feat: 科研分析层全栈落地——光谱/时域/运动学分析工具链 + JWST/X 射线数据源 + 定时文献同步
数据分析层（新增 services/{spectrum,timeseries,analysis}）:
- 光谱参数提取 parameters.rs：LAMOST/SDSS/APOGEE/DESI FITS header 跨源归一化读取
Teff/logg/[Fe/H]/RV 及 ASPCAP 20+ 元素丰度，rayon 并发批量提取
- 谱线测量 lines.rs：内置真空/空气波长谱线表，窗口内极值搜索 + 梯形法积分 EW + FWHM，支持自定义谱线
- 交叉相关测速 cross_correlate.rs：对数波长重采样对齐，内置 Pickles 模板按光谱型插值，
CCF 峰值位置提取 RV 及不确定度
- 周期搜索 periodicity.rs：Lomb-Scargle 周期图（含 FAP 误报概率）+ BLS 凌星检测 + 相位折叠
- 变星分类 classification.rs：振幅/偏度/峰度/过零率/eta 等统计特征 + 规则分类（RR Lyrae/Cepheid/食双星/AGN 等）
- SED 拟合 sed.rs：多波段测光黑体模型拟合，输出 T_eff/半径/消光 A_V/光度及不确定度
- 运动学 kinematics.rs：视差+自行+RV → 银河系 UVW 空间速度，含移动星群成员概率（Banyan Σ 简化版）
- 化学丰度 chemistry.rs：[α/Fe] vs [Fe/H] 计算，厚盘/薄盘/晕星族判别
- 观测规划 observability.rs：目标升落时间/airmass/月相影响/曝光时间估算
- 赫罗图 hr_diagram.rs：Gaia TAP CMD 查询，新增 GET /api/analysis/hr-diagram 端点
数据获取层:
- JWST：clients/mast/jwst.rs 封装 MAST Portal 锥形检索 + JwstSpectrumFetcher（NIRSpec/MIRI 光谱）
- X 射线：clients/heasarc 封装 HEASARC TAP（ADQL）+ XMM-Newton/Chandra 光谱 fetcher
- 图像 cutout：SDSS SkyServer/STScI DSS/Pan-STARRS 三源 cutout + 发现图（Finding Chart）生成
- Source 枚举新增 Jwst/Xmm/Chandra 并注册 ObservationRegistry，前端 SOURCE_THEME 与筛选器同步三源
Agent 工具集（24→35）:
- 新增 9 个分析工具：get_spectrum_parameters / measure_spectral_lines / measure_radial_velocity /
find_period / classify_variable_star / fit_sed / analyze_kinematics / analyze_abundance_pattern / plan_observation
- batch_process：批量样本"查询→下载→分析→报告"流水线，并发控制防数据源速率限制
- literature_monitor：按 ADS 查询式/时间窗/最低引用数检查最新文献
定时文献同步:
- sync_queries 表新增 is_scheduled 列（migration 20260713）
- 新增 POST /sync/queries/:id/schedule 端点
- 服务启动时拉起每小时调度器，对 is_scheduled=1 的检索配置静默执行 ADS（entdate 增量）/arXiv 增量同步
- search_history 工具收敛至 services/search::search_agent_history，消除 FTS 查询逻辑重复
其他:
- plotting skill 由占位填充为完整科研绘图规范：光谱/光变/折叠曲线/CMD/SED/[α/Fe]/周期图/Mollweide/发现图 9 类 matplotlib 模板
- 删除死代码 streaming_executor.rs（929 行，仅剩 mod 声明引用，无调用方）
- 新增 docs/roadmap-research-features.md 科研功能路线图及实现状态
This commit is contained in:
@@ -0,0 +1,378 @@
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// src/services/observation/cutout.rs
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//
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// 图像 Cutout 服务 —— SDSS / DSS / Pan-STARRS cutout API
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//
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// 支持：
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// - SDSS SkyServer cutout（光学 2.5m）
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// - STScI DSS（Digitized Sky Survey，多种底片）
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// - Pan-STARRS cutout（光学 1.8m）
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use anyhow::{anyhow, Result};
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use serde::{Deserialize, Serialize};
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use tracing::info;
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/// Cutout 数据源
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#[derive(Debug, Clone, Copy, Serialize, Deserialize, PartialEq, Eq)]
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pub enum CutoutSource {
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/// SDSS optical
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Sdss,
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/// DSS (POSS-I, POSS-II, etc.)
