feat(origin): expand scientific chart types

CHANGELOG.md

@@ -8,8 +8,14 @@
 
 ## Unreleased
 
+- Origin 绘图新增面积图、堆叠面积图、极坐标图、饼图和堆叠条形图；堆叠类图型改用 Origin 原生多系列分组与累计机制，跨输入数据也会先校验并对齐横坐标。
+
 - Windows Node 不再错误显示 Origin 运行状态中的中文；本机窗口、zcbot 管理页和用户专业软件任务列表会显示 Node、Adapter 及从本机程序读取的 Origin 软件版本。
 
+- Origin 绘图新增箱线图、直方图、堆叠柱形图、数据驱动尺寸的气泡图和带中心线的置信带图，覆盖重复试验分布、相组成占比、多变量关系及拟合不确定性展示。
+
+- Origin 绘图支持 1–4 个二维面板组成复合图，可在同一面板混合折线、散点、线点、柱形和条形系列，分别使用左右 Y 轴，并为任意系列添加对称 X/Y 误差棒；原有单图请求继续兼容。
+
 - Windows Node 的专业软件适配器现在可作为独立目录更新；后续扩展 Origin 绘图参数时，可只替换适配器并重启本机 Node，无需重装或替换 Node 程序，服务端契约更新也无需重启 zcbot。
 
 - Origin 绘图新增出版排版控制：可指定毫米画布、坐标范围与对数尺度、刻度角度和字号、标题/图例字号、网格，以及每条曲线的颜色、线型、点型和透明度；旧绘图请求继续沿用默认样式。

DESIGN.md

@@ -472,7 +472,9 @@ Node 通过 `Authorization: Bearer` 与 `X-Node-Id` 建立 `/v1/software-nodes/c
 
 第三阶段补齐多输入下载与恢复状态协议：请求使用通用 `inputs[]` 绑定 1–16 个 artifact，并由 `operation.plot.series[]` 以输入 key 引用各自的 X/Y 列；单文件不超过 100 MiB、总量不超过 512 MiB。已有 artifact 可直接提交；普通 task 文件先逐个调用 `register_artifact(path)` 登记稳定身份。Node 以自身 Bearer 身份访问每个任务绑定的只读下载端点，流式写入本 job 的 `input/<key>/<filename>`，同时校验大小与 SHA-256；不暴露工作区路径。Node 会原子读取/补报 `terminal.json`，断线后云端把活动任务标记 `disconnected` 并保留 Node/lease，重连按 job、lease、digest 恢复下载或幂等补报终态，不自动重派。Node UI 的“本机任务”只读取已经 accept 到本机的任务目录，不查询云端未派发 Job；每个任务以原子 `state.json` 持久化 `accepted/downloading_inputs/ready_to_run/software_running/uploading_outputs/succeeded/failed/cancelled` 通用阶段，窗口再与 request、terminal、upload-complete 合并成可恢复视图。
 
