use std::any::Any;
use std::sync::Arc;
use arrow::array::AsArray;
use arrow::datatypes::DataType::{Float32, Float64};
use arrow::datatypes::{DataType, Float32Type, Float64Type};
use datafusion_common::utils::take_function_args;
use datafusion_common::{Result, ScalarValue, internal_err};
use datafusion_expr::sort_properties::{ExprProperties, SortProperties};
use datafusion_expr::{
ColumnarValue, Documentation, ScalarFunctionArgs, ScalarUDFImpl, Signature,
Volatility,
};
use datafusion_macros::user_doc;
#[user_doc(
doc_section(label = "Math Functions"),
description = r#"Returns the sign of a number.
Negative numbers return `-1`.
Zero and positive numbers return `1`."#,
syntax_example = "signum(numeric_expression)",
standard_argument(name = "numeric_expression", prefix = "Numeric"),
sql_example = r#"```sql
> SELECT signum(-42);
+-------------+
| signum(-42) |
+-------------+
| -1 |
+-------------+
```"#
)]
#[derive(Debug, PartialEq, Eq, Hash)]
pub struct SignumFunc {
signature: Signature,
}
impl Default for SignumFunc {
fn default() -> Self {
SignumFunc::new()
}
}
impl SignumFunc {
pub fn new() -> Self {
use DataType::*;
Self {
signature: Signature::uniform(
1,
vec![Float64, Float32],
Volatility::Immutable,
),
}
}
}
impl ScalarUDFImpl for SignumFunc {
fn as_any(&self) -> &dyn Any {
self
}
fn name(&self) -> &str {
"signum"
}
fn signature(&self) -> &Signature {
&self.signature
}
fn return_type(&self, arg_types: &[DataType]) -> Result<DataType> {
match &arg_types[0] {
Float32 => Ok(Float32),
_ => Ok(Float64),
}
}
fn output_ordering(&self, input: &[ExprProperties]) -> Result<SortProperties> {
Ok(input[0].sort_properties)
}
fn invoke_with_args(&self, args: ScalarFunctionArgs) -> Result<ColumnarValue> {
let return_type = args.return_type().clone();
let [arg] = take_function_args(self.name(), args.args)?;
match arg {
ColumnarValue::Scalar(scalar) => {
if scalar.is_null() {
return ColumnarValue::Scalar(ScalarValue::Null)
.cast_to(&return_type, None);
}
match scalar {
ScalarValue::Float64(Some(v)) => {
let result = if v == 0.0 { 0.0 } else { v.signum() };
Ok(ColumnarValue::Scalar(ScalarValue::Float64(Some(result))))
}
ScalarValue::Float32(Some(v)) => {
let result = if v == 0.0 { 0.0 } else { v.signum() };
Ok(ColumnarValue::Scalar(ScalarValue::Float32(Some(result))))
}
_ => {
internal_err!(
"Unexpected scalar type for signum: {:?}",
scalar.data_type()
)
}
}
}
ColumnarValue::Array(array) => match array.data_type() {
Float64 => Ok(ColumnarValue::Array(Arc::new(
array.as_primitive::<Float64Type>().unary::<_, Float64Type>(
|x: f64| {
if x == 0.0 { 0.0 } else { x.signum() }
},
),
))),
Float32 => Ok(ColumnarValue::Array(Arc::new(
array.as_primitive::<Float32Type>().unary::<_, Float32Type>(
|x: f32| {
if x == 0.0 { 0.0 } else { x.signum() }
},
),
))),
other => {
internal_err!("Unsupported data type {other:?} for function signum")
}
},
}
}
fn documentation(&self) -> Option<&Documentation> {
self.doc()
}
}
#[cfg(test)]
mod test {
use std::sync::Arc;
use arrow::array::{ArrayRef, Float32Array, Float64Array};
use arrow::datatypes::{DataType, Field};
use datafusion_common::cast::{as_float32_array, as_float64_array};
use datafusion_common::config::ConfigOptions;
use datafusion_expr::{ColumnarValue, ScalarFunctionArgs, ScalarUDFImpl};
use crate::math::signum::SignumFunc;
#[test]
fn test_signum_f32() {
let array = Arc::new(Float32Array::from(vec![
-1.0,
-0.0,
0.0,
1.0,
-0.01,
0.01,
f32::NAN,
f32::INFINITY,
f32::NEG_INFINITY,
]));
let arg_fields = vec![Field::new("a", DataType::Float32, false).into()];
let args = ScalarFunctionArgs {
args: vec![ColumnarValue::Array(Arc::clone(&array) as ArrayRef)],
arg_fields,
number_rows: array.len(),
return_field: Field::new("f", DataType::Float32, true).into(),
config_options: Arc::new(ConfigOptions::default()),
};
let result = SignumFunc::new()
.invoke_with_args(args)
.expect("failed to initialize function signum");
match result {
ColumnarValue::Array(arr) => {
let floats = as_float32_array(&arr)
.expect("failed to convert result to a Float32Array");
assert_eq!(floats.len(), 9);
assert_eq!(floats.value(0), -1.0);
assert_eq!(floats.value(1), 0.0);
assert_eq!(floats.value(2), 0.0);
assert_eq!(floats.value(3), 1.0);
assert_eq!(floats.value(4), -1.0);
assert_eq!(floats.value(5), 1.0);
assert!(floats.value(6).is_nan());
assert_eq!(floats.value(7), 1.0);
assert_eq!(floats.value(8), -1.0);
}
ColumnarValue::Scalar(_) => {
panic!("Expected an array value")
}
}
}
#[test]
fn test_signum_f64() {
let array = Arc::new(Float64Array::from(vec![
-1.0,
-0.0,
0.0,
1.0,
-0.01,
0.01,
f64::NAN,
f64::INFINITY,
f64::NEG_INFINITY,
]));
let arg_fields = vec![Field::new("a", DataType::Float64, false).into()];
let args = ScalarFunctionArgs {
args: vec![ColumnarValue::Array(Arc::clone(&array) as ArrayRef)],
arg_fields,
number_rows: array.len(),
return_field: Field::new("f", DataType::Float64, true).into(),
config_options: Arc::new(ConfigOptions::default()),
};
let result = SignumFunc::new()
.invoke_with_args(args)
.expect("failed to initialize function signum");
match result {
ColumnarValue::Array(arr) => {
let floats = as_float64_array(&arr)
.expect("failed to convert result to a Float32Array");
assert_eq!(floats.len(), 9);
assert_eq!(floats.value(0), -1.0);
assert_eq!(floats.value(1), 0.0);
assert_eq!(floats.value(2), 0.0);
assert_eq!(floats.value(3), 1.0);
assert_eq!(floats.value(4), -1.0);
assert_eq!(floats.value(5), 1.0);
assert!(floats.value(6).is_nan());
assert_eq!(floats.value(7), 1.0);
assert_eq!(floats.value(8), -1.0);
}
ColumnarValue::Scalar(_) => {
panic!("Expected an array value")
}
}
}
}