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Dss,
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/// Pan-STARRS DR1
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Panstarrs,
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}
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impl CutoutSource {
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pub fn as_str(&self) -> &'static str {
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match self {
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Self::Sdss => "sdss",
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Self::Dss => "dss",
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Self::Panstarrs => "panstarrs",
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}
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}
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}
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/// Cutout 结果
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct CutoutResult {
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/// 图像数据（JPEG/PNG 字节）
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pub image_bytes: Vec<u8>,
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/// 图像格式
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pub format: String,
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/// 中心坐标
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pub ra: f64,
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pub dec: f64,
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/// cutout 大小（角秒）
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pub size_arcsec: f64,
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/// 数据源
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pub source: String,
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/// 图像宽度（像素）
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pub width: u32,
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/// 图像高度（像素）
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pub height: u32,
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}
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/// SDSS cutout（SkyServer）
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pub async fn sdss_cutout(ra: f64, dec: f64, size_arcsec: f64) -> Result<CutoutResult> {
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let scale = size_arcsec / 14.0; // 14 arcsec/pixel for SDSS
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let width = (size_arcsec / scale) as u32;
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let url = format!(
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"https://skyserver.sdss.org/dr18/SkyServerWS/ImgCutout/getjpeg?ra={}&dec={}&scale={:.4}&width={}&height={}",
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ra, dec, scale, width, width
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);
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info!(
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"[Cutout] SDSS: ra={:.4}, dec={:.4}, size={}\"",
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ra, dec, size_arcsec
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);
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let resp = reqwest::get(&url)
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.await
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.map_err(|e| anyhow!("SDSS cutout 请求失败: {}", e))?;
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if !resp.status().is_success() {
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return Err(anyhow!("SDSS cutout 失败: {}", resp.status()));
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}
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let bytes = resp.bytes().await?.to_vec();
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Ok(CutoutResult {
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image_bytes: bytes,
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format: "jpeg".to_string(),
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ra,
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dec,
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size_arcsec,
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source: "SDSS".to_string(),
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width,
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height: width,
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})
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}
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/// DSS cutout（STScI）
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pub async fn dss_cutout(ra: f64, dec: f64, size_arcsec: f64) -> Result<CutoutResult> {
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let size_deg = size_arcsec / 3600.0;
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let url = format!(
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"https://archive.stsci.edu/cgi-bin/dss_search?faste&ra={}&dec={}&equinox=J2000&epoch=2000&width={}&height={}&nimages=1&format=jpeg",
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ra, dec, size_deg, size_deg
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);
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info!(
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"[Cutout] DSS: ra={:.4}, dec={:.4}, size={}\"",
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ra, dec, size_arcsec
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);
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let resp = reqwest::get(&url)
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.await
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.map_err(|e| anyhow!("DSS cutout 请求失败: {}", e))?;
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if !resp.status().is_success() {
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return Err(anyhow!("DSS cutout 失败: {}", resp.status()));
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}
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let bytes = resp.bytes().await?.to_vec();
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let pixel_size = size_arcsec / 1.0; // ~1 arcsec/pixel for DSS
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let width = (size_arcsec / pixel_size) as u32;
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Ok(CutoutResult {
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image_bytes: bytes,
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format: "jpeg".to_string(),
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ra,
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dec,
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size_arcsec,
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source: "DSS".to_string(),
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width,
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height: width,
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})
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}
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/// Pan-STARRS cutout（via VizieR / PS1 cutout service）
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pub async fn panstarrs_cutout(ra: f64, dec: f64, size_arcsec: f64) -> Result<CutoutResult> {
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let size_deg = size_arcsec / 3600.0;
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// PS1 cutout service
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let url = format!(
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"https://ps1images.stsci.edu/cgi-bin/ps1cutoutservice?ra={}&dec={}&size={}&format=fits&filters=g,r,i,z,y",
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ra, dec, size_deg
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);
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info!(
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"[Cutout] Pan-STARRS: ra={:.4}, dec={:.4}, size={}\"",
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ra, dec, size_arcsec
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);
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let resp = reqwest::get(&url)
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.await
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.map_err(|e| anyhow!("PS1 cutout 请求失败: {}", e))?;
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if !resp.status().is_success() {