-第四阶段落地固定 Origin Worker：Node 仅从管理员安装的固定 Python 运行时启动随程序发布的 `worker.py`，参数只有本机 job 目录；请求不能指定脚本、解释器或文件路径。Worker 使用 `originpro` 生成 OPJU、PNG、SVG、PDF、plot spec 和 provenance，校验产物签名并原子写入终态。`origin.plot@v2` 保持单一外层契约，`series[]` 以 `x/y/z/y_error` 统一表达数据角色，再按 `plot.type` 判别必需角色；当前覆盖折线、散点、线点、柱/条形、分组柱形、Y 误差棒、等高线、三维曲面、三元图和规则网格热图，并以可选的 `canvas`、轴排版、图例、标题和 series style 统一表达出版级尺寸与样式，旧 XY 请求原样兼容。进程内 pipeline 按 job 去重，并脱离单次 WebSocket 的取消令牌运行；连接中断只延迟状态/终态上报。Node 进程若在 Worker 启动后重启，则保守失败而不重复驱动 Origin，避免无法证明的双执行。
+第四阶段落地固定 Origin Worker：Node 仅从管理员安装的固定 Python 运行时启动随程序发布的 `worker.py`，参数只有本机 job 目录；请求不能指定脚本、解释器或文件路径。Worker 使用 `originpro` 生成 OPJU、PNG、SVG、PDF、plot spec 和 provenance，校验产物签名并原子写入终态。`origin.plot@v2` 保持单一外层契约，旧单图 `series[]` 以 `x/y/z/y_error` 统一表达数据角色，再按 `plot.type` 判别必需角色；当前覆盖折线、散点、线点、柱/条形、分组柱形、Y 误差棒、等高线、三维曲面、三元图和规则网格热图，并以可选的 `canvas`、轴排版、图例、标题和 series style 统一表达出版级尺寸与样式。新增复合图不继续枚举 `dual_axis_line` 等组合类型，而使用 `multi_panel` feature：`panels[]` 显式描述 1–4 个二维 panel，每条系列用 `kind` 选择基础二维图型、用 `y_axis` 绑定左右轴，并可提供对称 `x_error/y_error`；`layout` 只允许 1×1、1×2、2×1、2×2 四种受控布局。Worker 使用 Origin 内置 panel 模板及 right-Y 图层，不接受模板名；Origin 不支持同一 3D 图窗多图层，因此 contour、surface、ternary 和 heatmap 不混入本阶段 panel。旧 XY 请求原样兼容。进程内 pipeline 按 job 去重，并脱离单次 WebSocket 的取消令牌运行；连接中断只延迟状态/终态上报。Node 进程若在 Worker 启动后重启，则保守失败而不重复驱动 Origin，避免无法证明的双执行。
+
+科研统计图继续以独立 feature 增量扩展同一契约：`box/histogram` 的系列只绑定原始 Y 列，统计规则由 Origin 固定模板决定；`bubble` 增加正数 `size` 数据角色，由受控 modifier column 驱动符号尺寸；`band` 要求同一输入的 `x/y/lower/upper`，先画上下界并填充到下一曲线，再叠加中心线，Worker 在打开 Origin 前拒绝非有限尺寸、非正尺寸和倒置边界。`stacked_column/stacked_area/stacked_bar` 统一把两条以上 XY 系列复制进内部连续 XYY 工作表，严格校验横坐标相同后建立 plot group，并只执行 Worker 内置的固定累计图层命令；请求不能提供命令、模板或工作表范围。`area/polar/pie` 继续使用固定 Origin 类型 ID。未经过目标 Origin 版本真机验证的统计属性不进入公共 schema，避免暴露看似可配但不能稳定复现的参数。
 
 第五阶段完成输出上传与发布：Node 只按固定 manifest ID 逐项流式 PUT，并携带 Node、lease、request digest 与内容摘要；云端重新绑定任务身份，不信 Node 提供的路径或媒体类型。文件先进入用户根下隐藏暂存区，固定文件名、单文件/总大小和 SHA-256 全部验证后，把 plot spec、provenance 整理进 `.meta/`，再将完整目录原子移动到 `<working_dir>/origin/<job_id>/`。PNG/SVG/PDF/OPJU 等正式输出登记平台 artifact UUID 和 `software_job_id`，`.meta/` 只落真实文件；成功状态返回 task-relative `output_dir`，Agent 以该目录为起点按需搜索。重复 PUT、complete 和重连均按摘要幂等；部分上传不可见，只有完整集合才能发布。Origin 执行槽与上传确认是两个正交状态：本地已有终态且固定 Worker 已退出时即释放软件执行槽，成功但尚无 `upload-complete.json` 的任务继续后台补传；若云端已经是 succeeded，重复 PUT/complete 必须按数据库持久化 manifest 校验并直接确认，不得按新版本目录规则重新发布旧 Job。
 

