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use crate::TEMP_SUFFIX;
use crate::chart::Chart;
use crate::error::ChartonError;
use crate::mark::Mark;
use crate::prelude::IntoChartonSource;
use polars::prelude::*;
impl<T: Mark> Chart<T> {
/// Prepares data for Error Bar marks by calculating statistical intervals.
///
/// This transformation follows the "Data-Driven Layout" strategy used in Bar charts:
/// 1. **Deduplication**: Checks if Color field is the same as X to determine grouping.
/// 2. **Aggregation**: Computes Mean and Standard Deviation (1-sigma) for the Y-axis.
/// 3. **Gap Filling**: Uses a Cartesian Product to ensure every X-category has
/// the same number of groups, preventing misalignment in grouped layouts.
pub(crate) fn transform_errorbar_data(mut self) -> Result<Self, ChartonError> {
// --- STEP 1: Extract Encoding Context ---
let y_enc = self.encoding.y.as_ref().unwrap();
let x_enc = self.encoding.x.as_ref().unwrap();
// 这儿针对的是一个x和color（如果有）多个x值的情况，如果x,y, standard都已经算好了，则用calculate_transform.rs
let color_enc_opt = self.encoding.color.as_ref(); // 提前在chart中判断是否为离散型，需要离散型
let x_field = &x_enc.field;
let y_field = &y_enc.field;
// Define temp column names for the interval bounds
let y_min_col = format!("{}_{}_min", TEMP_SUFFIX, y_field);
let y_max_col = format!("{}_{}_max", TEMP_SUFFIX, y_field);
// --- STEP 2: Aggregation & Grouping ---
let mut group_selectors = vec![col(x_field)];
// Only add Color to grouping if it's a different field than X
let has_grouping_color = if let Some(ce) = color_enc_opt {
if &ce.field != x_field {
group_selectors.push(col(&ce.field));
true
} else {
false
}
} else {
false
};
let grouped_df = self
.data
.df
.clone()
.lazy()
.group_by_stable(group_selectors)
.agg([
// Center point
col(y_field).mean().alias(y_field),
// Standard Deviation Interval (Sample std, ddof=1). n=1 results in Null here.
(col(y_field).mean() - col(y_field).std(1)).alias(&y_min_col),
(col(y_field).mean() + col(y_field).std(1)).alias(&y_max_col),
])
.collect()?;
// --- STEP 3: Cartesian Product Gap Filling ---
// Ensuring structural consistency across all X categories
let filled_df = if has_grouping_color {
let ce = color_enc_opt.unwrap();
// preserved user-defined order
let x_uniques = grouped_df.column(x_field)?.unique_stable()?;
let c_uniques = grouped_df.column(&ce.field)?.unique_stable()?;
let x_len = x_uniques.len();
let c_len = c_uniques.len();
let mut x_repeated = Vec::with_capacity(x_len * c_len);
let mut c_repeated = Vec::with_capacity(x_len * c_len);
for i in 0..x_len {
let x_val = x_uniques.get(i)?;
for j in 0..c_len {
x_repeated.push(x_val.clone());
c_repeated.push(c_uniques.get(j)?.clone());
}
}
let all_combinations = df![
x_field => x_repeated,
&ce.field => c_repeated
]?;
all_combinations
.lazy()
.join(
grouped_df.lazy(),
[col(x_field), col(&ce.field)],
[col(x_field), col(&ce.field)],
JoinType::Left.into(),
)
// Note: We leave Y values as Null for missing gaps.
// The ErrorBar renderer should 'continue' on Nulls rather than draw a 0-length bar.
.collect()?
} else {
grouped_df
};
// Final Step: Update the chart's data source
self.data = (&filled_df).into_source()?;
Ok(self)
}
}