Some(Function::MinA),
"MAXA" => Some(Function::MaxA),
"SMALL" => Some(Function::Small),
"LARGE" => Some(Function::Large),
"RANK.EQ" | "_XLFN.RANK.EQ" => Some(Function::RankEq),
"RANK.AVG" | "_XLFN.RANK.AVG" => Some(Function::RankAvg),
_ => None,
}
}
@@ -1078,6 +1382,7 @@ 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"),
@@ -1113,23 +1418,18 @@ impl fmt::Display for Function {
Function::WorkdayIntl => write!(f, "WORKDAY.INTL"),
Function::Yearfrac => write!(f, "YEARFRAC"),
Function::Isoweeknum => write!(f, "ISOWEEKNUM"),
Function::Accrint => write!(f, "ACCRINT"),
Function::Accrintm => write!(f, "ACCRINTM"),
Function::Pmt => write!(f, "PMT"),
Function::Pv => write!(f, "PV"),
Function::Rate => write!(f, "RATE"),
Function::Nper => write!(f, "NPER"),
Function::Fv => write!(f, "FV"),
Function::Fvschedule => write!(f, "FVSCHEDULE"),
Function::Ppmt => write!(f, "PPMT"),
Function::Price => write!(f, "PRICE"),
Function::Ipmt => write!(f, "IPMT"),
Function::Npv => write!(f, "NPV"),
Function::Mirr => write!(f, "MIRR"),
Function::Irr => write!(f, "IRR"),
Function::Xirr => write!(f, "XIRR"),
Function::Xnpv => write!(f, "XNPV"),
Function::Yield => write!(f, "YIELD"),
Function::Rept => write!(f, "REPT"),
Function::Textafter => write!(f, "TEXTAFTER"),
Function::Textbefore => write!(f, "TEXTBEFORE"),
@@ -1141,25 +1441,10 @@ impl fmt::Display for Function {
Function::Syd => write!(f, "SYD"),
Function::Nominal => write!(f, "NOMINAL"),
Function::Effect => write!(f, "EFFECT"),
Function::Duration => write!(f, "DURATION"),
Function::Mduration => write!(f, "MDURATION"),
Function::Pduration => write!(f, "PDURATION"),
Function::Coupdaybs => write!(f, "COUPDAYBS"),
Function::Coupdays => write!(f, "COUPDAYS"),
Function::Coupdaysnc => write!(f, "COUPDAYSNC"),
Function::Coupncd => write!(f, "COUPNCD"),
Function::Coupnum => write!(f, "COUPNUM"),
Function::Couppcd => write!(f, "COUPPCD"),
Function::Tbillyield => write!(f, "TBILLYIELD"),
Function::Tbillprice => write!(f, "TBILLPRICE"),
Function::Tbilleq => write!(f, "TBILLEQ"),
Function::Pricedisc => write!(f, "PRICEDISC"),
Function::Pricemat => write!(f, "PRICEMAT"),
Function::Yielddisc => write!(f, "YIELDDISC"),
Function::Yieldmat => write!(f, "YIELDMAT"),
Function::Disc => write!(f, "DISC"),
Function::Received => write!(f, "RECEIVED"),
Function::Intrate => write!(f, "INTRATE"),
Function::Dollarde => write!(f, "DOLLARDE"),
Function::Dollarfr => write!(f, "DOLLARFR"),
Function::Ddb => write!(f, "DDB"),
@@ -1250,11 +1535,99 @@ impl fmt::Display for Function {
Function::Combin => write!(f, "COMBIN"),
Function::Combina => write!(f, "COMBINA"),
Function::Sumsq => write!(f, "SUMSQ"),
Function::N => write!(f, "N"),
Function::Cell => write!(f, "CELL"),
Function::Info => write!(f, "INFO"),
Function::Sheets => write!(f, "SHEETS"),
Function::Daverage => write!(f, "DAVERAGE"),
Function::Dcount => write!(f, "DCOUNT"),
Function::Dget => write!(f, "DGET"),
Function::Dmax => write!(f, "DMAX"),
Function::Dmin => write!(f, "DMIN"),
Function::Dsum => write!(f, "DSUM"),
Function::Dcounta => write!(f, "DCOUNTA"),
Function::Dproduct => write!(f, "DPRODUCT"),
Function::Dstdev => write!(f, "DSTDEV"),
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::FTest => write!(f, "F.TEST"),
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"),
Function::Sumx2my2 => write!(f, "SUMX2MY2"),
Function::Sumx2py2 => write!(f, "SUMX2PY2"),
Function::Sumxmy2 => write!(f, "SUMXMY2"),
Function::Correl => write!(f, "CORREL"),
Function::Rsq => write!(f, "RSQ"),
Function::Intercept => write!(f, "INTERCEPT"),
Function::Slope => write!(f, "SLOPE"),
Function::Steyx => write!(f, "STEYX"),
// new ones
Function::Gauss => write!(f, "GAUSS"),
Function::Harmean => write!(f, "HARMEAN"),
Function::Kurt => write!(f, "KURT"),
Function::Large => write!(f, "LARGE"),
Function::MaxA => write!(f, "MAXA"),
Function::Median => write!(f, "MEDIAN"),
Function::MinA => write!(f, "MINA"),
Function::RankAvg => write!(f, "RANK.AVG"),
Function::RankEq => write!(f, "RANK.EQ"),
Function::Skew => write!(f, "SKEW"),
Function::SkewP => write!(f, "SKEW.P"),
Function::Small => write!(f, "SMALL"),
}
}
}
@@ -1375,6 +1748,7 @@ 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),
@@ -1410,24 +1784,18 @@ impl Model {
Function::WorkdayIntl => self.fn_workday_intl(args, cell),
Function::Yearfrac => self.fn_yearfrac(args, cell),
Function::Isoweeknum => self.fn_isoweeknum(args, cell),
// Financial
Function::Accrint => self.fn_accrint(args, cell),
Function::Accrintm => self.fn_accrintm(args, cell),
Function::Pmt => self.fn_pmt(args, cell),
Function::Pv => self.fn_pv(args, cell),
Function::Rate => self.fn_rate(args, cell),
Function::Nper => self.fn_nper(args, cell),
Function::Fv => self.fn_fv(args, cell),
Function::Fvschedule => self.fn_fvschedule(args, cell),
Function::Ppmt => self.fn_ppmt(args, cell),
Function::Price => self.fn_price(args, cell),
Function::Ipmt => self.fn_ipmt(args, cell),
Function::Npv => self.fn_npv(args, cell),
Function::Mirr => self.fn_mirr(args, cell),
Function::Irr => self.fn_irr(args, cell),
Function::Xirr => self.fn_xirr(args, cell),
Function::Xnpv => self.fn_xnpv(args, cell),
Function::Yield => self.fn_yield(args, cell),
Function::Rept => self.fn_rept(args, cell),
Function::Textafter => self.fn_textafter(args, cell),
Function::Textbefore => self.fn_textbefore(args, cell),
@@ -1439,25 +1807,10 @@ impl Model {
Function::Syd => self.fn_syd(args, cell),
Function::Nominal => self.fn_nominal(args, cell),
Function::Effect => self.fn_effect(args, cell),
Function::Duration => self.fn_duration(args, cell),
Function::Mduration => self.fn_mduration(args, cell),
Function::Pduration => self.fn_pduration(args, cell),
Function::Coupdaybs => self.fn_coupdaybs(args, cell),
Function::Coupdays => self.fn_coupdays(args, cell),
Function::Coupdaysnc => self.fn_coupdaysnc(args, cell),
Function::Coupncd => self.fn_coupncd(args, cell),
Function::Coupnum => self.fn_coupnum(args, cell),
Function::Couppcd => self.fn_couppcd(args, cell),
Function::Tbillyield => self.fn_tbillyield(args, cell),
Function::Tbillprice => self.fn_tbillprice(args, cell),
Function::Tbilleq => self.fn_tbilleq(args, cell),
Function::Pricedisc => self.fn_pricedisc(args, cell),
Function::Pricemat => self.fn_pricemat(args, cell),
Function::Yielddisc => self.fn_yielddisc(args, cell),
Function::Yieldmat => self.fn_yieldmat(args, cell),
Function::Disc => self.fn_disc(args, cell),
Function::Received => self.fn_received(args, cell),
Function::Intrate => self.fn_intrate(args, cell),
Function::Dollarde => self.fn_dollarde(args, cell),
Function::Dollarfr => self.fn_dollarfr(args, cell),
Function::Ddb => self.fn_ddb(args, cell),
@@ -1560,6 +1913,94 @@ impl Model {
Function::Cell => self.fn_cell(args, cell),
Function::Info => self.fn_info(args, cell),
Function::Sheets => self.fn_sheets(args, cell),
Function::Daverage => self.fn_daverage(args, cell),
Function::Dcount => self.fn_dcount(args, cell),
Function::Dget => self.fn_dget(args, cell),
Function::Dmax => self.fn_dmax(args, cell),
Function::Dmin => self.fn_dmin(args, cell),
Function::Dsum => self.fn_dsum(args, cell),
Function::Dcounta => self.fn_dcounta(args, cell),
Function::Dproduct => self.fn_dproduct(args, cell),
Function::Dstdev => self.fn_dstdev(args, cell),
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::FTest => self.fn_f_test(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),
Function::Sumx2my2 => self.fn_sumx2my2(args, cell),
Function::Sumx2py2 => self.fn_sumx2py2(args, cell),
Function::Sumxmy2 => self.fn_sumxmy2(args, cell),
Function::Correl => self.fn_correl(args, cell),
Function::Rsq => self.fn_rsq(args, cell),
Function::Intercept => self.fn_intercept(args, cell),
Function::Slope => self.fn_slope(args, cell),
Function::Steyx => self.fn_steyx(args, cell),
Function::Gauss => self.fn_gauss(args, cell),
Function::Harmean => self.fn_harmean(args, cell),
Function::Kurt => self.fn_kurt(args, cell),
Function::Large => self.fn_large(args, cell),
Function::MaxA => self.fn_maxa(args, cell),
Function::Median => self.fn_median(args, cell),
Function::MinA => self.fn_mina(args, cell),
Function::RankAvg => self.fn_rank_avg(args, cell),
Function::RankEq => self.fn_rank_eq(args, cell),
Function::Skew => self.fn_skew(args, cell),
Function::SkewP => self.fn_skew_p(args, cell),
Function::Small => self.fn_small(args, cell),
}
}
}

View File

@@ -1,733 +0,0 @@
use crate::constants::{LAST_COLUMN, LAST_ROW};
use crate::expressions::types::CellReferenceIndex;
use crate::{
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() {
return CalcResult::new_args_number_error(cell);
}
let mut count = 0.0;
let mut sum = 0.0;
for arg in args {
match self.evaluate_node_in_context(arg, cell) {
CalcResult::Number(value) => {
count += 1.0;
sum += value;
}
CalcResult::Boolean(b) => {
if let Node::ReferenceKind { .. } = arg {
} else {
sum += 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;
sum += 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>() {
sum += 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(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);
}
let mut count = 0.0;
let mut sum = 0.0;
for arg in args {
match self.evaluate_node_in_context(arg, cell) {
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::String(_) => count += 1.0,
CalcResult::Number(value) => {
count += 1.0;
sum += value;
}
CalcResult::Boolean(b) => {
if b {
sum += 1.0;
}
count += 1.0;
}
error @ CalcResult::Error { .. } => return error,
CalcResult::Range { .. } => {
return CalcResult::new_error(
Error::ERROR,
cell,
"Unexpected Range".to_string(),
);
}
CalcResult::EmptyCell | CalcResult::EmptyArg => {}
CalcResult::Array(_) => {
return CalcResult::Error {
error: Error::NIMPL,
origin: cell,
message: "Arrays not supported yet".to_string(),
}
}
}
}
}
}
CalcResult::Number(value) => {
count += 1.0;
sum += value;
}
CalcResult::String(s) => {
if let Node::ReferenceKind { .. } = arg {
// Do nothing
count += 1.0;
} else if let Ok(t) = s.parse::<f64>() {
sum += t;
count += 1.0;
} else {
return CalcResult::Error {
error: Error::VALUE,
origin: cell,
message: "Argument cannot be cast into number".to_string(),
};
}
}
CalcResult::Boolean(b) => {
count += 1.0;
if b {
sum += 1.0;
}
}
error @ CalcResult::Error { .. } => return error,
CalcResult::EmptyCell | CalcResult::EmptyArg => {}
CalcResult::Array(_) => {
return CalcResult::Error {
error: Error::NIMPL,
origin: cell,
message: "Arrays not supported yet".to_string(),
}
}
};
}
if count == 0.0 {
return CalcResult::Error {
error: Error::DIV,
origin: cell,
message: "Division by Zero".to_string(),
};
}
CalcResult::Number(sum / count)
}
pub(crate) fn fn_count(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
if args.is_empty() {
return CalcResult::new_args_number_error(cell);
}
let mut result = 0.0;
for arg in args {
match self.evaluate_node_in_context(arg, cell) {
CalcResult::Number(_) => {
result += 1.0;
}
CalcResult::Boolean(_) => {
if !matches!(arg, Node::ReferenceKind { .. }) {
result += 1.0;
}
}
CalcResult::String(s) => {
if !matches!(arg, Node::ReferenceKind { .. }) && s.parse::<f64>().is_ok() {
result += 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) {
if let CalcResult::Number(_) = self.evaluate_cell(CellReferenceIndex {
sheet: left.sheet,
row,
column,
}) {
result += 1.0;
}
}
}
}
_ => {
// Ignore everything else
}
};
}
CalcResult::Number(result)
}
pub(crate) fn fn_counta(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
if args.is_empty() {
return CalcResult::new_args_number_error(cell);
}
let mut result = 0.0;
for arg in args {
match self.evaluate_node_in_context(arg, cell) {
CalcResult::EmptyCell | CalcResult::EmptyArg => {}
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::EmptyCell | CalcResult::EmptyArg => {}
_ => {
result += 1.0;
}
}
}
}
}
_ => {
result += 1.0;
}
};
}
CalcResult::Number(result)
}
pub(crate) fn fn_countblank(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
// COUNTBLANK requires only one argument
if args.len() != 1 {
return CalcResult::new_args_number_error(cell);
}
let mut result = 0.0;
for arg in args {
match self.evaluate_node_in_context(arg, cell) {
CalcResult::EmptyCell | CalcResult::EmptyArg => result += 1.0,
CalcResult::String(s) => {
if s.is_empty() {
result += 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::EmptyCell | CalcResult::EmptyArg => result += 1.0,
CalcResult::String(s) => {
if s.is_empty() {
result += 1.0
}
}
_ => {}
}
}
}
}
_ => {}
};
}
CalcResult::Number(result)
}
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)
}
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))
}
}

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@@ -0,0 +1,213 @@
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)
}
}

View File

@@ -0,0 +1,311 @@
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)
}
}

View File

@@ -0,0 +1,397 @@
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,
};
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 {
let (width, height, values_left, values_right) = match self.fn_get_two_matrices(args, cell)
{
Ok(v) => v,
Err(r) => return r,
};
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)
}
}