PROGRESS.md

@@ -22,6 +22,12 @@
 
 ### 2026-08-14
 
+- **08-14 / Unreleased / Origin 常用二维图第三批**：adapter 0.8.0 新增 area、stacked_area、polar、pie、stacked_bar；所有堆叠图将跨输入系列复制到受控连续 XYY 工作表，先校验横坐标完全一致，再建立 plot group、激活目标图层并应用固定累计命令。已安装项目锁定的 Python 3.12 受管 runtime，Origin 2024 / originpro 1.1.15 probe 为 ready；堆叠柱、堆叠面积、极坐标、饼图和堆叠条形图的 OPJU/PNG 真机冒烟及视觉核对通过，其中堆叠柱总高为 15/18/17/22。相关 80 项 unittest 通过，未连接或写入数据库。
+
+- **08-14 / Unreleased / Origin 科研统计图第二批**：adapter 0.7.0 新增 box、histogram、stacked_column、bubble、band 五个 feature；箱线/直方图直接消费原始 Y 列，气泡以正数 size 列驱动符号尺寸，置信带以显式 center/lower/upper 绘制填充边界并拒绝倒置区间。堆叠柱经 Origin 2024 真机检查发现单独设置属性会退化为并排/覆盖，已在 0.8.0 改为原生 XYY 分组累计链路。高级箱线百分位和直方图分箱参数暂沿用 Origin 默认值，待真机验证稳定属性后再开放。
+
+- **08-14 / Unreleased / Origin 二维复合图第一批**：`origin.plot@v2` 新增 adapter 0.6.0 的 `multi_panel` feature，以 1–4 个显式 panel 表达横排、竖排或 2×2 复合图；panel 内每条系列可独立选择 line/scatter/line_scatter/column/bar、左右 Y 轴和对称 X/Y 误差列，并保留标题、图例、轴与系列样式。旧 11 类请求继续走原分支；多面板仅覆盖 Origin 原生支持的二维图层，不伪装支持 3D 多图层。专项 52 项 unittest、Python 编译、Ruff 致命规则、diff 检查与 win-x64 .NET build 通过，未启动 Origin、连接或写入数据库。
+
 - **08-14 / Unreleased / Adapter 目录化更新与契约热加载**：Windows Node 改为从 EXE 同级 `adapters/*/adapter.json` 发现能力，实际版本、Python/EXE 运行类型、入口和契约路径均由 manifest 声明；Host 使用通用 JSON Schema 校验并删除 Origin 专用 C# 校验，软件探测与轴范围、系列角色等语义规则下沉 Worker。Core 契约注册表按文件变化原子热加载，非法中间版本保留上一有效快照，工具 schema、注册默认值和调度查询均动态读取。新增无需编译 Node 的 Origin adapter 独立打包入口；专项 40 项 unittest、Python 编译、Ruff 致命规则、diff 检查、.NET build 与两类实际打包通过，全量 611 项仅 3 个既有数据库集成模块因显式测试库缺少 `users` 表未通过（另跳过 4 项），未连接或写入生产 DB。
 
 - **08-14 / Unreleased / Origin 出版级排版参数**：`origin.plot@v2` 新增可选画布、轴范围/尺度/步长/刻度排版/网格、标题与图例排版，以及逐系列颜色、线型、点型和透明度；PNG 宽度按物理画布与 DPI 计算，旧请求默认行为不变。共享契约、Node 二次校验、固定 Worker 与运行文档已同步，专项 68 项 unittest、Python 编译、Ruff 致命规则、diff 检查与 .NET build 通过；全量 608 项仅 3 个既有数据库集成模块因显式测试库缺少 `users` 表未通过，未连接或写入生产 DB。

RUN.md

@@ -1102,6 +1102,12 @@ install-windows-node.bat
 
 Web 用户登录后，文件栏 Job 中心会聚合本人最近任务。活动任务约 4 秒刷新一次，空闲时降为约 30 秒；停止已派发任务是协作取消，状态先显示“正在停止”，Node 在线时立即接收，断线后在下次连接或心跳时重放。Agent 可调用 `software_capability_list`、`register_artifact`、`software_job_submit`、`software_job_status` 和 `software_job_cancel`。Origin 输入必须是 artifact：已有 UUID 可直接提交，普通 task 文件先逐个用相对路径登记；登记不会发布聊天交付卡片。提交工具接收 `inputs`、`operation`、`outputs`，支持 1–16 个输入、跨输入系列和多个显式输出；`plot.canvas` 可指定毫米画布，轴可指定范围、步长、尺度、刻度角度/字号、标题字号和网格，`legend` 可控制显隐、位置和字号，`series[].style` 可控制颜色、线宽/线型、点型/点大小和透明度。所有排版字段可选，旧请求保持默认样式。任务只创建固定 v2 schema 的持久任务，不会阻塞当前对话等待完成。成功状态提供 `output_dir`，Agent可在该目录内搜索并分析；正式输出的 artifact 带 `software_job_id`，供结果卡和产物详情展示来源。Node 输出上传的逐任务诊断日志位于 `%ProgramData%\Zcbot\WindowsNode\jobs\<job-id>\logs\node-output-upload.log`；日志包含上传阶段、产物文件名、重试次数和 Windows `HRESULT`，单文件达到 1 MiB 后轮转一份 `.1`，不记录 Node Token 或认证请求头。
 