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return Err(anyhow!("PS1 cutout 失败: {}", resp.status()));
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}
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let bytes = resp.bytes().await?.to_vec();
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Ok(CutoutResult {
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image_bytes: bytes,
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format: "fits".to_string(),
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ra,
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dec,
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size_arcsec,
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source: "Pan-STARRS".to_string(),
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width: 0,
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height: 0,
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})
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}
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/// 统一 cutout 接口
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pub async fn get_cutout(
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source: CutoutSource,
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ra: f64,
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dec: f64,
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size_arcsec: f64,
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) -> Result<CutoutResult> {
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match source {
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CutoutSource::Sdss => sdss_cutout(ra, dec, size_arcsec).await,
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CutoutSource::Dss => dss_cutout(ra, dec, size_arcsec).await,
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CutoutSource::Panstarrs => panstarrs_cutout(ra, dec, size_arcsec).await,
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}
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}
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/// Finding Chart 生成（基于 cutout + 标注）
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pub async fn generate_finding_chart(
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ra: f64,
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dec: f64,
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size_arcsec: f64,
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source: CutoutSource,
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_label: Option<&str>,
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) -> Result<CutoutResult> {
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let result = get_cutout(source, ra, dec, size_arcsec).await?;
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// 保存到文件
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let ext = match result.format.as_str() {
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"jpeg" => "jpg",
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"fits" => "fits",
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_ => "png",
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};
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let file_name = format!("finding_chart_{:.4}_{:.4}.{}", ra, dec, ext);
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let file_path = format!("finding_charts/{}", file_name);
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let library_dir = std::env::var("LIBRARY_DIR").unwrap_or_else(|_| "library".to_string());
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let full_path = std::path::Path::new(&library_dir).join(&file_path);
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if let Some(parent) = full_path.parent() {
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tokio::fs::create_dir_all(parent).await.ok();
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}
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tokio::fs::write(&full_path, &result.image_bytes).await.ok();
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Ok(result)
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}
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// ═══════════════════════════════════════════════════════════════
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// CutoutFetcher —— ObservationFetcher trait 实现
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// ═══════════════════════════════════════════════════════════════
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use crate::api::AppState;
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use crate::services::observation::cache::{
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cached_files_total_size, fetch_observation_cache, log_write_failure, persist_bytes,
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write_observation_cache,
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};
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use crate::services::observation::fetcher::{Candidate, ObservationFetcher};
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use crate::services::observation::types::{
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Artifact, ObservationProduct, ProductSpec, ProductType, Source,
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};
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use tracing::warn;
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/// 图像 Cutout fetcher（SDSS/DSS/Pan-STARRS）
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///
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/// 这不是一个标准的 ObservationFetcher（cutout 不通过 TAP/VO 检索），
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/// 而是通过 HTTP API 直接获取图像 cutout。
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/// 注册为 (Source::Panstarrs, ProductType::Image) 的 fetcher，
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/// 坐标模式直接构造 cutout URL。
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#[derive(Debug)]
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pub struct CutoutFetcher;
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#[async_trait::async_trait]
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impl ObservationFetcher for CutoutFetcher {
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fn key(&self) -> (Source, ProductType) {
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(Source::Panstarrs, ProductType::Image)
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}
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fn subtypes(&self) -> &'static [&'static str] {
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&["sdss", "dss", "panstarrs"]
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}
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fn suggested_max_radius_deg(&self) -> f64 {
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0.0
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}
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fn hard_max_radius_deg(&self) -> f64 {
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0.0
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}
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fn supports_coordinates(&self) -> bool {
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true
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}
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fn supports_identifiers(&self) -> bool {
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false
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}
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async fn cone_search_raw(
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&self,
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_state: &AppState,
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ra: f64,
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dec: f64,
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_radius_deg: f64,
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_release: Option<&str>,
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_subtype: Option<&str>,
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_version: Option<&str>,
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) -> Result<Vec<Candidate>> {
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// Cutout 不做 cone search，直接返回目标本身
