use arrow::array::Array;
use polars::prelude::*;
use pyo3::prelude::*;
use super::PySeries;
use crate::utils::EnterPolarsExt;
#[pymethods]
impl PySeries {
fn scatter(&self, py: Python<'_>, idx: PySeries, values: PySeries) -> PyResult<()> {
py.enter_polars(|| {
let mut lock = self.series.write();
let s = std::mem::take(&mut *lock);
let result = scatter(s, &idx.series.into_inner(), &values.series.into_inner());
match result {
Ok(out) => {
*lock = out;
Ok(())
},
Err((s, e)) => {
*lock = s;
Err(e)
},
}
})
}
}
fn scatter(mut s: Series, idx: &Series, values: &Series) -> Result<Series, (Series, PolarsError)> {
let logical_dtype = s.dtype().clone();
let values = if logical_dtype.is_categorical() || logical_dtype.is_enum() {
if matches!(
values.dtype(),
DataType::Categorical(_, _) | DataType::Enum(_, _) | DataType::String
) {
match values.strict_cast(&logical_dtype) {
Ok(values) => values,
Err(err) => return Err((s, err)),
}
} else {
return Err((
s,
polars_err!(InvalidOperation: "invalid values dtype '{}' for scattering into dtype '{}'", values.dtype(), logical_dtype),
));
}
} else {
values.clone()
};
let idx = match polars_ops::prelude::convert_to_unsigned_index(idx, s.len()) {
Ok(idx) => idx,
Err(err) => return Err((s, err)),
};
let idx = idx.rechunk();
let idx = idx.downcast_as_array();
if idx.null_count() > 0 {
return Err((
s,
PolarsError::ComputeError("index values should not be null".into()),
));
}
let idx = idx.values().as_slice();
let mut values = match values.to_physical_repr().cast(&s.dtype().to_physical()) {
Ok(values) => values,
Err(err) => return Err((s, err)),
};
if values.len() == 1 && idx.len() > 1 {
values = values.new_from_index(0, idx.len());
}
s = s.to_physical_repr().into_owned();
let s_mut_ref = &mut s;
scatter_impl(s_mut_ref, logical_dtype, idx, &values).map_err(|err| (s, err))
}
fn scatter_impl(
s: &mut Series,
logical_dtype: DataType,
idx: &[IdxSize],
values: &Series,
) -> PolarsResult<Series> {
let mutable_s = s._get_inner_mut();
let s = match logical_dtype.to_physical() {
DataType::Int8 => {
let ca: &mut ChunkedArray<Int8Type> = mutable_s.as_mut();
let values = values.i8()?;
ca.scatter(idx, values)
},
DataType::Int16 => {
let ca: &mut ChunkedArray<Int16Type> = mutable_s.as_mut();
let values = values.i16()?;
ca.scatter(idx, values)
},
DataType::Int32 => {
let ca: &mut ChunkedArray<Int32Type> = mutable_s.as_mut();
let values = values.i32()?;
ca.scatter(idx, values)
},
DataType::Int64 => {
let ca: &mut ChunkedArray<Int64Type> = mutable_s.as_mut();
let values = values.i64()?;
ca.scatter(idx, values)
},
DataType::UInt8 => {
let ca: &mut ChunkedArray<UInt8Type> = mutable_s.as_mut();
let values = values.u8()?;
ca.scatter(idx, values)
},
DataType::UInt16 => {
let ca: &mut ChunkedArray<UInt16Type> = mutable_s.as_mut();
let values = values.u16()?;
ca.scatter(idx, values)
},
DataType::UInt32 => {
let ca: &mut ChunkedArray<UInt32Type> = mutable_s.as_mut();
let values = values.u32()?;
ca.scatter(idx, values)
},
DataType::UInt64 => {
let ca: &mut ChunkedArray<UInt64Type> = mutable_s.as_mut();
let values = values.u64()?;
ca.scatter(idx, values)
},
DataType::Float32 => {
let ca: &mut ChunkedArray<Float32Type> = mutable_s.as_mut();
let values = values.f32()?;
ca.scatter(idx, values)
},
DataType::Float64 => {
let ca: &mut ChunkedArray<Float64Type> = mutable_s.as_mut();
let values = values.f64()?;
ca.scatter(idx, values)
},
DataType::Boolean => {
let ca = s.bool()?;
let values = values.bool()?;
ca.scatter(idx, values)
},
DataType::String => {
let ca = s.str()?;
let values = values.str()?;
ca.scatter(idx, values)
},
_ => {
return Err(PolarsError::ComputeError(
format!("not yet implemented for dtype: {logical_dtype}").into(),
));
},
};
s.and_then(|s| s.cast(&logical_dtype))
}