+二维复合图使用 `plot.type=multi_panel`。`layout` 支持 1×1、1×2、2×1 和 2×2，`panels` 数量为 1–4；两个 panel 必须选择横排或竖排，三个和四个 panel 使用 2×2。每个 panel 的 `series[]` 必须显式给出 `kind`（`line/scatter/line_scatter/column/bar`），可用 `y_axis=right` 绑定右 Y 轴，并用 `x_error`、`y_error` 指定对称误差列；panel 可独立设置 `x_axis/y_axis/right_y_axis`、标题、标签和图例。一个请求最多仍为 16 条系列，且每个 panel 至少有一条左轴系列。`share_x/share_y` 会统一各主图层自动缩放后的范围。复合图不接受 Origin 模板名，也不支持把等高线、3D 曲面、三元图或热图混入 panel。
+
+科研统计图使用独立单图 type。`box` 和 `histogram` 的系列填写 `input/y`，直接使用原始观测列并采用 Origin 默认箱线统计与自动分箱；`stacked_column` 至少提供两条同类 `input/x/y` 系列；`bubble` 使用 `input/x/y/size`，每行 size 必须是有限正数；`band` 使用 `input/x/y/lower/upper`，其中 y 是中心线且每行 lower 不得大于 upper。当前 schema 不开放自定义箱线百分位、直方图分箱和分布拟合参数，也不允许把这五类统计图作为 `multi_panel.series[].kind`；在目标 Origin 版本完成真机验证后再增量开放。
+
+常用二维扩展单图 type 包括 `area`、`polar`、`pie`，均使用 `input/x/y`；其中 polar 的 X 是角度（度）、Y 是半径，pie 的 X 是扇区标签、Y 是数值，两者使用 Origin 原生坐标/标签系统且不接受笛卡尔 `x_axis/y_axis/z_axis` 参数。`stacked_area`、`stacked_bar` 与 `stacked_column` 一样至少提供两条 `input/x/y`。堆叠系列可以来自不同输入，但行数和逐行 X 值必须完全一致，否则 Worker 在启动绘图前以 `STACKED_PLOT_X_VALUES_MISMATCH` 拒绝，避免错位累计。统计图与这些扩展图暂不混入 `multi_panel.series[].kind`。
+
 专业软件契约位于 `software-contracts/*.json`。zcbot 会在文件变化后校验并热加载完整契约快照，正常修改契约不需要重启服务；非法或尚未写完的文件不会替换上一份有效快照。Node Host 从 EXE 同级的 `adapters/*/adapter.json` 发现本机能力，通用校验只读取 manifest 指向的 JSON Schema；Worker 可以是受管 Python 脚本或独立 EXE。
 
 两个 JSON 的职责不同：`adapter.json` 只描述本机如何启动（实际版本、runtime、入口和契约文件名），`origin.plot.v2.json` 描述云端与本机共同遵守的业务请求/输出契约。前者不能替代后者；独立打包脚本只是把根目录的同一份业务契约复制进 adapter 交付目录，不维护第二份源码。