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Ok(vec![Candidate {
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source: Source::Panstarrs,
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source_id: format!("cutout_{:.4}_{:.4}", ra, dec),
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label: format!("Cutout at ({:.4}, {:.4})", ra, dec),
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ra: Some(ra),
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dec: Some(dec),
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distance: Some(0.0),
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raw: None,
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}])
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}
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async fn resolve_identifier(
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&self,
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_identifier: &str,
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_release: Option<&str>,
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_subtype: Option<&str>,
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_version: Option<&str>,
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) -> Result<Candidate> {
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Err(anyhow!("Cutout 不支持标识符模式"))
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}
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async fn fetch(
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&self,
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state: &AppState,
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candidate: &Candidate,
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_release: Option<&str>,
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subtype: Option<&str>,
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_version: Option<&str>,
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force: bool,
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) -> Result<ObservationProduct> {
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let ra = candidate.ra.unwrap_or(0.0);
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let dec = candidate.dec.unwrap_or(0.0);
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let sub = subtype.unwrap_or("sdss");
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let product = ProductSpec::with_subtype(ProductType::Image, sub);
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let cache_key = format!("cutout_{:.4}_{:.4}_{}", ra, dec, sub);
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let source_label = candidate.label.clone();
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// 1) 检查缓存
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if !force {
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if let Some((artifacts, meta)) =
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fetch_observation_cache(&state.db, Source::Panstarrs, &product, &cache_key).await?
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{
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if cached_files_total_size(&state.config.storage.library_dir, &artifacts)
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.await
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.is_some()
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{
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info!("[Cutout] 缓存命中 (key={})", cache_key);
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return Ok(ObservationProduct {
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source: Source::Panstarrs,
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product,
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source_id: cache_key,
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source_label,
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artifacts,
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source_meta: meta,
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});
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}
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warn!("[Cutout] 缓存文件缺失，重新下载 (key={})", cache_key);
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}
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}
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// 2) 真实获取
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let source = match sub {
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"dss" => CutoutSource::Dss,
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"panstarrs" => CutoutSource::Panstarrs,
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_ => CutoutSource::Sdss,
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};
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let result = get_cutout(source, ra, dec, 120.0).await?; // 2 arcmin default
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let ext = match result.format.as_str() {
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"jpeg" => "jpg",
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"fits" => "fits",
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_ => "png",
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};
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let file_name = format!("cutout_{:.4}_{:.4}.{}", ra, dec, ext);
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let file_path = format!("Telescope/cutout/{}/{}", candidate.source_id, file_name);
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persist_bytes(
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&state.config.storage.library_dir,
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&file_path,
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&result.image_bytes,
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)
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.await?;
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let artifacts = vec![Artifact {
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band: None,
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original_name: Some(file_name),
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file_path: file_path.clone(),
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file_url: crate::services::observation::cache::file_url_from_path(&file_path),
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file_format: ext.to_string(),
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size_bytes: result.image_bytes.len(),
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cached: false,
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}];
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// 3) 写入缓存
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if let Err(e) = write_observation_cache(
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&state.db,
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Source::Panstarrs,
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&product,
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&cache_key,
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Some(ra),
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Some(dec),
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&artifacts,
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None,
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)
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.await
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{
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log_write_failure("panstarrs", "image", e);
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}
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Ok(ObservationProduct {
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source: Source::Panstarrs,
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product,
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source_id: cache_key,
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source_label,
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artifacts,
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source_meta: candidate.raw.clone(),
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})
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}
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}
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Reference in New Issue
Block a user