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@@ -0,0 +1,227 @@
use crate::expressions::types::CellReferenceIndex;
use crate::{
calc_result::CalcResult, expressions::parser::Node, expressions::token::Error, model::Model,
};
impl Model {
// CORREL(array1, array2) - Returns the correlation coefficient of two data sets
pub(crate) fn fn_correl(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
let (_, _, values_left, values_right) = match self.fn_get_two_matrices(args, cell) {
Ok(s) => s,
Err(e) => return e,
};
let mut n = 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;
for (x_opt, y_opt) in values_left.into_iter().zip(values_right.into_iter()) {
if let (Some(x), Some(y)) = (x_opt, y_opt) {
n += 1.0;
sum_x += x;
sum_y += y;
sum_x2 += x * x;
sum_y2 += y * y;
sum_xy += x * y;
}
}
// Need at least 2 valid pairs
if n < 2.0 {
return CalcResult::new_error(
Error::DIV,
cell,
"CORREL requires at least two numeric data points in each range".to_string(),
);
}
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;
let denom = (denom_x * denom_y).sqrt();
if denom == 0.0 || !denom.is_finite() {
return CalcResult::new_error(
Error::DIV,
cell,
"Division by zero in CORREL".to_string(),
);
}
let r = num / denom;
CalcResult::Number(r)
}
// SLOPE(known_y's, known_x's) - Returns the slope of the linear regression line
pub(crate) fn fn_slope(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
let (_rows, _cols, values_y, values_x) = match self.fn_get_two_matrices(args, cell) {
Ok(s) => s,
Err(e) => return e,
};
let mut n = 0.0;
let mut sum_x = 0.0;
let mut sum_y = 0.0;
let mut sum_x2 = 0.0;
let mut sum_xy = 0.0;
let len = values_y.len().min(values_x.len());
for i in 0..len {
if let (Some(y), Some(x)) = (values_y[i], values_x[i]) {
n += 1.0;
sum_x += x;
sum_y += y;
sum_x2 += x * x;
sum_xy += x * y;
}
}
if n < 2.0 {
return CalcResult::new_error(
Error::DIV,
cell,
"SLOPE requires at least two numeric data points".to_string(),
);
}
let denom = n * sum_x2 - sum_x * sum_x;
if denom == 0.0 || !denom.is_finite() {
return CalcResult::new_error(
Error::DIV,
cell,
"Division by zero in SLOPE".to_string(),
);
}
let num = n * sum_xy - sum_x * sum_y;
let slope = num / denom;
CalcResult::Number(slope)
}
// INTERCEPT(known_y's, known_x's) - Returns the y-intercept of the linear regression line
pub(crate) fn fn_intercept(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
let (_rows, _cols, values_y, values_x) = match self.fn_get_two_matrices(args, cell) {
Ok(s) => s,
Err(e) => return e,
};
let mut n = 0.0;
let mut sum_x = 0.0;
let mut sum_y = 0.0;
let mut sum_x2 = 0.0;
let mut sum_xy = 0.0;
let len = values_y.len().min(values_x.len());
for i in 0..len {
if let (Some(y), Some(x)) = (values_y[i], values_x[i]) {
n += 1.0;
sum_x += x;
sum_y += y;
sum_x2 += x * x;
sum_xy += x * y;
}
}
if n < 2.0 {
return CalcResult::new_error(
Error::DIV,
cell,
"INTERCEPT requires at least two numeric data points".to_string(),
);
}
let denom = n * sum_x2 - sum_x * sum_x;
if denom == 0.0 || !denom.is_finite() {
return CalcResult::new_error(
Error::DIV,
cell,
"Division by zero in INTERCEPT".to_string(),
);
}
let num = n * sum_xy - sum_x * sum_y;
let slope = num / denom;
let intercept = (sum_y - slope * sum_x) / n;
CalcResult::Number(intercept)
}
// STEYX(known_y's, known_x's) - Returns the standard error of the predicted y-values
pub(crate) fn fn_steyx(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
let (_rows, _cols, values_y, values_x) = match self.fn_get_two_matrices(args, cell) {
Ok(s) => s,
Err(e) => return e,
};
let mut n = 0.0;
let mut sum_x = 0.0;
let mut sum_y = 0.0;
let mut sum_x2 = 0.0;
let mut sum_xy = 0.0;
// We need the actual pairs again later for residuals
let mut pairs: Vec<(f64, f64)> = Vec::new();
let len = values_y.len().min(values_x.len());
for i in 0..len {
if let (Some(y), Some(x)) = (values_y[i], values_x[i]) {
n += 1.0;
sum_x += x;
sum_y += y;
sum_x2 += x * x;
sum_xy += x * y;
pairs.push((x, y));
}
}
// Need at least 3 points for STEYX (n - 2 in denominator)
if n < 3.0 {
return CalcResult::new_error(
Error::DIV,
cell,
"STEYX requires at least three numeric data points".to_string(),
);
}
let denom = n * sum_x2 - sum_x * sum_x;
if denom == 0.0 || !denom.is_finite() {
return CalcResult::new_error(
Error::DIV,
cell,
"Division by zero in STEYX".to_string(),
);
}
let num = n * sum_xy - sum_x * sum_y;
let slope = num / denom;
let intercept = (sum_y - slope * sum_x) / n;
// Sum of squared residuals: Σ (y - ŷ)^2, ŷ = intercept + slope * x
let mut sse = 0.0;
for (x, y) in pairs {
let y_hat = intercept + slope * x;
let diff = y - y_hat;
sse += diff * diff;
}
let dof = n - 2.0;
if dof <= 0.0 {
return CalcResult::new_error(
Error::DIV,
cell,
"STEYX has non-positive degrees of freedom".to_string(),
);
}
let sey = (sse / dof).sqrt();
if !sey.is_finite() {
return CalcResult::new_error(Error::DIV, cell, "Numerical error in STEYX".to_string());
}
CalcResult::Number(sey)
}
}

File diff suppressed because it is too large Load Diff

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@@ -0,0 +1,264 @@
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)
}
}

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@@ -0,0 +1,135 @@
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)
}
}

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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)
}
}

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use statrs::distribution::{Continuous, ContinuousCDF, FisherSnedecor};
use crate::expressions::types::CellReferenceIndex;
use crate::functions::statistical::t_dist::sample_var;
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)
}
// F.TEST(array1, array2)
pub(crate) fn fn_f_test(&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(),
);
}
};
// Get second sample as Vec<Option<f64>>
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 values1: Vec<f64> = values1_opts.into_iter().flatten().collect();
let values2: Vec<f64> = values2_opts.into_iter().flatten().collect();
let n1 = values1.len();
let n2 = values2.len();
// If fewer than 2 numeric values in either sample -> #DIV/0!
if n1 < 2 || n2 < 2 {
return CalcResult::new_error(
Error::DIV,
cell,
"F.TEST requires at least two numeric values in each sample".to_string(),
);
}
let v1 = sample_var(&values1);
let v2 = sample_var(&values2);
if v1 <= 0.0 || v2 <= 0.0 {
return CalcResult::new_error(
Error::DIV,
cell,
"Variance of one sample is zero in F.TEST".to_string(),
);
}
// F ratio: larger variance / smaller variance
let mut f = v1 / v2;
let mut df1 = (n1 - 1) as f64;
let mut df2 = (n2 - 1) as f64;
if f < 1.0 {
f = 1.0 / f;
std::mem::swap(&mut df1, &mut df2);
}
let dist = match FisherSnedecor::new(df1, df2) {
Ok(d) => d,
Err(_) => {
return CalcResult::new_error(
Error::NUM,
cell,
"Invalid parameters for F distribution in F.TEST".to_string(),
);
}
};
// One-tailed right-tail probability
let tail = 1.0 - dist.cdf(f);
// F.TEST is two-tailed: p = 2 * tail (with F >= 1)
let mut p = 2.0 * tail;
// 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)
}
}

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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)
}
}

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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 {
pub(crate) fn fn_gauss(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
if args.len() != 1 {
return CalcResult::new_args_number_error(cell);
}
let z = match self.get_number_no_bools(&args[0], cell) {
Ok(f) => f,
Err(s) => return s,
};
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 = dist.cdf(z) - 0.5;
if !result.is_finite() {
return CalcResult::Error {
error: Error::NUM,
origin: cell,
message: "Invalid result for GAUSS".to_string(),
};
}
CalcResult::Number(result)
}
}

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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))
}
}

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@@ -0,0 +1,108 @@
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)
}
}

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@@ -0,0 +1,337 @@
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)
}
}

View File

@@ -0,0 +1,124 @@
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)
}
}

View File

@@ -0,0 +1,26 @@
mod beta;
mod binom;
mod chisq;
mod correl;
mod count_and_average;
mod covariance;
mod devsq;
mod exponential;
mod fisher;
mod gamma;
mod gauss;
mod geomean;
mod hypegeom;
mod if_ifs;
mod log_normal;
mod normal;
mod pearson;
mod phi;
mod poisson;
mod rank_eq_avg;
mod standard_dev;
mod standardize;
mod t_dist;
mod variance;
mod weibull;
mod z_test;

View File

@@ -0,0 +1,325 @@
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)
}
}

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use crate::expressions::types::CellReferenceIndex;
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 {
let (_, _, values_left, values_right) = match self.fn_get_two_matrices(args, cell) {
Ok(result) => result,
Err(e) => return e,
};
// 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();
CalcResult::Number(num / denom)
}
// RSQ(array1, array2) = CORREL(array1, array2)^2
pub(crate) fn fn_rsq(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
let (_rows, _cols, values1, values2) = match self.fn_get_two_matrices(args, cell) {
Ok(s) => s,
Err(e) => return e,
};
let mut n = 0.0_f64;
let mut sum_x = 0.0_f64;
let mut sum_y = 0.0_f64;
let mut sum_x2 = 0.0_f64;
let mut sum_y2 = 0.0_f64;
let mut sum_xy = 0.0_f64;
let len = values1.len().min(values2.len());
for i in 0..len {
if let (Some(x), Some(y)) = (values1[i], values2[i]) {
n += 1.0;
sum_x += x;
sum_y += y;
sum_x2 += x * x;
sum_y2 += y * y;
sum_xy += x * y;
}
}
if n < 2.0 {
return CalcResult::new_error(
Error::DIV,
cell,
"RSQ requires at least two numeric data points in each range".to_string(),
);
}
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;
let denom = (denom_x * denom_y).sqrt();
if denom == 0.0 || !denom.is_finite() {
return CalcResult::new_error(Error::DIV, cell, "Division by zero in RSQ".to_string());
}
let r = num / denom;
CalcResult::Number(r * r)
}
}

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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)
}
}

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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)
}
}

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use crate::expressions::types::CellReferenceIndex;
use crate::{
calc_result::CalcResult, expressions::parser::Node, expressions::token::Error, model::Model,
};
impl Model {
// Helper to collect numeric values from the 2nd argument of RANK.*
fn collect_rank_values(
&mut self,
arg: &Node,
cell: CellReferenceIndex,
) -> Result<Vec<f64>, CalcResult> {
let values = match self.evaluate_node_in_context(arg, cell) {
CalcResult::Array(array) => match self.values_from_array(array) {
Ok(v) => v,
Err(e) => {
return Err(CalcResult::Error {
error: Error::VALUE,
origin: cell,
message: format!("Unsupported array argument: {}", e),
})
}
},
CalcResult::Range { left, right } => self.values_from_range(left, right)?,
CalcResult::Boolean(value) => {
if !matches!(arg, Node::ReferenceKind { .. }) {
vec![Some(if value { 1.0 } else { 0.0 })]
} else {
return Err(CalcResult::Error {
error: Error::NUM,
origin: cell,
message: "Unsupported argument type".to_string(),
});
}
}
_ => {
return Err(CalcResult::Error {
error: Error::NIMPL,
origin: cell,
message: "Unsupported argument type".to_string(),
})
}
};
let numeric_values: Vec<f64> = values.into_iter().flatten().collect();
Ok(numeric_values)
}
// RANK.EQ(number, ref, [order])
pub(crate) fn fn_rank_eq(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
if !(2..=3).contains(&args.len()) {
return CalcResult::new_args_number_error(cell);
}
// number
let number = match self.get_number_no_bools(&args[0], cell) {
Ok(f) => f,
Err(e) => return e,
};
// ref
let mut values = match self.collect_rank_values(&args[1], cell) {
Ok(v) => v,
Err(e) => return e,
};
if values.is_empty() {
return CalcResult::Error {
error: Error::NUM,
origin: cell,
message: "No numeric values for RANK.EQ".to_string(),
};
}
// order: default 0 (descending)
let order = if args.len() == 2 {
0.0
} else {
match self.get_number_no_bools(&args[2], cell) {
Ok(f) => f,
Err(e) => return e,
}
};
values.retain(|v| !v.is_nan());
// "better" = greater (descending) or smaller (ascending)
let mut better = 0;
let mut equal = 0;
if order == 0.0 {
// descending
for v in &values {
if *v > number {
better += 1;
} else if *v == number {
equal += 1;
}
}
} else {
// ascending
for v in &values {
if *v < number {
better += 1;
} else if *v == number {
equal += 1;
}
}
}
if equal == 0 {
return CalcResult::Error {
error: Error::NA,
origin: cell,
message: "Number not found in reference for RANK.EQ".to_string(),
};
}
let rank = (better as f64) + 1.0;
CalcResult::Number(rank)
}
// RANK.AVG(number, ref, [order])
pub(crate) fn fn_rank_avg(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
if !(2..=3).contains(&args.len()) {
return CalcResult::new_args_number_error(cell);
}
// number
let number = match self.get_number_no_bools(&args[0], cell) {
Ok(f) => f,
Err(e) => return e,
};
// ref
let mut values = match self.collect_rank_values(&args[1], cell) {
Ok(v) => v,
Err(e) => return e,
};
if values.is_empty() {
return CalcResult::Error {
error: Error::NUM,
origin: cell,
message: "No numeric values for RANK.AVG".to_string(),
};
}
// order: default 0 (descending)
let order = if args.len() == 2 {
0.0
} else {
match self.get_number_no_bools(&args[2], cell) {
Ok(f) => f,
Err(e) => return e,
}
};
values.retain(|v| !v.is_nan());
// > or < depending on order
let mut better = 0;
let mut equal = 0;
if order == 0.0 {
// descending
for v in &values {
if *v > number {
better += 1;
} else if *v == number {
equal += 1;
}
}
} else {
// ascending
for v in &values {
if *v < number {
better += 1;
} else if *v == number {
equal += 1;
}
}
}
if equal == 0 {
return CalcResult::Error {
error: Error::NA,
origin: cell,
message: "Number not found in reference for RANK.AVG".to_string(),
};
}
// For ties, average of the ranks. If the equal values occupy positions
// (better+1) ..= (better+equal), the average is:
// better + (equal + 1) / 2
let better_f = better as f64;
let equal_f = equal as f64;
let rank = better_f + (equal_f + 1.0) / 2.0;
CalcResult::Number(rank)
}
}

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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())
}
}

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@@ -0,0 +1,38 @@
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)
}
}

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@@ -0,0 +1,588 @@
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)
}
pub(crate) 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)
}
}

View File

@@ -0,0 +1,518 @@
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)
}
}

View File

@@ -0,0 +1,71 @@
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)
}
}

View File

@@ -0,0 +1,171 @@
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)
}
}

View File

@@ -1,7 +1,10 @@
#[cfg(feature = "use_regex_lite")]
use regex_lite as regex;
use crate::{calc_result::CalcResult, expressions::token::is_english_error_string};
use crate::{
calc_result::CalcResult, expressions::token::is_english_error_string,
number_format::to_excel_precision,
};
/// This test for exact match (modulo case).
/// * strings are not cast into bools or numbers
@@ -34,6 +37,8 @@ pub(crate) fn values_are_equal(left: &CalcResult, right: &CalcResult) -> bool {
pub(crate) fn compare_values(left: &CalcResult, right: &CalcResult) -> i32 {
match (left, right) {
(CalcResult::Number(value1), CalcResult::Number(value2)) => {
let value1 = to_excel_precision(*value1, 15);
let value2 = to_excel_precision(*value2, 15);
if (value2 - value1).abs() < f64::EPSILON {
return 0;
}