software-contracts/origin.plot.v2.json

@@ -65,7 +65,18 @@
     "contour": "0.5.0",
     "surface_3d": "0.5.0",
     "ternary": "0.5.0",
-    "heatmap": "0.5.0"
+    "heatmap": "0.5.0",
+    "multi_panel": "0.6.0",
+    "box": "0.7.0",
+    "histogram": "0.7.0",
+    "stacked_column": "0.7.0",
+    "bubble": "0.7.0",
+    "band": "0.7.0",
+    "area": "0.8.0",
+    "stacked_area": "0.8.0",
+    "polar": "0.8.0",
+    "pie": "0.8.0",
+    "stacked_bar": "0.8.0"
   },
   "summary": {
     "title_path": ["operation", "plot", "title"]
@@ -112,14 +123,16 @@
         "properties": {
           "plot": {
             "type": "object",
-            "required": ["type", "series"],
+            "required": ["type"],
             "additionalProperties": false,
             "properties": {
               "type": {
                 "enum": [
                   "line", "scatter", "line_scatter", "column", "bar",
                   "grouped_column", "y_error", "contour", "surface_3d",
-                  "ternary", "heatmap"
+                  "ternary", "heatmap", "multi_panel", "box", "histogram",
+                  "stacked_column", "bubble", "band", "area",
+                  "stacked_area", "polar", "pie", "stacked_bar"
                 ]
               },
               "series": {
@@ -136,12 +149,32 @@
                     "x": {"type": "string", "minLength": 1, "maxLength": 128},
                     "y": {"type": "string", "minLength": 1, "maxLength": 128},
                     "z": {"type": "string", "minLength": 1, "maxLength": 128},
+                    "size": {"type": "string", "minLength": 1, "maxLength": 128},
+                    "lower": {"type": "string", "minLength": 1, "maxLength": 128},
+                    "upper": {"type": "string", "minLength": 1, "maxLength": 128},
                     "y_error": {"type": "string", "minLength": 1, "maxLength": 128},
                     "label": {"type": "string", "minLength": 1, "maxLength": 200},
                     "style": {"$ref": "#/$defs/series_style"}
                   }
                 }
               },
+              "layout": {
+                "type": "object",
+                "required": ["rows", "columns"],
+                "additionalProperties": false,
+                "properties": {
+                  "rows": {"type": "integer", "minimum": 1, "maximum": 2},
+                  "columns": {"type": "integer", "minimum": 1, "maximum": 2},
+                  "share_x": {"type": "boolean"},
+                  "share_y": {"type": "boolean"}
+                }
+              },
+              "panels": {
+                "type": "array",
+                "minItems": 1,
+                "maxItems": 4,
+                "items": {"$ref": "#/$defs/panel"}
+              },
               "template": {"const": "publication_double_column"},
               "title": {"type": "string", "maxLength": 500},
               "title_style": {"$ref": "#/$defs/text_style"},
@@ -171,6 +204,22 @@
               "error_bars": {"type": "null"}
             },
             "allOf": [
+              {
+                "if": {"properties": {"type": {"const": "multi_panel"}}},
+                "then": {
+                  "required": ["layout", "panels"],
+                  "not": {"required": ["series"]}
+                },
+                "else": {
+                  "required": ["series"],
+                  "not": {
+                    "anyOf": [
+                      {"required": ["layout"]},
+                      {"required": ["panels"]}
+                    ]
+                  }
+                }
+              },
               {
                 "if": {"properties": {"type": {"enum": ["contour", "surface_3d", "ternary", "heatmap"]}}},
                 "then": {
@@ -179,7 +228,10 @@
                       "maxItems": 1,
                       "items": {
                         "required": ["input", "x", "y", "z"],
-                        "not": {"required": ["y_error"]}
+                        "not": {"anyOf": [
+                          {"required": ["y_error"]}, {"required": ["size"]},
+                          {"required": ["lower"]}, {"required": ["upper"]}
+                        ]}
                       }
                     }
                   }
@@ -192,7 +244,10 @@
                     "series": {
                       "items": {
                         "required": ["input", "x", "y", "y_error"],
-                        "not": {"required": ["z"]}
+                        "not": {"anyOf": [
+                          {"required": ["z"]}, {"required": ["size"]},
+                          {"required": ["lower"]}, {"required": ["upper"]}
+                        ]}
                       }
                     }
                   }
@@ -206,24 +261,114 @@
                       "minItems": 2,
                       "items": {
                         "required": ["input", "x", "y"],
-                        "not": {"anyOf": [{"required": ["z"]}, {"required": ["y_error"]}]}
+                        "not": {"anyOf": [
+                          {"required": ["z"]}, {"required": ["y_error"]},
+                          {"required": ["size"]}, {"required": ["lower"]},
+                          {"required": ["upper"]}
+                        ]}
                       }
                     }
                   }
                 }
               },
               {
-                "if": {"properties": {"type": {"enum": ["line", "scatter", "line_scatter", "column", "bar"]}}},
+                "if": {"properties": {"type": {"enum": [
+                  "line", "scatter", "line_scatter", "column", "bar",
+                  "area", "polar", "pie"
+                ]}}},
                 "then": {
                   "properties": {
                     "series": {
