re_types/blueprint/datatypes/
tensor_dimension_index_slider.rs

1// DO NOT EDIT! This file was auto-generated by crates/build/re_types_builder/src/codegen/rust/api.rs
2// Based on "crates/store/re_types/definitions/rerun/blueprint/datatypes/tensor_dimension_index_slider.fbs".
3
4#![allow(unused_imports)]
5#![allow(unused_parens)]
6#![allow(clippy::clone_on_copy)]
7#![allow(clippy::cloned_instead_of_copied)]
8#![allow(clippy::map_flatten)]
9#![allow(clippy::needless_question_mark)]
10#![allow(clippy::new_without_default)]
11#![allow(clippy::redundant_closure)]
12#![allow(clippy::too_many_arguments)]
13#![allow(clippy::too_many_lines)]
14
15use ::re_types_core::try_serialize_field;
16use ::re_types_core::SerializationResult;
17use ::re_types_core::{ComponentBatch as _, SerializedComponentBatch};
18use ::re_types_core::{ComponentDescriptor, ComponentName};
19use ::re_types_core::{DeserializationError, DeserializationResult};
20
21/// **Datatype**: Defines a slider for the index of some dimension.
22///
23/// ⚠️ **This type is _unstable_ and may change significantly in a way that the data won't be backwards compatible.**
24#[derive(Clone, Debug, Default, Copy, Hash, PartialEq, Eq)]
25pub struct TensorDimensionIndexSlider {
26    /// The dimension number.
27    pub dimension: u32,
28}
29
30::re_types_core::macros::impl_into_cow!(TensorDimensionIndexSlider);
31
32impl ::re_types_core::Loggable for TensorDimensionIndexSlider {
33    #[inline]
34    fn arrow_datatype() -> arrow::datatypes::DataType {
35        #![allow(clippy::wildcard_imports)]
36        use arrow::datatypes::*;
37        DataType::Struct(Fields::from(vec![Field::new(
38            "dimension",
39            DataType::UInt32,
40            false,
41        )]))
42    }
43
44    fn to_arrow_opt<'a>(
45        data: impl IntoIterator<Item = Option<impl Into<::std::borrow::Cow<'a, Self>>>>,
46    ) -> SerializationResult<arrow::array::ArrayRef>
47    where
48        Self: Clone + 'a,
49    {
50        #![allow(clippy::wildcard_imports)]
51        #![allow(clippy::manual_is_variant_and)]
52        use ::re_types_core::{arrow_helpers::as_array_ref, Loggable as _, ResultExt as _};
53        use arrow::{array::*, buffer::*, datatypes::*};
54        Ok({
55            let fields = Fields::from(vec![Field::new("dimension", DataType::UInt32, false)]);
56            let (somes, data): (Vec<_>, Vec<_>) = data
57                .into_iter()
58                .map(|datum| {
59                    let datum: Option<::std::borrow::Cow<'a, Self>> = datum.map(Into::into);
60                    (datum.is_some(), datum)
61                })
62                .unzip();
63            let validity: Option<arrow::buffer::NullBuffer> = {
64                let any_nones = somes.iter().any(|some| !*some);
65                any_nones.then(|| somes.into())
66            };
67            as_array_ref(StructArray::new(
68                fields,
69                vec![{
70                    let (somes, dimension): (Vec<_>, Vec<_>) = data
71                        .iter()
72                        .map(|datum| {
73                            let datum = datum.as_ref().map(|datum| datum.dimension.clone());
74                            (datum.is_some(), datum)
75                        })
76                        .unzip();
77                    let dimension_validity: Option<arrow::buffer::NullBuffer> = {
78                        let any_nones = somes.iter().any(|some| !*some);
79                        any_nones.then(|| somes.into())
80                    };
81                    as_array_ref(PrimitiveArray::<UInt32Type>::new(
82                        ScalarBuffer::from(
83                            dimension
84                                .into_iter()
85                                .map(|v| v.unwrap_or_default())
86                                .collect::<Vec<_>>(),
87                        ),
88                        dimension_validity,
89                    ))
90                }],
91                validity,
92            ))
93        })
94    }
95
96    fn from_arrow_opt(
97        arrow_data: &dyn arrow::array::Array,
98    ) -> DeserializationResult<Vec<Option<Self>>>