View File

@@ -2068,21 +2068,7 @@ impl Model {
scope: Option<u32>,
formula: &str,
) -> Result<(), String> {
if !is_valid_identifier(name) {
return Err("Invalid defined name".to_string());
};
let name_upper = name.to_uppercase();
let defined_names = &self.workbook.defined_names;
let sheet_id = match scope {
Some(index) => Some(self.workbook.worksheet(index)?.sheet_id),
None => None,
};
// if the defined name already exist return error
for df in defined_names {
if df.name.to_uppercase() == name_upper && df.sheet_id == sheet_id {
return Err("Defined name already exists".to_string());
}
}
let sheet_id = self.is_valid_defined_name(name, scope, formula)?;
self.workbook.defined_names.push(DefinedName {
name: name.to_string(),
formula: formula.to_string(),
@@ -2093,6 +2079,48 @@ impl Model {
Ok(())
}
/// Validates if a defined name can be created
pub fn is_valid_defined_name(
&self,
name: &str,
scope: Option<u32>,
formula: &str,
) -> Result<Option<u32>, String> {
if !is_valid_identifier(name) {
return Err("Name: Invalid defined name".to_string());
}
let name_upper = name.to_uppercase();
let defined_names = &self.workbook.defined_names;
let sheet_id = match scope {
Some(index) => match self.workbook.worksheet(index) {
Ok(ws) => Some(ws.sheet_id),
Err(_) => return Err("Scope: Invalid sheet index".to_string()),
},
None => None,
};
// if the defined name already exist return error
for df in defined_names {
if df.name.to_uppercase() == name_upper && df.sheet_id == sheet_id {
return Err("Name: Defined name already exists".to_string());
}
}
// Make sure the formula is valid
match common::ParsedReference::parse_reference_formula(
None,
formula,
&self.locale,
|name| self.get_sheet_index_by_name(name),
) {
Ok(_) => {}
Err(_) => {
return Err("Formula: Invalid defined name formula".to_string());
}
};
Ok(sheet_id)
}
/// Delete defined name of name and scope
pub fn delete_defined_name(&mut self, name: &str, scope: Option<u32>) -> Result<(), String> {
let name_upper = name.to_uppercase();
@@ -2126,7 +2154,7 @@ impl Model {
new_formula: &str,
) -> Result<(), String> {
if !is_valid_identifier(new_name) {
return Err("Invalid defined name".to_string());
return Err("Name: Invalid defined name".to_string());
};
let name_upper = name.to_uppercase();
let new_name_upper = new_name.to_uppercase();
@@ -2134,18 +2162,28 @@ impl Model {
if name_upper != new_name_upper || scope != new_scope {
for key in self.parsed_defined_names.keys() {
if key.1.to_uppercase() == new_name_upper && key.0 == new_scope {
return Err("Defined name already exists".to_string());
return Err("Name: Defined name already exists".to_string());
}
}
}
let defined_names = &self.workbook.defined_names;
let sheet_id = match scope {
Some(index) => Some(self.workbook.worksheet(index)?.sheet_id),
Some(index) => Some(
self.workbook
.worksheet(index)
.map_err(|_| "Scope: Invalid sheet index")?
.sheet_id,
),
None => None,
};
let new_sheet_id = match new_scope {
Some(index) => Some(self.workbook.worksheet(index)?.sheet_id),
Some(index) => Some(
self.workbook
.worksheet(index)
.map_err(|_| "Scope: Invalid sheet index")?
.sheet_id,
),
None => None,
};

View File

@@ -112,29 +112,36 @@ pub fn to_precision(value: f64, precision: usize) -> f64 {
/// ```
/// This intends to be equivalent to the js: `${parseFloat(value.toPrecision(precision)})`
/// See ([ecma](https://tc39.es/ecma262/#sec-number.prototype.toprecision)).
/// FIXME: There has to be a better algorithm :/
pub fn to_excel_precision_str(value: f64) -> String {
to_precision_str(value, 15)
}
pub fn to_excel_precision(value: f64, precision: usize) -> f64 {
if !value.is_finite() {
return value;
}
let s = format!("{:.*e}", precision.saturating_sub(1), value);
s.parse::<f64>().unwrap_or(value)
}
pub fn to_precision_str(value: f64, precision: usize) -> String {
if value.is_infinite() {
return "inf".to_string();
if !value.is_finite() {
if value.is_infinite() {
return "inf".to_string();
} else {
return "NaN".to_string();
}
}
if value.is_nan() {
return "NaN".to_string();
}
let exponent = value.abs().log10().floor();
let base = value / 10.0_f64.powf(exponent);
let base = format!("{0:.1$}", base, precision - 1);
let value = format!("{base}e{exponent}").parse::<f64>().unwrap_or({
// TODO: do this in a way that does not require a possible error
0.0
});
let s = format!("{:.*e}", precision.saturating_sub(1), value);
let parsed = s.parse::<f64>().unwrap_or(value);
// I would love to use the std library. There is not a speed concern here
// problem is it doesn't do the right thing
// Also ryu is my favorite _modern_ algorithm
let mut buffer = ryu::Buffer::new();
let text = buffer.format(value);
let text = buffer.format(parsed);
// The above algorithm converts 2 to 2.0 regrettably
if let Some(stripped) = text.strip_suffix(".0") {
return stripped.to_string();

View File

@@ -133,6 +133,7 @@ fn fn_imcot() {
);
}
#[cfg_attr(target_os = "windows", ignore)]
#[test]
fn fn_imtan() {
let mut model = new_empty_model();

View File

@@ -11,19 +11,14 @@ mod test_datedif_leap_month_end;
mod test_days360_month_end;
mod test_degrees_radians;
mod test_error_propagation;
mod test_fn_accrint;
mod test_fn_accrintm;
mod test_fn_average;
mod test_fn_averageifs;
mod test_fn_choose;
mod test_fn_concatenate;
mod test_fn_count;
mod test_fn_coupon;
mod test_fn_day;
mod test_fn_duration;
mod test_fn_exact;
mod test_fn_financial;
mod test_fn_financial_bonds;
mod test_fn_formulatext;
mod test_fn_if;
mod test_fn_maxifs;
@@ -50,6 +45,7 @@ mod test_set_user_input;
mod test_sheet_markup;
mod test_sheets;
mod test_styles;
mod test_sumsq;
mod test_trigonometric;
mod test_true_false;
mod test_weekday_return_types;
@@ -60,15 +56,20 @@ 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_floor;
mod test_fn_datevalue_timevalue;
mod test_fn_fv;
mod test_fn_round;
mod test_fn_fvschedule;
mod test_fn_type;
mod test_frozen_rows_and_columns;
mod test_geomean;
@@ -79,10 +80,13 @@ mod test_issue_483;
mod test_ln;
mod test_log;
mod test_log10;
mod test_mod_quotient;
mod test_networkdays;
mod test_now;
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;

View File

@@ -0,0 +1,24 @@
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_f_test;
mod test_fn_fisher;
mod test_fn_gauss;
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;

View File

@@ -0,0 +1,40 @@
#![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");
}

View File

@@ -0,0 +1,86 @@
#![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!");
}

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#![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!");
}

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#![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");
}

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#![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!");
}

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#![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");
}

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#![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");
}

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#![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!");
}

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#![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!");
}

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#![allow(clippy::unwrap_used)]
use crate::test::util::new_empty_model;
#[test]
fn test_fn_f_test_sanity() {
let mut model = new_empty_model();
// Valid call
model._set("A1", "=F.TEST(A2:A7, B2:B7)");
model._set("A2", "9");
model._set("A3", "12");
model._set("A4", "14");
model._set("A5", "16");
model._set("A6", "18");
model._set("A7", "20");
model._set("B2", "11");
model._set("B3", "10");
model._set("B4", "15");
model._set("B5", "17");
model._set("B6", "19");
model._set("B7", "21");
// Too few args
model._set("A8", "=F.TEST(A2:A7)");
// Too many args
model._set("A9", "=F.TEST(A2:A7, B2:B7, C2:C7)");
model.evaluate();
assert_eq!(model._get_text("A1"), *"0.859284302");
assert_eq!(model._get_text("A8"), *"#ERROR!");
assert_eq!(model._get_text("A9"), *"#ERROR!");
}

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#![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!");
}

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#![allow(clippy::unwrap_used)]
use crate::test::util::new_empty_model;
#[test]
fn test_fn_gauss_smoke() {
let mut model = new_empty_model();
model._set("A1", "=GAUSS(-3)");
model._set("A2", "=GAUSS(-2.3)");
model._set("A3", "=GAUSS(-1.7)");
model._set("A4", "=GAUSS(0)");
model._set("A5", "=GAUSS(0.5)");
model._set("A6", "=GAUSS(1)");
model._set("A7", "=GAUSS(1.3)");
model._set("A8", "=GAUSS(3)");
model._set("A9", "=GAUSS(4)");
model._set("G6", "=GAUSS()");
model._set("G7", "=GAUSS(1, 1)");
model.evaluate();
assert_eq!(model._get_text("A1"), *"-0.498650102");
assert_eq!(model._get_text("A2"), *"-0.48927589");
assert_eq!(model._get_text("A3"), *"-0.455434537");
assert_eq!(model._get_text("A4"), *"0");
assert_eq!(model._get_text("A5"), *"0.191462461");
assert_eq!(model._get_text("A6"), *"0.341344746");
assert_eq!(model._get_text("A7"), *"0.403199515");
assert_eq!(model._get_text("A8"), *"0.498650102");
assert_eq!(model._get_text("A9"), *"0.499968329");
assert_eq!(model._get_text("G6"), *"#ERROR!");
assert_eq!(model._get_text("G7"), *"#ERROR!");
}

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#![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!");
}

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#![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!");
}

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#![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!");
}

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#![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");
}

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#![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!");
}

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#![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");
}

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#![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");
}

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#![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!");
}

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#![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");
}

View File

@@ -0,0 +1,46 @@
#![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");
}

View File

@@ -0,0 +1,41 @@
#![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!");
}

View File

@@ -0,0 +1,36 @@
#![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");
}

View File

@@ -0,0 +1,27 @@
#![allow(clippy::unwrap_used)]
use crate::test::util::new_empty_model;
#[test]
fn arguments() {
let mut model = new_empty_model();
model._set("A1", "=ARABIC()");
model._set("A2", "=ARABIC(V)");
model._set("A3", "=ARABIC(V, 2)");
model._set("A4", "=ROMAN()");
model._set("A5", "=ROMAN(5)");
model._set("A6", "=ROMAN(5, 0)");
model._set("A7", "=ROMAN(5, 0, 2)");
model.evaluate();
assert_eq!(model._get_text("A1"), *"#ERROR!");
assert_eq!(model._get_text("A2"), *"5");
assert_eq!(model._get_text("A3"), *"#ERROR!");
assert_eq!(model._get_text("A4"), *"#ERROR!");
assert_eq!(model._get_text("A5"), *"V");
assert_eq!(model._get_text("A6"), *"V");
assert_eq!(model._get_text("A7"), *"#ERROR!");
}

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@@ -0,0 +1,35 @@
#![allow(clippy::unwrap_used)]
use crate::test::util::new_empty_model;
#[test]
fn arguments() {
let mut model = new_empty_model();
model._set("A1", "=CELL("address",A1)");
model._set("A2", "=CELL()");
model._set("A3", "=INFO("system")");
model._set("A4", "=INFO()");
model._set("A5", "=N(TRUE)");
model._set("A6", "=N()");
model._set("A7", "=N(1, 2)");
model._set("A8", "=SHEETS()");
model._set("A9", "=SHEETS(1)");
model.evaluate();
assert_eq!(model._get_text("A1"), *"$A$1");
assert_eq!(model._get_text("A2"), *"#ERROR!");
assert_eq!(model._get_text("A3"), *"#N/IMPL!");
assert_eq!(model._get_text("A4"), *"#ERROR!");
assert_eq!(model._get_text("A5"), *"1");
assert_eq!(model._get_text("A6"), *"#ERROR!");
assert_eq!(model._get_text("A7"), *"#ERROR!");
assert_eq!(model._get_text("A8"), *"1");
assert_eq!(model._get_text("A9"), *"#N/IMPL!");
}

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@@ -0,0 +1,27 @@
#![allow(clippy::unwrap_used)]
use crate::test::util::new_empty_model;
#[test]
fn arguments() {
let mut model = new_empty_model();
model._set("A1", "=COMBIN(5,2)");
model._set("A2", "=COMBINA(5,2)");
model._set("A3", "=COMBIN()");
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.evaluate();
assert_eq!(model._get_text("A1"), *"10");
assert_eq!(model._get_text("A2"), *"15");
assert_eq!(model._get_text("A3"), *"#ERROR!");
assert_eq!(model._get_text("A4"), *"#ERROR!");
assert_eq!(model._get_text("A5"), *"#ERROR!");
assert_eq!(model._get_text("A6"), *"#ERROR!");
assert_eq!(model._get_text("A7"), *"#ERROR!");
assert_eq!(model._get_text("A8"), *"#ERROR!");
}

View File

@@ -542,7 +542,6 @@ fn test_yearfrac_function() {
// Edge cases
model._set("A4", "=YEARFRAC(44561,44561,1)"); // Same date = 0
model._set("A5", "=YEARFRAC(44926,44561,1)"); // Reverse = negative
model._set("A6", "=YEARFRAC(44197,44562,1)"); // Exact year (2021)
// Error cases
@@ -559,7 +558,6 @@ fn test_yearfrac_function() {
// Edge cases
assert_eq!(model._get_text("A4"), *"0"); // Same date
assert_eq!(model._get_text("A5"), *"-1"); // Negative
assert_eq!(model._get_text("A6"), *"1"); // Exact year
// Error cases

View File

@@ -0,0 +1,23 @@
#![allow(clippy::unwrap_used)]
use crate::test::util::new_empty_model;
#[test]
fn arguments() {
let mut model = new_empty_model();
model._set("A1", "=EVEN(2)");
model._set("A2", "=ODD(2)");
model._set("A3", "=EVEN()");
model._set("A4", "=ODD()");
model._set("A5", "=EVEN(1, 2)");
model._set("A6", "=ODD(1, 2)");
model.evaluate();
assert_eq!(model._get_text("A1"), *"2");
assert_eq!(model._get_text("A2"), *"3");
assert_eq!(model._get_text("A3"), *"#ERROR!");
assert_eq!(model._get_text("A4"), *"#ERROR!");
assert_eq!(model._get_text("A5"), *"#ERROR!");
assert_eq!(model._get_text("A6"), *"#ERROR!");
}

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@@ -0,0 +1,26 @@
#![allow(clippy::unwrap_used)]
use crate::test::util::new_empty_model;
#[test]
fn fn_arguments() {
let mut model = new_empty_model();
model._set("A1", "=EXP()");
model._set("A2", "=SIGN()");
model._set("A3", "=EXP(0)");
model._set("A4", "=SIGN(-10)");
model._set("A5", "=EXP(1, 2)");
model._set("A6", "=SIGN(1, 2)");
model.evaluate();
assert_eq!(model._get_text("A1"), *"#ERROR!");
assert_eq!(model._get_text("A2"), *"#ERROR!");
assert_eq!(model._get_text("A3"), *"1");
assert_eq!(model._get_text("A4"), *"-1");
assert_eq!(model._get_text("A5"), *"#ERROR!");
assert_eq!(model._get_text("A6"), *"#ERROR!");
}