                       "items": {
                         "required": ["input", "x", "y"],
-                        "not": {"anyOf": [{"required": ["z"]}, {"required": ["y_error"]}]}
+                        "not": {"anyOf": [
+                          {"required": ["z"]}, {"required": ["y_error"]},
+                          {"required": ["size"]}, {"required": ["lower"]},
+                          {"required": ["upper"]}
+                        ]}
                       }
                     }
                   }
                 }
+              },
+              {
+                "if": {"properties": {"type": {"enum": ["box", "histogram"]}}},
+                "then": {
+                  "properties": {
+                    "series": {
+                      "items": {
+                        "required": ["input", "y"],
+                        "not": {"anyOf": [
+                          {"required": ["x"]}, {"required": ["z"]},
+                          {"required": ["y_error"]}, {"required": ["size"]},
+                          {"required": ["lower"]}, {"required": ["upper"]}
+                        ]}
+                      }
+                    }
+                  }
+                }
+              },
+              {
+                "if": {"properties": {"type": {"enum": [
+                  "stacked_column", "stacked_area", "stacked_bar"
+                ]}}},
+                "then": {
+                  "properties": {
+                    "series": {
+                      "minItems": 2,
+                      "items": {
+                        "required": ["input", "x", "y"],
+                        "not": {"anyOf": [
+                          {"required": ["z"]}, {"required": ["y_error"]},
+                          {"required": ["size"]}, {"required": ["lower"]},
+                          {"required": ["upper"]}
+                        ]}
+                      }
+                    }
+                  }
+                }
+              },
+              {
+                "if": {"properties": {"type": {"const": "bubble"}}},
+                "then": {
+                  "properties": {
+                    "series": {
+                      "items": {
+                        "required": ["input", "x", "y", "size"],
+                        "not": {"anyOf": [
+                          {"required": ["z"]}, {"required": ["y_error"]},
+                          {"required": ["lower"]}, {"required": ["upper"]}
+                        ]}
+                      }
+                    }
+                  }
+                }
+              },
+              {
+                "if": {"properties": {"type": {"const": "band"}}},
+                "then": {
+                  "properties": {
+                    "series": {
+                      "items": {
+                        "required": ["input", "x", "y", "lower", "upper"],
+                        "not": {"anyOf": [
+                          {"required": ["z"]}, {"required": ["y_error"]},
+                          {"required": ["size"]}
+                        ]}
+                      }
+                    }
+                  }
+                }
+              },
+              {
+                "if": {"properties": {"type": {"enum": ["polar", "pie"]}}},
+                "then": {
+                  "not": {"anyOf": [
+                    {"required": ["x_axis"]},
+                    {"required": ["y_axis"]},
+                    {"required": ["z_axis"]}
+                  ]}
+                }
               }
             ]
           }
@@ -321,6 +466,54 @@
           "symbol_size": {"type": "number", "minimum": 1, "maximum": 100},
           "transparency": {"type": "integer", "minimum": 0, "maximum": 100}
         }
+      },
+      "panel_series": {
+        "type": "object",
+        "required": ["input", "x", "y", "kind"],
+        "additionalProperties": false,
+        "properties": {
+          "input": {"type": "string", "pattern": "^[a-z][a-z0-9_]{0,31}$"},
+          "x": {"type": "string", "minLength": 1, "maxLength": 128},
+          "y": {"type": "string", "minLength": 1, "maxLength": 128},
+          "x_error": {"type": "string", "minLength": 1, "maxLength": 128},
+          "y_error": {"type": "string", "minLength": 1, "maxLength": 128},
+          "kind": {"enum": ["line", "scatter", "line_scatter", "column", "bar"]},
+          "y_axis": {"enum": ["left", "right"]},
+          "label": {"type": "string", "minLength": 1, "maxLength": 200},
+          "style": {"$ref": "#/$defs/series_style"}
+        }
+      },
+      "panel": {
+        "type": "object",
+        "required": ["key", "series"],
+        "additionalProperties": false,
+        "properties": {
+          "key": {"type": "string", "pattern": "^[a-z][a-z0-9_]{0,31}$"},
+          "series": {
+            "type": "array",
+            "minItems": 1,
+            "maxItems": 16,
+            "uniqueItems": true,
+            "items": {"$ref": "#/$defs/panel_series"}
+          },
+          "panel_label": {"type": "string", "minLength": 1, "maxLength": 20},
+          "title": {"type": "string", "maxLength": 500},
+          "title_style": {"$ref": "#/$defs/text_style"},
+          "x_axis": {"$ref": "#/$defs/axis"},
+          "y_axis": {"$ref": "#/$defs/axis"},
+          "right_y_axis": {"$ref": "#/$defs/axis"},
+          "legend": {
+            "type": "object",
+            "additionalProperties": false,
+            "properties": {
+              "enabled": {"type": "boolean"},
+              "position": {
+                "enum": ["top_left", "top_right", "bottom_left", "bottom_right"]
+              },
+              "font_size": {"type": "number", "minimum": 6, "maximum": 72}
+            }
+          }
+        }
       }
     }
   }