99    where
100        Self: Sized,
101    {
102        #![allow(clippy::wildcard_imports)]
103        use ::re_types_core::{arrow_zip_validity::ZipValidity, Loggable as _, ResultExt as _};
104        use arrow::{array::*, buffer::*, datatypes::*};
105        Ok({
106            let arrow_data = arrow_data
107                .as_any()
108                .downcast_ref::<arrow::array::StructArray>()
109                .ok_or_else(|| {
110                    let expected = Self::arrow_datatype();
111                    let actual = arrow_data.data_type().clone();
112                    DeserializationError::datatype_mismatch(expected, actual)
113                })
114                .with_context("rerun.blueprint.datatypes.TensorDimensionIndexSlider")?;
115            if arrow_data.is_empty() {
116                Vec::new()
117            } else {
118                let (arrow_data_fields, arrow_data_arrays) =
119                    (arrow_data.fields(), arrow_data.columns());
120                let arrays_by_name: ::std::collections::HashMap<_, _> = arrow_data_fields
121                    .iter()
122                    .map(|field| field.name().as_str())
123                    .zip(arrow_data_arrays)
124                    .collect();
125                let dimension = {
126                    if !arrays_by_name.contains_key("dimension") {
127                        return Err(DeserializationError::missing_struct_field(
128                            Self::arrow_datatype(),
129                            "dimension",
130                        ))
131                        .with_context("rerun.blueprint.datatypes.TensorDimensionIndexSlider");
132                    }
133                    let arrow_data = &**arrays_by_name["dimension"];
134                    arrow_data
135                        .as_any()
136                        .downcast_ref::<UInt32Array>()
137                        .ok_or_else(|| {
138                            let expected = DataType::UInt32;
139                            let actual = arrow_data.data_type().clone();
140                            DeserializationError::datatype_mismatch(expected, actual)
141                        })
142                        .with_context(
143                            "rerun.blueprint.datatypes.TensorDimensionIndexSlider#dimension",
144                        )?
145                        .into_iter()
146                };
147                ZipValidity::new_with_validity(
148                        ::itertools::izip!(dimension),
149                        arrow_data.nulls(),
150                    )
151                    .map(|opt| {
152                        opt
153                            .map(|(dimension)| Ok(Self {
154                                dimension: dimension
155                                    .ok_or_else(DeserializationError::missing_data)
156                                    .with_context(
157                                        "rerun.blueprint.datatypes.TensorDimensionIndexSlider#dimension",
158                                    )?,
159                            }))
160                            .transpose()
161                    })
162                    .collect::<DeserializationResult<Vec<_>>>()
163                    .with_context(
164                        "rerun.blueprint.datatypes.TensorDimensionIndexSlider",
165                    )?
166            }
167        })
168    }
169}
170
171impl From<u32> for TensorDimensionIndexSlider {
172    #[inline]
173    fn from(dimension: u32) -> Self {
174        Self { dimension }
175    }
176}
177
178impl From<TensorDimensionIndexSlider> for u32 {
179    #[inline]
180    fn from(value: TensorDimensionIndexSlider) -> Self {
181        value.dimension
182    }
183}
184
185impl ::re_byte_size::SizeBytes for TensorDimensionIndexSlider {
186    #[inline]
187    fn heap_size_bytes(&self) -> u64 {
188        self.dimension.heap_size_bytes()
189    }
190
191    #[inline]
192    fn is_pod() -> bool {
193        <u32>::is_pod()
194    }
195}
re_types/blueprint/datatypes/tensor_dimension_index_slider.rs

re_types/blueprint/datatypes/
tensor_dimension_index_slider.rs