123
base/src/test/test_floor.rs Normal file
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@@ -0,0 +1,123 @@
#![allow(clippy::unwrap_used)]
use crate::test::util::new_empty_model;
#[test]
fn test_floor_floating_point_precision() {
// This test specifically checks the floating-point precision bug fix
// Bug: FLOOR(7.1, 0.1) was returning 7.0 instead of 7.1
let mut model = new_empty_model();
// FLOOR tests
model._set("C5", "=FLOOR(7.1, 0.1)");
model._set("H7", "=FLOOR(-7.1, -0.1)");
// FLOOR.PRECISE tests
model._set("C53", "=FLOOR.PRECISE(7.1, 0.1)");
model._set("H53", "=FLOOR.PRECISE(7.1, -0.1)");
// FLOOR.MATH tests
model._set("C101", "=FLOOR.MATH(7.1, 0.1)");
model._set("H101", "=FLOOR.MATH(7.1, -0.1)");
model.evaluate();
// All should return 7.1
assert_eq!(model._get_text("C5"), *"7.1");
assert_eq!(model._get_text("H7"), *"-7.1");
assert_eq!(model._get_text("C53"), *"7.1");
assert_eq!(model._get_text("H53"), *"7.1");
assert_eq!(model._get_text("C101"), *"7.1");
assert_eq!(model._get_text("H101"), *"7.1");
}
#[test]
fn test_floor_additional_precision_cases() {
let mut model = new_empty_model();
model._set("A1", "=FLOOR(7.9, 0.1)");
model._set("A2", "=FLOOR(2.6, 0.5)");
model._set("A3", "=FLOOR(0.3, 0.1)"); // 0.1 + 0.2 type scenario
model.evaluate();
assert_eq!(model._get_text("A1"), *"7.9");
assert_eq!(model._get_text("A2"), *"2.5");
assert_eq!(model._get_text("A3"), *"0.3");
}
#[test]
fn test_floor_basic_cases() {
let mut model = new_empty_model();
model._set("A1", "=FLOOR(3.7, 2)");
model._set("A2", "=FLOOR(3.2, 1)");
model._set("A3", "=FLOOR(10, 3)");
model._set("A4", "=FLOOR(7, 2)");
model.evaluate();
assert_eq!(model._get_text("A1"), *"2");
assert_eq!(model._get_text("A2"), *"3");
assert_eq!(model._get_text("A3"), *"9");
assert_eq!(model._get_text("A4"), *"6");
}
#[test]
fn test_floor_negative_numbers() {
let mut model = new_empty_model();
// Both negative: rounds toward zero
model._set("A1", "=FLOOR(-2.5, -2)");
model._set("A2", "=FLOOR(-11, -3)");
// Negative number, positive significance: rounds away from zero
model._set("A3", "=FLOOR(-11, 3)");
model._set("A4", "=FLOOR(-2.5, 2)");
model.evaluate();
assert_eq!(model._get_text("A1"), *"-2");
assert_eq!(model._get_text("A2"), *"-9");
assert_eq!(model._get_text("A3"), *"-12");
assert_eq!(model._get_text("A4"), *"-4");
}
#[test]
fn test_floor_error_cases() {
let mut model = new_empty_model();
// Positive number with negative significance should error
model._set("A1", "=FLOOR(2.5, -2)");
model._set("A2", "=FLOOR(10, -3)");
// Division by zero
model._set("A3", "=FLOOR(5, 0)");
// Wrong number of arguments
model._set("A4", "=FLOOR(5)");
model._set("A5", "=FLOOR(5, 1, 1)");
model.evaluate();
assert_eq!(model._get_text("A1"), *"#NUM!");
assert_eq!(model._get_text("A2"), *"#NUM!");
assert_eq!(model._get_text("A3"), *"#DIV/0!");
assert_eq!(model._get_text("A4"), *"#ERROR!");
assert_eq!(model._get_text("A5"), *"#ERROR!");
}
#[test]
fn test_floor_edge_cases() {
let mut model = new_empty_model();
// Zero value
model._set("A1", "=FLOOR(0, 5)");
model._set("A2", "=FLOOR(0, 0)");
// Exact multiples
model._set("A3", "=FLOOR(10, 5)");
model._set("A4", "=FLOOR(9, 3)");
model.evaluate();
assert_eq!(model._get_text("A1"), *"0");
assert_eq!(model._get_text("A2"), *"0");
assert_eq!(model._get_text("A3"), *"10");
assert_eq!(model._get_text("A4"), *"9");
}

View File

@@ -1,134 +0,0 @@
#![allow(clippy::unwrap_used)]
use crate::{cell::CellValue, test::util::new_empty_model};
#[test]
fn fn_accrint() {
let mut model = new_empty_model();
model._set("A1", "=DATE(2020,1,1)");
model._set("A2", "=DATE(2020,1,1)");
model._set("A3", "=DATE(2020,1,31)");
model._set("A4", "10%");
model._set("A5", "$1,000");
model._set("A6", "2");
model._set("B1", "=ACCRINT(A1,A2,A3,A4,A5,A6)");
model._set("C1", "=ACCRINT(A1)");
model._set("C2", "=ACCRINT(A1,A2,A3,A4,A5,3)");
model.evaluate();
match model.get_cell_value_by_ref("Sheet1!B1") {
Ok(CellValue::Number(v)) => {
assert!((v - 8.333333333333334).abs() < 1e-9);
}
other => unreachable!("Expected number for B1, got {:?}", other),
}
assert_eq!(model._get_text("C1"), *"#ERROR!");
assert_eq!(model._get_text("C2"), *"#NUM!");
}
#[test]
fn fn_accrint_parameters() {
let mut model = new_empty_model();
model._set("A1", "=DATE(2020,1,1)");
model._set("A2", "=DATE(2020,1,1)");
model._set("A3", "=DATE(2020,7,1)");
model._set("A4", "8%");
model._set("A5", "1000");
model._set("B1", "=ACCRINT(A1,A2,A3,A4,A5,2,0,TRUE)");
model._set("B2", "=ACCRINT(A1,A2,A3,A4,A5,2,1,TRUE)");
model._set("B3", "=ACCRINT(A1,A2,A3,A4,A5,2,4,TRUE)");
model._set("B4", "=ACCRINT(A1,A2,A3,A4,A5,1)");
model._set("B5", "=ACCRINT(A1,A2,A3,A4,A5,4)");
model._set("B6", "=ACCRINT(A1,A2,A3,A4,A5,2)");
model._set("B7", "=ACCRINT(A1,A2,A3,A4,A5,2,0)");
model.evaluate();
match model.get_cell_value_by_ref("Sheet1!B1") {
Ok(CellValue::Number(v)) => {
assert!((v - 40.0).abs() < 1e-9);
}
other => unreachable!("Expected number for B1, got {:?}", other),
}
match (
model.get_cell_value_by_ref("Sheet1!B1"),
model.get_cell_value_by_ref("Sheet1!B6"),
) {
(Ok(CellValue::Number(v1)), Ok(CellValue::Number(v2))) => {
assert!((v1 - v2).abs() < 1e-12);
}
other => unreachable!("Expected matching numbers, got {:?}", other),
}
}
#[test]
fn fn_accrint_errors() {
let mut model = new_empty_model();
model._set("A1", "=DATE(2020,1,1)");
model._set("A2", "=DATE(2020,1,1)");
model._set("A3", "=DATE(2020,7,1)");
model._set("A4", "8%");
model._set("A5", "1000");
model._set("B1", "=ACCRINT()");
model._set("B2", "=ACCRINT(A1,A2,A3,A4,A5)");
model._set("B3", "=ACCRINT(A1,A2,A3,A4,A5,2,0,TRUE,1)");
model._set("C1", "=ACCRINT(A1,A2,A3,A4,A5,0)");
model._set("C2", "=ACCRINT(A1,A2,A3,A4,A5,3)");
model._set("C3", "=ACCRINT(A1,A2,A3,A4,A5,-1)");
model._set("D1", "=ACCRINT(A1,A2,A3,A4,A5,2,-1)");
model._set("D2", "=ACCRINT(A1,A2,A3,A4,A5,2,5)");
model._set("E1", "=ACCRINT(A3,A2,A1,A4,A5,2)");
model._set("E2", "=ACCRINT(A1,A3,A1,A4,A5,2)");
model._set("F1", "=ACCRINT(A1,A2,A3,A4,0,2)");
model._set("F2", "=ACCRINT(A1,A2,A3,A4,-1000,2)");
model._set("F3", "=ACCRINT(A1,A2,A3,-8%,A5,2)");
model.evaluate();
assert_eq!(model._get_text("B1"), *"#ERROR!");
assert_eq!(model._get_text("B2"), *"#ERROR!");
assert_eq!(model._get_text("B3"), *"#ERROR!");
assert_eq!(model._get_text("C1"), *"#NUM!");
assert_eq!(model._get_text("C2"), *"#NUM!");
assert_eq!(model._get_text("C3"), *"#NUM!");
assert_eq!(model._get_text("D1"), *"#NUM!");
assert_eq!(model._get_text("D2"), *"#NUM!");
assert_eq!(model._get_text("E1"), *"#NUM!");
assert_eq!(model._get_text("E2"), *"#NUM!");
assert_eq!(model._get_text("F2"), *"#NUM!");
assert_eq!(model._get_text("F3"), *"#NUM!");
match model.get_cell_value_by_ref("Sheet1!F1") {
Ok(CellValue::Number(v)) => {
assert!((v - 0.0).abs() < 1e-9);
}
other => unreachable!("Expected 0 for F1, got {:?}", other),
}
}
#[test]
fn fn_accrint_combined() {
let mut model = new_empty_model();
model._set("A1", "=DATE(2018,10,15)");
model._set("A2", "=DATE(2019,2,1)");
model._set("A3", "5%");
model._set("A4", "1000");
model._set("B1", "=ACCRINT(A1,A1,A2,A3,A4,2)");
model.evaluate();
match model.get_cell_value_by_ref("Sheet1!B1") {
Ok(CellValue::Number(v)) => {
assert!((v - 14.722222222222221).abs() < 1e-9);
}
other => unreachable!("Expected number for B1, got {:?}", other),
}
}

View File

@@ -1,122 +0,0 @@
#![allow(clippy::unwrap_used)]
use crate::{cell::CellValue, test::util::new_empty_model};
#[test]
fn fn_accrintm() {
let mut model = new_empty_model();
model._set("A1", "=DATE(2020,1,1)");
model._set("A2", "=DATE(2020,7,1)");
model._set("A3", "10%");
model._set("A4", "$1,000");
model._set("B1", "=ACCRINTM(A1,A2,A3,A4)");
model._set("C1", "=ACCRINTM(A1)");
model.evaluate();
match model.get_cell_value_by_ref("Sheet1!B1") {
Ok(CellValue::Number(v)) => {
assert!((v - 50.0).abs() < 1e-9);
}
other => unreachable!("Expected number for B1, got {:?}", other),
}
assert_eq!(model._get_text("C1"), *"#ERROR!");
}
#[test]
fn fn_accrintm_parameters() {
let mut model = new_empty_model();
model._set("A1", "=DATE(2020,1,1)");
model._set("A2", "=DATE(2020,7,1)");
model._set("A3", "8%");
model._set("A4", "1000");
model._set("B1", "=ACCRINTM(A1,A2,A3,A4,0)");
model._set("B2", "=ACCRINTM(A1,A2,A3,A4,1)");
model._set("B3", "=ACCRINTM(A1,A2,A3,A4,4)");
model._set("C1", "=ACCRINTM(A1,A2,A3,A4)");
model.evaluate();
match (
model.get_cell_value_by_ref("Sheet1!B1"),
model.get_cell_value_by_ref("Sheet1!B2"),
) {
(Ok(CellValue::Number(v1)), Ok(CellValue::Number(v2))) => {
assert!(v1 > 0.0 && v2 > 0.0);
}
other => unreachable!("Expected numbers for basis test, got {:?}", other),
}
match (
model.get_cell_value_by_ref("Sheet1!B1"),
model.get_cell_value_by_ref("Sheet1!C1"),
) {
(Ok(CellValue::Number(v1)), Ok(CellValue::Number(v2))) => {
assert!((v1 - v2).abs() < 1e-12);
}
other => unreachable!(
"Expected matching numbers for default test, got {:?}",
other
),
}
}
#[test]
fn fn_accrintm_errors() {
let mut model = new_empty_model();
model._set("A1", "=DATE(2020,1,1)");
model._set("A2", "=DATE(2020,7,1)");
model._set("A3", "8%");
model._set("A4", "1000");
model._set("B1", "=ACCRINTM()");
model._set("B2", "=ACCRINTM(A1,A2,A3)");
model._set("B3", "=ACCRINTM(A1,A2,A3,A4,0,1)");
model._set("C1", "=ACCRINTM(A1,A2,A3,A4,-1)");
model._set("C2", "=ACCRINTM(A1,A2,A3,A4,5)");
model._set("D1", "=ACCRINTM(A2,A1,A3,A4)");
model._set("E1", "=ACCRINTM(A1,A2,A3,0)");
model._set("E2", "=ACCRINTM(A1,A2,A3,-1000)");
model._set("E3", "=ACCRINTM(A1,A2,-8%,A4)");
model.evaluate();
assert_eq!(model._get_text("B1"), *"#ERROR!");
assert_eq!(model._get_text("B2"), *"#ERROR!");
assert_eq!(model._get_text("B3"), *"#ERROR!");
assert_eq!(model._get_text("C1"), *"#NUM!");
assert_eq!(model._get_text("C2"), *"#NUM!");
assert_eq!(model._get_text("D1"), *"#NUM!");
assert_eq!(model._get_text("E2"), *"#NUM!");
assert_eq!(model._get_text("E3"), *"#NUM!");
match model.get_cell_value_by_ref("Sheet1!E1") {
Ok(CellValue::Number(v)) => {
assert!((v - 0.0).abs() < 1e-9);
}
other => unreachable!("Expected 0 for E1, got {:?}", other),
}
}
#[test]
fn fn_accrintm_combined() {
let mut model = new_empty_model();
model._set("C1", "=DATE(2016,4,5)");
model._set("C2", "=DATE(2019,2,1)");
model._set("A3", "5%");
model._set("A4", "1000");
model._set("B2", "=ACCRINTM(C1,C2,A3,A4)");
model.evaluate();
match model.get_cell_value_by_ref("Sheet1!B2") {
Ok(CellValue::Number(v)) => {
assert!((v - 141.11111111111111).abs() < 1e-9);
}
other => unreachable!("Expected number for B2, got {:?}", other),
}
}

View File

@@ -1,260 +0,0 @@
#![allow(clippy::unwrap_used)]
use crate::{cell::CellValue, test::util::new_empty_model};
#[test]
fn fn_coupon_functions() {
let mut model = new_empty_model();
// Test with basis 1 (original test)
model._set("A1", "=DATE(2001,1,25)");
model._set("A2", "=DATE(2001,11,15)");
model._set("B1", "=COUPDAYBS(A1,A2,2,1)");
model._set("B2", "=COUPDAYS(A1,A2,2,1)");
model._set("B3", "=COUPDAYSNC(A1,A2,2,1)");
model._set("B4", "=COUPNCD(A1,A2,2,1)");
model._set("B5", "=COUPNUM(A1,A2,2,1)");
model._set("B6", "=COUPPCD(A1,A2,2,1)");
// Test with basis 3 for better coverage
model._set("C1", "=COUPDAYBS(DATE(2001,1,25),DATE(2001,11,15),2,3)");
model._set("C2", "=COUPDAYS(DATE(2001,1,25),DATE(2001,11,15),2,3)");
model._set("C3", "=COUPDAYSNC(DATE(2001,1,25),DATE(2001,11,15),2,3)");
model._set("C4", "=COUPNCD(DATE(2001,1,25),DATE(2001,11,15),2,3)");
model._set("C5", "=COUPNUM(DATE(2007,1,25),DATE(2008,11,15),2,1)");
model._set("C6", "=COUPPCD(DATE(2001,1,25),DATE(2001,11,15),2,3)");
model.evaluate();
// Test basis 1
assert_eq!(model._get_text("B1"), "71");
assert_eq!(model._get_text("B2"), "181");
assert_eq!(model._get_text("B3"), "110");
assert_eq!(
model.get_cell_value_by_ref("Sheet1!B4"),
Ok(CellValue::Number(37026.0))
);
assert_eq!(model._get_text("B5"), "2");
assert_eq!(
model.get_cell_value_by_ref("Sheet1!B6"),
Ok(CellValue::Number(36845.0))
);
// Test basis 3 (more comprehensive coverage)
assert_eq!(model._get_text("C1"), "71");
assert_eq!(model._get_text("C2"), "181"); // Fixed: actual days
assert_eq!(model._get_text("C3"), "110");
assert_eq!(model._get_text("C4"), "37026");
assert_eq!(model._get_text("C5"), "4");
assert_eq!(model._get_text("C6"), "36845");
}
#[test]
fn fn_coupon_functions_error_cases() {
let mut model = new_empty_model();
// Test invalid frequency
model._set("E1", "=COUPDAYBS(DATE(2001,1,25),DATE(2001,11,15),3,1)");
// Test invalid basis
model._set("E2", "=COUPDAYS(DATE(2001,1,25),DATE(2001,11,15),2,5)");
// Test settlement >= maturity
model._set("E3", "=COUPDAYSNC(DATE(2001,11,15),DATE(2001,1,25),2,1)");
// Test too few arguments
model._set("E4", "=COUPNCD(DATE(2001,1,25),DATE(2001,11,15))");
// Test too many arguments
model._set("E5", "=COUPNUM(DATE(2001,1,25),DATE(2001,11,15),2,1,1)");
model.evaluate();
// All should return errors
assert_eq!(model._get_text("E1"), "#NUM!");
assert_eq!(model._get_text("E2"), "#NUM!");
assert_eq!(model._get_text("E3"), "#NUM!");
assert_eq!(model._get_text("E4"), *"#ERROR!");
assert_eq!(model._get_text("E5"), *"#ERROR!");
}
#[test]
fn fn_coupdays_actual_day_count_fix() {
// Verify COUPDAYS correctly distinguishes between fixed vs actual day count methods
// Bug: basis 2&3 were incorrectly using fixed calculations like basis 0&4
let mut model = new_empty_model();
model._set("A1", "=DATE(2023,1,15)");
model._set("A2", "=DATE(2023,7,15)");
model._set("B1", "=COUPDAYS(A1,A2,2,0)"); // 30/360: uses 360/freq
model._set("B2", "=COUPDAYS(A1,A2,2,2)"); // Actual/360: uses actual days
model._set("B3", "=COUPDAYS(A1,A2,2,3)"); // Actual/365: uses actual days
model._set("B4", "=COUPDAYS(A1,A2,2,4)"); // 30/360 European: uses 360/freq
model.evaluate();
// Basis 0&4: theoretical 360/2 = 180 days
assert_eq!(model._get_text("B1"), "180");
assert_eq!(model._get_text("B4"), "180");
// Basis 2&3: actual days between Jan 15 and Jul 15 = 181 days
assert_eq!(model._get_text("B2"), "181");
assert_eq!(model._get_text("B3"), "181");
}
// =============================================================================
// FEBRUARY EDGE CASE TESTS - Day Count Convention Compliance
// =============================================================================
// These tests verify that financial functions correctly handle February dates
// according to the official 30/360 day count convention specifications.
#[test]
fn test_coupon_functions_february_consistency() {
let mut model = new_empty_model();
// Test that coupon functions behave consistently between US and European methods
// when February dates are involved
// Settlement: Last day of February (non-leap year)
// Maturity: Some date in following year that creates a clear test case
model._set("A1", "=DATE(2023,2,28)"); // Last day of Feb, non-leap year
model._set("A2", "=DATE(2024,2,28)"); // Same day next year
// Test COUPDAYS with different basis values
model._set("B1", "=COUPDAYS(A1,A2,2,0)"); // US 30/360 - should treat Feb 28 as day 30
model._set("B2", "=COUPDAYS(A1,A2,2,4)"); // European 30/360 - should treat Feb 28 as day 28
model._set("B3", "=COUPDAYS(A1,A2,2,1)"); // Actual/actual - should use real days
model.evaluate();
// All should return valid numbers (no errors)
assert_ne!(model._get_text("B1"), *"#NUM!");
assert_ne!(model._get_text("B2"), *"#NUM!");
assert_ne!(model._get_text("B3"), *"#NUM!");
// US and European 30/360 should potentially give different results for February dates
// (though the exact difference depends on the specific coupon calculation logic)
let us_result = model._get_text("B1");
let european_result = model._get_text("B2");
let actual_result = model._get_text("B3");
// Verify all are numeric
assert!(us_result.parse::<f64>().is_ok());
assert!(european_result.parse::<f64>().is_ok());
assert!(actual_result.parse::<f64>().is_ok());
}
#[test]
fn test_february_edge_cases_leap_vs_nonleap() {
let mut model = new_empty_model();
// Test leap year vs non-leap year February handling
// Feb 28 in non-leap year (this IS the last day of February)
model._set("A1", "=DATE(2023,2,28)");
model._set("A2", "=DATE(2023,8,28)");
// Feb 28 in leap year (this is NOT the last day of February)
model._set("A3", "=DATE(2024,2,28)");
model._set("A4", "=DATE(2024,8,28)");
// Feb 29 in leap year (this IS the last day of February)
model._set("A5", "=DATE(2024,2,29)");
model._set("A6", "=DATE(2024,8,29)");
// Test with basis 0 (US 30/360) - should have special February handling
model._set("B1", "=COUPDAYS(A1,A2,2,0)"); // Feb 28 non-leap (last day)
model._set("B2", "=COUPDAYS(A3,A4,2,0)"); // Feb 28 leap year (not last day)
model._set("B3", "=COUPDAYS(A5,A6,2,0)"); // Feb 29 leap year (last day)
model.evaluate();
// All should succeed
assert_ne!(model._get_text("B1"), *"#NUM!");
assert_ne!(model._get_text("B2"), *"#NUM!");
assert_ne!(model._get_text("B3"), *"#NUM!");
// Verify they're all numeric
assert!(model._get_text("B1").parse::<f64>().is_ok());
assert!(model._get_text("B2").parse::<f64>().is_ok());
assert!(model._get_text("B3").parse::<f64>().is_ok());
}
#[test]
fn test_us_nasd_both_february_rule() {
let mut model = new_empty_model();
// Test the specific US/NASD rule: "If both date A and B fall on the last day of February,
// then date B will be changed to the 30th"
// Case 1: Both dates are Feb 28 in non-leap years (both are last day of February)
model._set("A1", "=DATE(2023,2,28)"); // Last day of Feb 2023
model._set("A2", "=DATE(2025,2,28)"); // Last day of Feb 2025
// Case 2: Both dates are Feb 29 in leap years (both are last day of February)
model._set("A3", "=DATE(2024,2,29)"); // Last day of Feb 2024
model._set("A4", "=DATE(2028,2,29)"); // Last day of Feb 2028
// Case 3: Mixed - Feb 28 non-leap to Feb 29 leap (both are last day of February)
model._set("A5", "=DATE(2023,2,28)"); // Last day of Feb 2023
model._set("A6", "=DATE(2024,2,29)"); // Last day of Feb 2024
// Case 4: Control - Feb 28 in leap year (NOT last day) to Feb 29 (IS last day)
model._set("A7", "=DATE(2024,2,28)"); // NOT last day of Feb 2024
model._set("A8", "=DATE(2024,2,29)"); // IS last day of Feb 2024
// Test using coupon functions that should apply US/NASD 30/360 (basis 0)
model._set("B1", "=COUPDAYS(A1,A2,1,0)"); // Both last day Feb - Rule 1 should apply
model._set("B2", "=COUPDAYS(A3,A4,1,0)"); // Both last day Feb - Rule 1 should apply
model._set("B3", "=COUPDAYS(A5,A6,1,0)"); // Both last day Feb - Rule 1 should apply
model._set("B4", "=COUPDAYS(A7,A8,1,0)"); // Only end is last day Feb - Rule 1 should NOT apply
// Compare with European method (basis 4) - should behave differently
model._set("C1", "=COUPDAYS(A1,A2,1,4)"); // European - no special Feb handling
model._set("C2", "=COUPDAYS(A3,A4,1,4)"); // European - no special Feb handling
model._set("C3", "=COUPDAYS(A5,A6,1,4)"); // European - no special Feb handling
model._set("C4", "=COUPDAYS(A7,A8,1,4)"); // European - no special Feb handling
model.evaluate();
// All should succeed without errors
for row in ["B1", "B2", "B3", "B4", "C1", "C2", "C3", "C4"] {
assert_ne!(model._get_text(row), *"#NUM!", "Failed for {row}");
assert!(
model._get_text(row).parse::<f64>().is_ok(),
"Non-numeric result for {row}"
);
}
}
#[test]
fn test_coupon_functions_february_edge_cases() {
let mut model = new_empty_model();
// Test that coupon functions handle February dates correctly without errors
// Settlement: February 28, 2023 (non-leap), Maturity: February 28, 2024 (leap)
model._set("A1", "=DATE(2023,2,28)");
model._set("A2", "=DATE(2024,2,28)");
// Test with basis 0 (US 30/360 - should use special February handling)
model._set("B1", "=COUPDAYBS(A1,A2,2,0)");
model._set("B2", "=COUPDAYS(A1,A2,2,0)");
model._set("B3", "=COUPDAYSNC(A1,A2,2,0)");
// Test with basis 4 (European 30/360 - should NOT use special February handling)
model._set("C1", "=COUPDAYBS(A1,A2,2,4)");
model._set("C2", "=COUPDAYS(A1,A2,2,4)");
model._set("C3", "=COUPDAYSNC(A1,A2,2,4)");
model.evaluate();
// With US method (basis 0), February dates should be handled specially
// With European method (basis 4), February dates should use actual dates
// Key point: both should work without errors
// We're ensuring functions complete successfully with February dates
assert_ne!(model._get_text("B1"), *"#NUM!");
assert_ne!(model._get_text("B2"), *"#NUM!");
assert_ne!(model._get_text("B3"), *"#NUM!");
assert_ne!(model._get_text("C1"), *"#NUM!");
assert_ne!(model._get_text("C2"), *"#NUM!");
assert_ne!(model._get_text("C3"), *"#NUM!");
}

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@@ -0,0 +1,22 @@
#![allow(clippy::unwrap_used)]
use crate::test::util::new_empty_model;
#[test]
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("A5", "=DATEVALUE(1,2)");
model._set("A6", "=TIMEVALUE(1,2)");
model.evaluate();
assert_eq!(model._get_text("A1"), *"#ERROR!");
assert_eq!(model._get_text("A2"), *"#ERROR!");
assert_eq!(model._get_text("A3"), *"36526");
assert_eq!(model._get_text("A4"), *"0.5");
assert_eq!(model._get_text("A5"), *"#ERROR!");
assert_eq!(model._get_text("A6"), *"#ERROR!");
}

View File

@@ -1,350 +0,0 @@
#![allow(clippy::unwrap_used)]
#![allow(clippy::panic)]
use crate::{cell::CellValue, test::util::new_empty_model};
// Test constants for realistic bond scenarios
const BOND_SETTLEMENT: &str = "=DATE(2020,1,1)";
const BOND_MATURITY_4Y: &str = "=DATE(2024,1,1)";
const BOND_MATURITY_INVALID: &str = "=DATE(2016,1,1)"; // Before settlement
const BOND_MATURITY_SAME: &str = "=DATE(2020,1,1)"; // Same as settlement
const BOND_MATURITY_1DAY: &str = "=DATE(2020,1,2)"; // Very short term
// Standard investment-grade corporate bond parameters
const STD_COUPON: f64 = 0.08; // 8% annual coupon rate
const STD_YIELD: f64 = 0.09; // 9% yield (discount bond scenario)
const STD_FREQUENCY: i32 = 2; // Semi-annual payments (most common)
// Helper function to reduce test repetition
fn assert_numerical_result(model: &crate::Model, cell_ref: &str, should_be_positive: bool) {
if let Ok(CellValue::Number(v)) = model.get_cell_value_by_ref(cell_ref) {
if should_be_positive {
assert!(v > 0.0, "Expected positive value at {cell_ref}, got {v}");
}
// Value is valid - test passes
} else {
panic!("Expected numerical result at {cell_ref}");
}
}
#[test]
fn fn_duration_mduration_arguments() {
let mut model = new_empty_model();
// Test argument count validation
model._set("A1", "=DURATION()");
model._set("A2", "=DURATION(1,2,3,4)");
model._set("A3", "=DURATION(1,2,3,4,5,6,7)");
model._set("B1", "=MDURATION()");
model._set("B2", "=MDURATION(1,2,3,4)");
model._set("B3", "=MDURATION(1,2,3,4,5,6,7)");
model.evaluate();
// Too few or too many arguments should result in errors
assert_eq!(model._get_text("A1"), *"#ERROR!");
assert_eq!(model._get_text("A2"), *"#ERROR!");
assert_eq!(model._get_text("A3"), *"#ERROR!");
assert_eq!(model._get_text("B1"), *"#ERROR!");
assert_eq!(model._get_text("B2"), *"#ERROR!");
assert_eq!(model._get_text("B3"), *"#ERROR!");
}
#[test]
fn fn_duration_mduration_settlement_maturity_errors() {
let mut model = new_empty_model();
model._set("A1", BOND_SETTLEMENT);
model._set("A2", BOND_MATURITY_INVALID); // Before settlement
model._set("A3", BOND_MATURITY_SAME); // Same as settlement
// Both settlement > maturity and settlement = maturity should error
model._set(
"B1",
&format!("=DURATION(A1,A2,{STD_COUPON},{STD_YIELD},{STD_FREQUENCY})"),
);
model._set(
"B2",
&format!("=DURATION(A1,A3,{STD_COUPON},{STD_YIELD},{STD_FREQUENCY})"),
);
model._set(
"B3",
&format!("=MDURATION(A1,A2,{STD_COUPON},{STD_YIELD},{STD_FREQUENCY})"),
);
model._set(
"B4",
&format!("=MDURATION(A1,A3,{STD_COUPON},{STD_YIELD},{STD_FREQUENCY})"),
);
model.evaluate();
assert_eq!(model._get_text("B1"), *"#NUM!");
assert_eq!(model._get_text("B2"), *"#NUM!");
assert_eq!(model._get_text("B3"), *"#NUM!");
assert_eq!(model._get_text("B4"), *"#NUM!");
}
#[test]
fn fn_duration_mduration_negative_values_errors() {
let mut model = new_empty_model();
model._set("A1", BOND_SETTLEMENT);
model._set("A2", BOND_MATURITY_4Y);
// Test negative coupon (coupons must be >= 0)
model._set(
"B1",
&format!("=DURATION(A1,A2,-0.01,{STD_YIELD},{STD_FREQUENCY})"),
);
model._set(
"B2",
&format!("=MDURATION(A1,A2,-0.01,{STD_YIELD},{STD_FREQUENCY})"),
);
// Test negative yield (yields must be >= 0)
model._set(
"C1",
&format!("=DURATION(A1,A2,{STD_COUPON},-0.01,{STD_FREQUENCY})"),
);
model._set(
"C2",
&format!("=MDURATION(A1,A2,{STD_COUPON},-0.01,{STD_FREQUENCY})"),
);
model.evaluate();
assert_eq!(model._get_text("B1"), *"#NUM!");
assert_eq!(model._get_text("B2"), *"#NUM!");
assert_eq!(model._get_text("C1"), *"#NUM!");
assert_eq!(model._get_text("C2"), *"#NUM!");
}
#[test]
fn fn_duration_mduration_invalid_frequency_errors() {
let mut model = new_empty_model();
model._set("A1", BOND_SETTLEMENT);
model._set("A2", BOND_MATURITY_4Y);
// Only 1, 2, and 4 are valid frequencies (annual, semi-annual, quarterly)
let invalid_frequencies = [0, 3, 5, 12]; // Common invalid values
for (i, &freq) in invalid_frequencies.iter().enumerate() {
let row = i + 1;
model._set(
&format!("B{row}"),
&format!("=DURATION(A1,A2,{STD_COUPON},{STD_YIELD},{freq})"),
);
model._set(
&format!("C{row}"),
&format!("=MDURATION(A1,A2,{STD_COUPON},{STD_YIELD},{freq})"),
);
}
model.evaluate();
for i in 1..=invalid_frequencies.len() {
assert_eq!(model._get_text(&format!("B{i}")), *"#NUM!");
assert_eq!(model._get_text(&format!("C{i}")), *"#NUM!");
}
}
#[test]
fn fn_duration_mduration_frequency_variations() {
let mut model = new_empty_model();
model._set("A1", BOND_SETTLEMENT);
model._set("A2", BOND_MATURITY_4Y);
// Test all valid frequencies: 1=annual, 2=semi-annual, 4=quarterly
let valid_frequencies = [1, 2, 4];
for (i, &freq) in valid_frequencies.iter().enumerate() {
let row = i + 1;
model._set(
&format!("B{row}"),
&format!("=DURATION(A1,A2,{STD_COUPON},{STD_YIELD},{freq})"),
);
model._set(
&format!("C{row}"),
&format!("=MDURATION(A1,A2,{STD_COUPON},{STD_YIELD},{freq})"),
);
}
model.evaluate();
// All should return positive numerical values
for i in 1..=valid_frequencies.len() {
assert_numerical_result(&model, &format!("Sheet1!B{i}"), true);
assert_numerical_result(&model, &format!("Sheet1!C{i}"), true);
}
}
#[test]
fn fn_duration_mduration_basis_variations() {
let mut model = new_empty_model();
model._set("A1", BOND_SETTLEMENT);
model._set("A2", BOND_MATURITY_4Y);
// Test all valid basis values (day count conventions)
// 0=30/360 US, 1=Actual/actual, 2=Actual/360, 3=Actual/365, 4=30/360 European
for basis in 0..=4 {
let row = basis + 1;
model._set(
&format!("B{row}"),
&format!("=DURATION(A1,A2,{STD_COUPON},{STD_YIELD},{STD_FREQUENCY},{basis})"),
);
model._set(
&format!("C{row}"),
&format!("=MDURATION(A1,A2,{STD_COUPON},{STD_YIELD},{STD_FREQUENCY},{basis})"),
);
}
// Test default basis (should be 0)
model._set(
"D1",
&format!("=DURATION(A1,A2,{STD_COUPON},{STD_YIELD},{STD_FREQUENCY})"),
);
model._set(
"D2",
&format!("=MDURATION(A1,A2,{STD_COUPON},{STD_YIELD},{STD_FREQUENCY})"),
);
model.evaluate();
// All basis values should work
for row in 1..=5 {
assert_numerical_result(&model, &format!("Sheet1!B{row}"), true);
assert_numerical_result(&model, &format!("Sheet1!C{row}"), true);
}
// Default basis should match basis 0
if let (Ok(CellValue::Number(d1)), Ok(CellValue::Number(b1))) = (
model.get_cell_value_by_ref("Sheet1!D1"),
model.get_cell_value_by_ref("Sheet1!B1"),
) {
assert!(
(d1 - b1).abs() < 1e-10,
"Default basis should match basis 0"
);
}
}
#[test]
fn fn_duration_mduration_edge_cases() {
let mut model = new_empty_model();
model._set("A1", BOND_SETTLEMENT);
model._set("A2", BOND_MATURITY_1DAY); // Very short term (1 day)
model._set("A3", BOND_MATURITY_4Y); // Standard term
// Edge case scenarios with explanations
let test_cases = [
("B", "A1", "A2", STD_COUPON, STD_YIELD, "short_term"), // 1-day bond
("C", "A1", "A3", 0.0, STD_YIELD, "zero_coupon"), // Zero coupon bond
("D", "A1", "A3", STD_COUPON, 0.0, "zero_yield"), // Zero yield
("E", "A1", "A3", 1.0, 0.5, "high_rates"), // High coupon/yield (100%/50%)
];
for (col, settlement, maturity, coupon, yield_rate, _scenario) in test_cases {
model._set(
&format!("{col}1"),
&format!("=DURATION({settlement},{maturity},{coupon},{yield_rate},{STD_FREQUENCY})"),
);
model._set(
&format!("{col}2"),
&format!("=MDURATION({settlement},{maturity},{coupon},{yield_rate},{STD_FREQUENCY})"),
);
}
model.evaluate();
// All edge cases should return positive values
for col in ["B", "C", "D", "E"] {
assert_numerical_result(&model, &format!("Sheet1!{col}1"), true);
assert_numerical_result(&model, &format!("Sheet1!{col}2"), true);
}
}
#[test]
fn fn_duration_mduration_relationship() {
let mut model = new_empty_model();
model._set("A1", BOND_SETTLEMENT);
model._set("A2", BOND_MATURITY_4Y);
// Test mathematical relationship: MDURATION = DURATION / (1 + yield/frequency)
model._set(
"B1",
&format!("=DURATION(A1,A2,{STD_COUPON},{STD_YIELD},{STD_FREQUENCY})"),
);
model._set(
"B2",
&format!("=MDURATION(A1,A2,{STD_COUPON},{STD_YIELD},{STD_FREQUENCY})"),
);
model._set("B3", &format!("=B1/(1+{STD_YIELD}/{STD_FREQUENCY})")); // Manual calculation
// Test with quarterly frequency and different yield
model._set("C1", &format!("=DURATION(A1,A2,{STD_COUPON},0.12,4)"));
model._set("C2", &format!("=MDURATION(A1,A2,{STD_COUPON},0.12,4)"));
model._set("C3", "=C1/(1+0.12/4)"); // Manual calculation for quarterly
model.evaluate();
// MDURATION should equal DURATION / (1 + yield/frequency) for both scenarios
if let (Ok(CellValue::Number(md)), Ok(CellValue::Number(manual))) = (
model.get_cell_value_by_ref("Sheet1!B2"),
model.get_cell_value_by_ref("Sheet1!B3"),
) {
assert!(
(md - manual).abs() < 1e-10,
"MDURATION should equal DURATION/(1+yield/freq)"
);
}
if let (Ok(CellValue::Number(md)), Ok(CellValue::Number(manual))) = (
model.get_cell_value_by_ref("Sheet1!C2"),
model.get_cell_value_by_ref("Sheet1!C3"),
) {
assert!(
(md - manual).abs() < 1e-10,
"MDURATION should equal DURATION/(1+yield/freq) for quarterly"
);
}
}
#[test]
fn fn_duration_mduration_regression() {
// Original regression test with known expected values
let mut model = new_empty_model();
model._set("A1", "=DATE(2016,1,1)");
model._set("A2", "=DATE(2020,1,1)");
model._set(
"B1",
&format!("=DURATION(A1,A2,{STD_COUPON},{STD_YIELD},{STD_FREQUENCY})"),
);
model._set(
"B2",
&format!("=MDURATION(A1,A2,{STD_COUPON},{STD_YIELD},{STD_FREQUENCY})"),
);
model.evaluate();
// Verify exact values for regression testing
if let Ok(CellValue::Number(v1)) = model.get_cell_value_by_ref("Sheet1!B1") {
assert!(
(v1 - 3.410746844012284).abs() < 1e-9,
"DURATION regression test failed"
);
} else {
panic!("Unexpected value for DURATION");
}
if let Ok(CellValue::Number(v2)) = model.get_cell_value_by_ref("Sheet1!B2") {
assert!(
(v2 - 3.263872578002186).abs() < 1e-9,
"MDURATION regression test failed"
);
} else {
panic!("Unexpected value for MDURATION");
}
}

View File

@@ -1,5 +1,4 @@
#![allow(clippy::unwrap_used)]
#![allow(clippy::panic)]
use crate::{cell::CellValue, test::util::new_empty_model};
@@ -26,10 +25,6 @@ fn fn_arguments() {
model._set("E2", "=RATE(1,1)");
model._set("E3", "=RATE(1,1,1,1,1,1)");
model._set("F1", "=FVSCHEDULE()");
model._set("F2", "=FVSCHEDULE(1)");
model._set("F3", "=FVSCHEDULE(1,1,1)");
model.evaluate();
assert_eq!(model._get_text("A1"), *"#ERROR!");
@@ -51,10 +46,6 @@ fn fn_arguments() {
assert_eq!(model._get_text("E1"), *"#ERROR!");
assert_eq!(model._get_text("E2"), *"#ERROR!");
assert_eq!(model._get_text("E3"), *"#ERROR!");
assert_eq!(model._get_text("F1"), *"#ERROR!");
assert_eq!(model._get_text("F2"), *"#ERROR!");
assert_eq!(model._get_text("F3"), *"#ERROR!");
}
#[test]
@@ -477,18 +468,3 @@ fn fn_db_misc() {
assert_eq!(model._get_text("B1"), "$0.00");
}
#[test]
fn fn_fvschedule() {
let mut model = new_empty_model();
model._set("A1", "1000");
model._set("A2", "0.08");
model._set("A3", "0.09");
model._set("A4", "0.1");
model._set("B1", "=FVSCHEDULE(A1, A2:A4)");
model.evaluate();
assert_eq!(model._get_text("B1"), "1294.92");
}

View File

@@ -1,615 +0,0 @@
#![allow(clippy::unwrap_used)]
use crate::{cell::CellValue, test::util::new_empty_model};
#[test]
fn fn_price_yield() {
let mut model = new_empty_model();
model._set("A1", "=DATE(2023,1,1)");
model._set("A2", "=DATE(2024,1,1)");
model._set("A3", "5%");
model._set("B1", "=PRICE(A1,A2,A3,6%,100,1)");
model._set("B2", "=YIELD(A1,A2,A3,B1,100,1)");
model.evaluate();
assert_eq!(model._get_text("B1"), "99.056603774");
assert_eq!(model._get_text("B2"), "0.06");
}
#[test]
fn fn_price_frequencies() {
let mut model = new_empty_model();
model._set("A1", "=DATE(2023,1,1)");
model._set("A2", "=DATE(2024,1,1)");
model._set("B1", "=PRICE(A1,A2,5%,6%,100,1)");
model._set("B2", "=PRICE(A1,A2,5%,6%,100,2)");
model._set("B3", "=PRICE(A1,A2,5%,6%,100,4)");
model.evaluate();
let annual: f64 = model._get_text("B1").parse().unwrap();
let semi: f64 = model._get_text("B2").parse().unwrap();
let quarterly: f64 = model._get_text("B3").parse().unwrap();
assert_ne!(annual, semi);
assert_ne!(semi, quarterly);
}
#[test]
fn fn_yield_frequencies() {
let mut model = new_empty_model();
model._set("A1", "=DATE(2023,1,1)");
model._set("A2", "=DATE(2024,1,1)");
model._set("B1", "=YIELD(A1,A2,5%,99,100,1)");
model._set("B2", "=YIELD(A1,A2,5%,99,100,2)");
model._set("B3", "=YIELD(A1,A2,5%,99,100,4)");
model.evaluate();
let annual: f64 = model._get_text("B1").parse().unwrap();
let semi: f64 = model._get_text("B2").parse().unwrap();
let quarterly: f64 = model._get_text("B3").parse().unwrap();
assert_ne!(annual, semi);
assert_ne!(semi, quarterly);
}
#[test]
fn fn_price_argument_errors() {
let mut model = new_empty_model();
model._set("A1", "=DATE(2023,1,1)");
model._set("A2", "=DATE(2024,1,1)");
model._set("B1", "=PRICE()");
model._set("B2", "=PRICE(A1,A2,5%,6%,100)");
model._set("B3", "=PRICE(A1,A2,5%,6%,100,2,0,99)");
model.evaluate();
assert_eq!(model._get_text("B1"), *"#ERROR!");
assert_eq!(model._get_text("B2"), *"#ERROR!");
assert_eq!(model._get_text("B3"), *"#ERROR!");
}
#[test]
fn fn_yield_argument_errors() {
let mut model = new_empty_model();
model._set("A1", "=DATE(2023,1,1)");
model._set("A2", "=DATE(2024,1,1)");
model._set("B1", "=YIELD()");
model._set("B2", "=YIELD(A1,A2,5%,99,100)");
model._set("B3", "=YIELD(A1,A2,5%,99,100,2,0,99)");
model.evaluate();
assert_eq!(model._get_text("B1"), *"#ERROR!");
assert_eq!(model._get_text("B2"), *"#ERROR!");
assert_eq!(model._get_text("B3"), *"#ERROR!");
}
#[test]
fn fn_price_invalid_frequency() {
let mut model = new_empty_model();
model._set("A1", "=DATE(2023,1,1)");
model._set("A2", "=DATE(2024,1,1)");
model._set("B1", "=PRICE(A1,A2,5%,6%,100,0)");
model._set("B2", "=PRICE(A1,A2,5%,6%,100,3)");
model._set("B3", "=PRICE(A1,A2,5%,6%,100,5)");
model.evaluate();
assert_eq!(model._get_text("B1"), *"#NUM!");
assert_eq!(model._get_text("B2"), *"#NUM!");
assert_eq!(model._get_text("B3"), *"#NUM!");
}
#[test]
fn fn_pricedisc() {
let mut model = new_empty_model();
model._set("A2", "=DATE(2022,1,25)");
model._set("A3", "=DATE(2022,11,15)");
model._set("A4", "3.75%");
model._set("A5", "100");
model._set("B1", "=PRICEDISC(A2,A3,A4,A5)");
model._set("C1", "=PRICEDISC(A2,A3)");
model.evaluate();
assert_eq!(model._get_text("B1"), "96.979166667");
assert_eq!(model._get_text("C1"), *"#ERROR!");
}
#[test]
fn fn_pricemat() {
let mut model = new_empty_model();
model._set("A1", "=DATE(2019,2,15)");
model._set("A2", "=DATE(2025,4,13)");
model._set("A3", "=DATE(2018,11,11)");
model._set("A4", "5.75%");
model._set("A5", "6.5%");
model._set("B1", "=PRICEMAT(A1,A2,A3,A4,A5)");
model.evaluate();
assert_eq!(model._get_text("B1"), "96.271187821");
}
#[test]
fn fn_yielddisc() {
let mut model = new_empty_model();
model._set("A1", "=DATE(2022,1,25)");
model._set("A2", "=DATE(2022,11,15)");
model._set("A3", "97");
model._set("A4", "100");
model._set("B1", "=YIELDDISC(A1,A2,A3,A4)");
model.evaluate();
assert_eq!(model._get_text("B1"), "0.038393175");
}
#[test]
fn fn_yieldmat() {
let mut model = new_empty_model();
model._set("A1", "=DATE(2019,2,15)");
model._set("A2", "=DATE(2025,4,13)");
model._set("A3", "=DATE(2018,11,11)");
model._set("A4", "5.75%");
model._set("A5", "96.27");
model._set("B1", "=YIELDMAT(A1,A2,A3,A4,A5)");
model.evaluate();
assert_eq!(model._get_text("B1"), "0.065002762");
}
#[test]
fn fn_disc() {
let mut model = new_empty_model();
model._set("A1", "=DATE(2022,1,25)");
model._set("A2", "=DATE(2022,11,15)");
model._set("A3", "97");
model._set("A4", "100");
model._set("B1", "=DISC(A1,A2,A3,A4)");
model.evaluate();
assert_eq!(model._get_text("B1"), "0.037241379");
}
#[test]
fn fn_received() {
let mut model = new_empty_model();
model._set("A1", "=DATE(2020,1,1)");
model._set("A2", "=DATE(2023,6,30)");
model._set("A3", "20000");
model._set("A4", "5%");
model._set("A5", "3");
model._set("B1", "=RECEIVED(A1,A2,A3,A4,A5)");
model.evaluate();
assert_eq!(model._get_text("B1"), "24236.387782205");
}
#[test]
fn fn_intrate() {
let mut model = new_empty_model();
model._set("A1", "=DATE(2020,1,1)");
model._set("A2", "=DATE(2023,6,30)");
model._set("A3", "10000");
model._set("A4", "12000");
model._set("A5", "3");
model._set("B1", "=INTRATE(A1,A2,A3,A4,A5)");
model.evaluate();
assert_eq!(model._get_text("B1"), "0.057210031");
}
#[test]
fn fn_bond_functions_arguments() {
let mut model = new_empty_model();
// PRICEDISC: 4-5 args
model._set("A1", "=PRICEDISC()");
model._set("A2", "=PRICEDISC(1,2,3)");
model._set("A3", "=PRICEDISC(1,2,3,4,5,6)");
// PRICEMAT: 5-6 args
model._set("B1", "=PRICEMAT()");
model._set("B2", "=PRICEMAT(1,2,3,4)");
model._set("B3", "=PRICEMAT(1,2,3,4,5,6,7)");
// YIELDDISC: 4-5 args
model._set("C1", "=YIELDDISC()");
model._set("C2", "=YIELDDISC(1,2,3)");
model._set("C3", "=YIELDDISC(1,2,3,4,5,6)");
// YIELDMAT: 5-6 args
model._set("D1", "=YIELDMAT()");
model._set("D2", "=YIELDMAT(1,2,3,4)");
model._set("D3", "=YIELDMAT(1,2,3,4,5,6,7)");
// DISC: 4-5 args
model._set("E1", "=DISC()");
model._set("E2", "=DISC(1,2,3)");
model._set("E3", "=DISC(1,2,3,4,5,6)");
// RECEIVED: 4-5 args
model._set("F1", "=RECEIVED()");
model._set("F2", "=RECEIVED(1,2,3)");
model._set("F3", "=RECEIVED(1,2,3,4,5,6)");
// INTRATE: 4-5 args
model._set("G1", "=INTRATE()");
model._set("G2", "=INTRATE(1,2,3)");
model._set("G3", "=INTRATE(1,2,3,4,5,6)");
model.evaluate();
assert_eq!(model._get_text("A1"), *"#ERROR!");
assert_eq!(model._get_text("A2"), *"#ERROR!");
assert_eq!(model._get_text("A3"), *"#ERROR!");
assert_eq!(model._get_text("B1"), *"#ERROR!");
assert_eq!(model._get_text("B2"), *"#ERROR!");
assert_eq!(model._get_text("B3"), *"#ERROR!");
assert_eq!(model._get_text("C1"), *"#ERROR!");
assert_eq!(model._get_text("C2"), *"#ERROR!");
assert_eq!(model._get_text("C3"), *"#ERROR!");
assert_eq!(model._get_text("D1"), *"#ERROR!");
assert_eq!(model._get_text("D2"), *"#ERROR!");
assert_eq!(model._get_text("D3"), *"#ERROR!");
assert_eq!(model._get_text("E1"), *"#ERROR!");
assert_eq!(model._get_text("E2"), *"#ERROR!");
assert_eq!(model._get_text("E3"), *"#ERROR!");
assert_eq!(model._get_text("F1"), *"#ERROR!");
assert_eq!(model._get_text("F2"), *"#ERROR!");
assert_eq!(model._get_text("F3"), *"#ERROR!");
assert_eq!(model._get_text("G1"), *"#ERROR!");
assert_eq!(model._get_text("G2"), *"#ERROR!");
assert_eq!(model._get_text("G3"), *"#ERROR!");
}
#[test]
fn fn_bond_functions_date_boundaries() {
let mut model = new_empty_model();
// Date boundary values
model._set("A1", "0"); // Below MINIMUM_DATE_SERIAL_NUMBER
model._set("A2", "1"); // MINIMUM_DATE_SERIAL_NUMBER
model._set("A3", "2958465"); // MAXIMUM_DATE_SERIAL_NUMBER
model._set("A4", "2958466"); // Above MAXIMUM_DATE_SERIAL_NUMBER
// Test settlement < minimum
model._set("B1", "=PRICEDISC(A1,A2,0.05,100)");
model._set("B2", "=YIELDDISC(A1,A2,95,100)");
model._set("B3", "=DISC(A1,A2,95,100)");
model._set("B4", "=RECEIVED(A1,A2,1000,0.05)");
model._set("B5", "=INTRATE(A1,A2,1000,1050)");
// Test maturity > maximum
model._set("C1", "=PRICEDISC(A2,A4,0.05,100)");
model._set("C2", "=YIELDDISC(A2,A4,95,100)");
model._set("C3", "=DISC(A2,A4,95,100)");
model._set("C4", "=RECEIVED(A2,A4,1000,0.05)");
model._set("C5", "=INTRATE(A2,A4,1000,1050)");
// Test PRICEMAT/YIELDMAT with issue < minimum
model._set("D1", "=PRICEMAT(A2,A3,A1,0.06,0.05)");
model._set("D2", "=YIELDMAT(A2,A3,A1,0.06,99)");
// Test PRICEMAT/YIELDMAT with issue > maximum
model._set("E1", "=PRICEMAT(A2,A3,A4,0.06,0.05)");
model._set("E2", "=YIELDMAT(A2,A3,A4,0.06,99)");
model.evaluate();
assert_eq!(model._get_text("B1"), *"#NUM!");
assert_eq!(model._get_text("B2"), *"#NUM!");
assert_eq!(model._get_text("B3"), *"#NUM!");
}
#[test]
fn fn_yield_invalid_frequency() {
let mut model = new_empty_model();
model._set("A1", "=DATE(2023,1,1)");
model._set("A2", "=DATE(2024,1,1)");
model._set("B1", "=YIELD(A1,A2,5%,99,100,0)");
model._set("B2", "=YIELD(A1,A2,5%,99,100,3)");
model._set("B3", "=YIELD(A1,A2,5%,99,100,5)");
model.evaluate();
assert_eq!(model._get_text("B1"), *"#NUM!");
assert_eq!(model._get_text("B2"), *"#NUM!");
assert_eq!(model._get_text("B3"), *"#NUM!");
}
#[test]
fn fn_bond_functions_date_ordering() {
let mut model = new_empty_model();
model._set("A1", "=DATE(2022,1,1)"); // settlement
model._set("A2", "=DATE(2021,12,31)"); // maturity (before settlement)
model._set("A3", "=DATE(2020,1,1)"); // issue
// Test settlement >= maturity
model._set("B1", "=PRICEDISC(A1,A2,0.05,100)");
model._set("B2", "=YIELDDISC(A1,A2,95,100)");
model._set("B3", "=DISC(A1,A2,95,100)");
model._set("B4", "=RECEIVED(A1,A2,1000,0.05)");
model._set("B5", "=INTRATE(A1,A2,1000,1050)");
model._set("B6", "=PRICEMAT(A1,A2,A3,0.06,0.05)");
model._set("B7", "=YIELDMAT(A1,A2,A3,0.06,99)");
// Test settlement < issue for YIELDMAT/PRICEMAT
model._set("A4", "=DATE(2023,1,1)"); // later issue date
model._set("C1", "=PRICEMAT(A1,A2,A4,0.06,0.05)"); // settlement < issue
model._set("C2", "=YIELDMAT(A1,A2,A4,0.06,99)"); // settlement < issue
model.evaluate();
assert_eq!(model._get_text("B1"), *"#NUM!");
assert_eq!(model._get_text("B2"), *"#NUM!");
assert_eq!(model._get_text("B3"), *"#NUM!");
}
#[test]
fn fn_price_invalid_dates() {
let mut model = new_empty_model();
model._set("A1", "=DATE(2023,1,1)");
model._set("A2", "=DATE(2024,1,1)");
model._set("B1", "=PRICE(A2,A1,5%,6%,100,2)");
model._set("B2", "=PRICE(A1,A1,5%,6%,100,2)");
model.evaluate();
assert_eq!(model._get_text("B1"), *"#NUM!");
assert_eq!(model._get_text("B2"), *"#NUM!");
}
#[test]
fn fn_bond_functions_parameter_validation() {
let mut model = new_empty_model();
model._set("A1", "=DATE(2022,1,1)");
model._set("A2", "=DATE(2022,12,31)");
model._set("A3", "=DATE(2021,1,1)");
// Test negative/zero prices and redemptions
model._set("B1", "=PRICEDISC(A1,A2,0.05,0)"); // zero redemption
model._set("B2", "=PRICEDISC(A1,A2,0,100)"); // zero discount
model._set("B3", "=PRICEDISC(A1,A2,-0.05,100)"); // negative discount
model._set("C1", "=YIELDDISC(A1,A2,0,100)"); // zero price
model._set("C2", "=YIELDDISC(A1,A2,95,0)"); // zero redemption
model._set("C3", "=YIELDDISC(A1,A2,-95,100)"); // negative price
model._set("D1", "=DISC(A1,A2,0,100)"); // zero price
model._set("D2", "=DISC(A1,A2,95,0)"); // zero redemption
model._set("D3", "=DISC(A1,A2,-95,100)"); // negative price
model._set("E1", "=RECEIVED(A1,A2,0,0.05)"); // zero investment
model._set("E2", "=RECEIVED(A1,A2,1000,0)"); // zero discount
model._set("E3", "=RECEIVED(A1,A2,-1000,0.05)"); // negative investment
model._set("F1", "=INTRATE(A1,A2,0,1050)"); // zero investment
model._set("F2", "=INTRATE(A1,A2,1000,0)"); // zero redemption
model._set("F3", "=INTRATE(A1,A2,-1000,1050)"); // negative investment
model._set("G1", "=PRICEMAT(A1,A2,A3,-0.06,0.05)"); // negative rate
model._set("G2", "=PRICEMAT(A1,A2,A3,0.06,-0.05)"); // negative yield
model._set("H1", "=YIELDMAT(A1,A2,A3,0.06,0)"); // zero price
model._set("H2", "=YIELDMAT(A1,A2,A3,-0.06,99)"); // negative rate
model.evaluate();
assert_eq!(model._get_text("B1"), *"#NUM!");
assert_eq!(model._get_text("B2"), *"#NUM!");
}
#[test]
fn fn_yield_invalid_dates() {
let mut model = new_empty_model();
model._set("A1", "=DATE(2023,1,1)");
model._set("A2", "=DATE(2024,1,1)");
model._set("B1", "=YIELD(A2,A1,5%,99,100,2)");
model._set("B2", "=YIELD(A1,A1,5%,99,100,2)");
model.evaluate();
assert_eq!(model._get_text("B1"), *"#NUM!");
assert_eq!(model._get_text("B2"), *"#NUM!");
}
#[test]
fn fn_price_with_basis() {
let mut model = new_empty_model();
model._set("A1", "=DATE(2023,1,1)");
model._set("A2", "=DATE(2024,1,1)");
model._set("B1", "=PRICE(A1,A2,5%,6%,100,2,0)");
model._set("B2", "=PRICE(A1,A2,5%,6%,100,2,1)");
model.evaluate();
assert!(model._get_text("B1").parse::<f64>().is_ok());
assert!(model._get_text("B2").parse::<f64>().is_ok());
}
#[test]
fn fn_yield_with_basis() {
let mut model = new_empty_model();
model._set("A1", "=DATE(2023,1,1)");
model._set("A2", "=DATE(2024,1,1)");
model._set("B1", "=YIELD(A1,A2,5%,99,100,2,0)");
model._set("B2", "=YIELD(A1,A2,5%,99,100,2,1)");
model.evaluate();
assert!(model._get_text("B1").parse::<f64>().is_ok());
assert!(model._get_text("B2").parse::<f64>().is_ok());
}
#[test]
fn fn_price_yield_inverse_functions() {
// Verifies PRICE and YIELD are mathematical inverses
// Regression test for periods calculation type mismatch
let mut model = new_empty_model();
model._set("A1", "=DATE(2023,1,15)");
model._set("A2", "=DATE(2024,7,15)"); // ~1.5 years, fractional periods
model._set("A3", "4.75%"); // coupon
model._set("A4", "5.125%"); // yield
model._set("B1", "=PRICE(A1,A2,A3,A4,100,2)");
model._set("B2", "=YIELD(A1,A2,A3,B1,100,2)");
model.evaluate();
let calculated_yield: f64 = model._get_text("B2").parse().unwrap();
let expected_yield = 0.05125;
assert!(
(calculated_yield - expected_yield).abs() < 1e-12,
"YIELD should recover original yield: expected {expected_yield}, got {calculated_yield}"
);
}
#[test]
fn fn_price_yield_round_trip_stability() {
// Tests numerical stability through multiple PRICE->YIELD->PRICE cycles
let mut model = new_empty_model();
model._set("A1", "=DATE(2023,3,10)");
model._set("A2", "=DATE(2024,11,22)"); // Irregular period length
model._set("A3", "3.25%"); // coupon rate
model._set("A4", "4.875%"); // initial yield
// First round-trip
model._set("B1", "=PRICE(A1,A2,A3,A4,100,4)");
model._set("B2", "=YIELD(A1,A2,A3,B1,100,4)");
// Second round-trip
model._set("B3", "=PRICE(A1,A2,A3,B2,100,4)");
model.evaluate();
let price1: f64 = model._get_text("B1").parse().unwrap();
let price2: f64 = model._get_text("B3").parse().unwrap();
assert!(
(price1 - price2).abs() < 1e-10,
"Round-trip should be stable: {price1} vs {price2}"
);
}
#[test]
fn fn_bond_functions_basis_validation() {
let mut model = new_empty_model();
model._set("A1", "=DATE(2022,1,1)");
model._set("A2", "=DATE(2022,12,31)");
model._set("A3", "=DATE(2021,1,1)");
// Test valid basis values (0-4)
model._set("B1", "=PRICEDISC(A1,A2,0.05,100,0)");
model._set("B2", "=PRICEDISC(A1,A2,0.05,100,1)");
model._set("B3", "=PRICEDISC(A1,A2,0.05,100,2)");
model._set("B4", "=PRICEDISC(A1,A2,0.05,100,3)");
model._set("B5", "=PRICEDISC(A1,A2,0.05,100,4)");
// Test invalid basis values
model._set("C1", "=PRICEDISC(A1,A2,0.05,100,-1)");
model._set("C2", "=PRICEDISC(A1,A2,0.05,100,5)");
model._set("C3", "=YIELDDISC(A1,A2,95,100,10)");
model._set("C4", "=DISC(A1,A2,95,100,-5)");
model._set("C5", "=RECEIVED(A1,A2,1000,0.05,99)");
model._set("C6", "=INTRATE(A1,A2,1000,1050,-2)");
model._set("C7", "=PRICEMAT(A1,A2,A3,0.06,0.05,7)");
model._set("C8", "=YIELDMAT(A1,A2,A3,0.06,99,-3)");
model.evaluate();
// Valid basis should work
assert_ne!(model._get_text("B1"), *"#ERROR!");
assert_ne!(model._get_text("B2"), *"#ERROR!");
assert_ne!(model._get_text("B3"), *"#ERROR!");
assert_ne!(model._get_text("B4"), *"#ERROR!");
assert_ne!(model._get_text("B5"), *"#ERROR!");
// Invalid basis should error
assert_eq!(model._get_text("C1"), *"#NUM!");
assert_eq!(model._get_text("C2"), *"#NUM!");
assert_eq!(model._get_text("C3"), *"#NUM!");
assert_eq!(model._get_text("C4"), *"#NUM!");
assert_eq!(model._get_text("C5"), *"#NUM!");
assert_eq!(model._get_text("C6"), *"#NUM!");
assert_eq!(model._get_text("C7"), *"#NUM!");
assert_eq!(model._get_text("C8"), *"#NUM!");
}
#[test]
fn fn_bond_functions_relationships() {
// Test mathematical relationships between functions
let mut model = new_empty_model();
model._set("A1", "=DATE(2021,1,1)");
model._set("A2", "=DATE(2021,7,1)");
model._set("B1", "=PRICEDISC(A1,A2,5%,100)");
model._set("B2", "=YIELDDISC(A1,A2,B1,100)");
model._set("B3", "=DISC(A1,A2,B1,100)");
model._set("B4", "=RECEIVED(A1,A2,1000,5%)");
model._set("B5", "=INTRATE(A1,A2,1000,1050)");
model._set("B6", "=PRICEMAT(A1,A2,DATE(2020,7,1),6%,5%)");
model._set("B7", "=YIELDMAT(A1,A2,DATE(2020,7,1),6%,99)");
model.evaluate();
assert_eq!(
model.get_cell_value_by_ref("Sheet1!B1"),
Ok(CellValue::Number(97.5))
);
if let Ok(CellValue::Number(v)) = model.get_cell_value_by_ref("Sheet1!B2") {
assert!((v - 0.051282051).abs() < 1e-6);
}
if let Ok(CellValue::Number(v)) = model.get_cell_value_by_ref("Sheet1!B3") {
assert!((v - 0.05).abs() < 1e-6);
}
if let Ok(CellValue::Number(v)) = model.get_cell_value_by_ref("Sheet1!B4") {
assert!((v - 1025.641025).abs() < 1e-6);
}
if let Ok(CellValue::Number(v)) = model.get_cell_value_by_ref("Sheet1!B5") {
assert!((v - 0.10).abs() < 1e-6);
}
if let Ok(CellValue::Number(v)) = model.get_cell_value_by_ref("Sheet1!B6") {
assert!((v - 100.414634).abs() < 1e-6);
}
if let Ok(CellValue::Number(v)) = model.get_cell_value_by_ref("Sheet1!B7") {
assert!((v - 0.078431372).abs() < 1e-6);
}
}

View File

@@ -1,127 +0,0 @@
#![allow(clippy::unwrap_used)]
use crate::{cell::CellValue, test::util::new_empty_model};
#[test]
fn computation() {
let mut model = new_empty_model();
model._set("B1", "0.1");
model._set("B2", "0.2");
model._set("A1", "=FVSCHEDULE(100,B1:B2)");
model.evaluate();
assert_eq!(model._get_text("A1"), "132");
}
#[test]
fn fvschedule_basic_with_precise_assertion() {
let mut model = new_empty_model();
model._set("A1", "1000");
model._set("B1", "0.09");
model._set("B2", "0.11");
model._set("B3", "0.1");
model._set("C1", "=FVSCHEDULE(A1,B1:B3)");
model.evaluate();
assert_eq!(
model.get_cell_value_by_ref("Sheet1!C1"),
Ok(CellValue::Number(1330.89))
);
}
#[test]
fn fvschedule_compound_rates() {
let mut model = new_empty_model();
model._set("A1", "1");
model._set("A2", "0.1");
model._set("A3", "0.2");
model._set("A4", "0.3");
model._set("B1", "=FVSCHEDULE(A1, A2:A4)");
model.evaluate();
// 1 * (1+0.1) * (1+0.2) * (1+0.3) = 1 * 1.1 * 1.2 * 1.3 = 1.716
assert_eq!(model._get_text("B1"), "1.716");
}
#[test]
fn fvschedule_ignore_non_numbers() {
let mut model = new_empty_model();
model._set("A1", "1");
model._set("A2", "0.1");
model._set("A3", "foo"); // non-numeric value should be ignored
model._set("A4", "0.2");
model._set("B1", "=FVSCHEDULE(A1, A2:A4)");
model.evaluate();
// 1 * (1+0.1) * (1+0.2) = 1 * 1.1 * 1.2 = 1.32
assert_eq!(model._get_text("B1"), "1.32");
}
#[test]
fn fvschedule_argument_count() {
let mut model = new_empty_model();
model._set("A1", "=FVSCHEDULE()");
model._set("A2", "=FVSCHEDULE(1)");
model._set("A3", "=FVSCHEDULE(1,1,1)");
model.evaluate();
assert_eq!(model._get_text("A1"), *"#ERROR!");
assert_eq!(model._get_text("A2"), *"#ERROR!");
assert_eq!(model._get_text("A3"), *"#ERROR!");
}
#[test]
fn fvschedule_edge_cases() {
let mut model = new_empty_model();
// Test with zero principal
model._set("A1", "0");
model._set("A2", "0.1");
model._set("A3", "0.2");
model._set("B1", "=FVSCHEDULE(A1, A2:A3)");
// Test with negative principal
model._set("C1", "-100");
model._set("D1", "=FVSCHEDULE(C1, A2:A3)");
// Test with zero rates
model._set("E1", "100");
model._set("E2", "0");
model._set("E3", "0");
model._set("F1", "=FVSCHEDULE(E1, E2:E3)");
model.evaluate();
assert_eq!(model._get_text("B1"), "0"); // 0 * anything = 0
assert_eq!(model._get_text("D1"), "-132"); // -100 * 1.1 * 1.2 = -132
assert_eq!(model._get_text("F1"), "100"); // 100 * 1 * 1 = 100
}
#[test]
fn fvschedule_rate_validation() {
let mut model = new_empty_model();
// Test with rate exactly -1 (should cause error due to validation in patch 1)
model._set("A1", "100");
model._set("A2", "-1");
model._set("A3", "0.1");
model._set("B1", "=FVSCHEDULE(A1, A2:A3)");
// Test with rate less than -1 (should cause error)
model._set("C1", "100");
model._set("C2", "-1.5");
model._set("C3", "0.1");
model._set("D1", "=FVSCHEDULE(C1, C2:C3)");
model.evaluate();
assert_eq!(model._get_text("B1"), "#NUM!");
assert_eq!(model._get_text("D1"), "#NUM!");
}

View File

@@ -0,0 +1,22 @@
#![allow(clippy::unwrap_used)]
use crate::test::util::new_empty_model;
#[test]
fn arguments() {
let mut model = new_empty_model();
model._set("A1", "=MOD(5,2)");
model._set("A2", "=MOD()");
model._set("A3", "=MOD(5, 2, 1)");
model._set("A4", "=QUOTIENT(5, 2)");
model._set("A5", "=QUOTIENT()");
model._set("A6", "=QUOTIENT(5, 2, 1)");
model.evaluate();
assert_eq!(model._get_text("A1"), *"1");
assert_eq!(model._get_text("A2"), *"#ERROR!");
assert_eq!(model._get_text("A3"), *"#ERROR!");
assert_eq!(model._get_text("A4"), *"2");
assert_eq!(model._get_text("A5"), *"#ERROR!");
assert_eq!(model._get_text("A6"), *"#ERROR!");
}

View File

@@ -0,0 +1,40 @@
#![allow(clippy::unwrap_used)]
use crate::test::util::new_empty_model;
#[test]
fn arguments() {
let mut model = new_empty_model();
model._set("A1", "=MROUND()");
model._set("A2", "=MROUND(10)");
model._set("A3", "=MROUND(10, 3)");
model._set("A4", "=MROUND(10, 3, 1)");
model._set("A5", "=TRUNC()");
model._set("A6", "=TRUNC(10)");
model._set("A7", "=TRUNC(10.22, 1)");
model._set("A8", "=TRUNC(10, 3, 1)");
model._set("A9", "=INT()");
model._set("A10", "=INT(10.22)");
model._set("A11", "=INT(10.22, 1)");
model._set("A12", "=INT(10.22, 1, 2)");
model.evaluate();
assert_eq!(model._get_text("A1"), *"#ERROR!");
assert_eq!(model._get_text("A2"), *"#ERROR!");
assert_eq!(model._get_text("A3"), *"9");
assert_eq!(model._get_text("A4"), *"#ERROR!");
assert_eq!(model._get_text("A5"), *"#ERROR!");
assert_eq!(model._get_text("A6"), *"#ERROR!");
assert_eq!(model._get_text("A7"), *"10.2");
assert_eq!(model._get_text("A8"), *"#ERROR!");
assert_eq!(model._get_text("A9"), *"#ERROR!");
assert_eq!(model._get_text("A10"), *"10");
assert_eq!(model._get_text("A11"), *"#ERROR!");
assert_eq!(model._get_text("A12"), *"#ERROR!");
}

39
base/src/test/test_now.rs Normal file
View File

@@ -0,0 +1,39 @@
#![allow(clippy::unwrap_used)]
use crate::{mock_time, test::util::new_empty_model};
// 14:44 20 Mar 2023 Berlin
const TIMESTAMP_2023: i64 = 1679319865208;
#[test]
fn arguments() {
mock_time::set_mock_time(TIMESTAMP_2023);
let mut model = new_empty_model();
model._set("A1", "=NOW(1, 1)");
model._set("A2", "=NOW(\"Europe/Berlin\")");
model._set("A3", "=NOW(\"faketimezone\")");
model.evaluate();
assert_eq!(
model._get_text("A1"),
"#ERROR!",
"Wrong number of arguments"
);
assert_eq!(model._get_text("A2"), *"20/03/2023 14:44:25");
assert_eq!(
model._get_text("A3"),
"#VALUE!",
"Invalid timezone: faketimezone"
);
}
#[test]
fn returns_date_time() {
mock_time::set_mock_time(TIMESTAMP_2023);
let mut model = new_empty_model();
model._set("A1", "=NOW()");
model.evaluate();
let text = model._get_text("A1");
assert_eq!(text, *"20/03/2023 13:44:25");
}

View File

@@ -8,6 +8,15 @@ fn test_simple_format() {
assert_eq!(formatted.text, "2.3".to_string());
}
#[test]
fn test_maximum_zeros() {
let formatted = format_number(1.0 / 3.0, "#,##0.0000000000000000000", "en");
assert_eq!(formatted.text, "0.3333333333333330000".to_string());
let formatted = format_number(1234.0 + 1.0 / 3.0, "#,##0.0000000000000000000", "en");
assert_eq!(formatted.text, "1,234.3333333333300000000".to_string());
}
#[test]
#[ignore = "not yet implemented"]
fn test_wrong_locale() {

View File

@@ -0,0 +1,17 @@
#![allow(clippy::unwrap_used)]
use crate::test::util::new_empty_model;
#[test]
fn arguments() {
let mut model = new_empty_model();
model._set("A1", "=SUMSQ()");
model._set("A2", "=SUMSQ(2)");
model._set("A3", "=SUMSQ(1, 2)");
model.evaluate();
assert_eq!(model._get_text("A1"), *"#ERROR!");
assert_eq!(model._get_text("A2"), *"4");
assert_eq!(model._get_text("A3"), *"5");
}

View File

@@ -33,7 +33,8 @@ fn now_basic_utc() {
model.evaluate();
assert_eq!(model._get_text("A1"), *"20/03/2023");
assert_eq!(model._get_text("A2"), *"45005.572511574");
// 45005.572511574
assert_eq!(model._get_text("A2"), *"20/03/2023 13:44:25");
}
#[test]
@@ -46,5 +47,5 @@ fn now_basic_europe_berlin() {
assert_eq!(model._get_text("A1"), *"20/03/2023");
// This is UTC + 1 hour: 45005.572511574 + 1/24
assert_eq!(model._get_text("A2"), *"45005.614178241");
assert_eq!(model._get_text("A2"), *"20/03/2023 14:44:25");
}

View File

@@ -96,3 +96,14 @@ fn test_fn_tan_pi2() {
// This is consistent with IEEE 754 but inconsistent with Excel
assert_eq!(model._get_text("A1"), *"1.63312E+16");
}
#[test]
fn test_trigonometric_identity() {
let mut model = new_empty_model();
model._set("A1", "=COTH(1)*CSCH(1)");
model._set("A2", "=COSH(1)/(SINH(1))^2");
model._set("A3", "=A1=A2");
model.evaluate();
assert_eq!(model._get_text("A3"), *"TRUE");
}

View File

@@ -0,0 +1,53 @@
#![allow(clippy::unwrap_used)]
use crate::test::util::new_empty_model;
#[test]
fn fn_arguments() {
let mut model = new_empty_model();
model._set("A1", "=CSC()");
model._set("A2", "=SEC()");
model._set("A3", "=COT()");
model._set("A4", "=CSCH()");
model._set("A5", "=SECH()");
model._set("A6", "=COTH()");
model._set("A7", "=ACOT()");
model._set("A8", "=ACOTH()");
model._set("B1", "=CSC(1, 2)");
model._set("B2", "=SEC(1, 2)");
model._set("B3", "=COT(1, 2)");
model._set("B4", "=CSCH(1, 2)");
model._set("B5", "=SECH(1, 2)");
model._set("B6", "=COTH(1, 2)");
model._set("B7", "=ACOT(1, 2)");
model._set("B8", "=ACOTH(1, 2)");
model.evaluate();
assert_eq!(model._get_text("A1"), *"#ERROR!");
assert_eq!(model._get_text("A2"), *"#ERROR!");
assert_eq!(model._get_text("A3"), *"#ERROR!");
assert_eq!(model._get_text("A4"), *"#ERROR!");
assert_eq!(model._get_text("A5"), *"#ERROR!");
assert_eq!(model._get_text("A6"), *"#ERROR!");
assert_eq!(model._get_text("A7"), *"#ERROR!");
assert_eq!(model._get_text("A8"), *"#ERROR!");
assert_eq!(model._get_text("B1"), *"#ERROR!");
assert_eq!(model._get_text("B2"), *"#ERROR!");
assert_eq!(model._get_text("B3"), *"#ERROR!");
assert_eq!(model._get_text("B4"), *"#ERROR!");
assert_eq!(model._get_text("B5"), *"#ERROR!");
assert_eq!(model._get_text("B6"), *"#ERROR!");
assert_eq!(model._get_text("B7"), *"#ERROR!");
assert_eq!(model._get_text("B8"), *"#ERROR!");
}

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