tests/test_origin_worker.py

@@ -218,20 +218,334 @@ class OriginWorkerUnitTests(unittest.TestCase):
         with self.assertRaisesRegex(ValueError, "INPUT_BINDINGS_MUST_BE_USED_EXACTLY"):
             worker._validate_semantics(request)
 
-    def test_series_support_xyz_and_y_error_roles(self) -> None:
+    def test_multi_panel_semantics_cover_layout_axes_and_total_series(self) -> None:
+        request = {
+            "inputs": [{"key": "sample"}],
+            "operation": {"plot": {
+                "type": "multi_panel",
+                "layout": {"rows": 1, "columns": 2, "share_x": True},
+                "panels": [
+                    {
+                        "key": "strength",
+                        "series": [{
+                            "input": "sample", "x": "age", "y": "strength",
+                            "kind": "scatter", "y_error": "sd",
+                        }],
+                    },
+                    {
+                        "key": "thermal",
+                        "series": [
+                            {
+                                "input": "sample", "x": "temperature", "y": "tg",
+                                "kind": "line",
+                            },
+                            {
+                                "input": "sample", "x": "temperature", "y": "dtg",
+                                "kind": "line", "y_axis": "right",
+                            },
+                        ],
+                        "right_y_axis": {"title": "DTG"},
+                    },
+                ],
+            }},
+            "outputs": [{"key": "figure_png", "format": "png"}],
+        }
+        worker._validate_semantics(request)
+
+        request["operation"]["plot"]["layout"] = {"rows": 1, "columns": 1}
+        with self.assertRaisesRegex(ValueError, "PANEL_LAYOUT_TOO_SMALL"):
+            worker._validate_semantics(request)
+
+        request["operation"]["plot"]["layout"] = {
+            "rows": 1, "columns": 2, "share_x": True,
+        }
+        request["operation"]["plot"]["panels"][0]["x_axis"] = {
+            "scale": "log10", "minimum": 0,
+        }
+        with self.assertRaisesRegex(ValueError, "X_AXIS_LOG_LIMIT_INVALID"):
+            worker._validate_semantics(request)
+
+        request["operation"]["plot"]["panels"][0]["x_axis"] = {"minimum": 1}
+        with self.assertRaisesRegex(ValueError, "SHARED_X_AXIS_CONFIG_MISMATCH"):
+            worker._validate_semantics(request)
+
+    def test_mixed_xy_series_pass_kind_axis_and_error_columns_to_origin(self) -> None:
+        class FakePlot:
+            pass
+
+        class FakeLayer:
+            def __init__(self):
+                self.calls = []
+                self.grouped = False
+
+            def add_plot(self, worksheet, **arguments):
+                self.calls.append((worksheet, arguments))
+                return FakePlot()
+
+            def group(self):
+                self.grouped = True
+
+        layer = FakeLayer()
+        series = [
+            {
+                "input": "sample", "x": "age", "y": "strength",
+                "kind": "scatter", "x_error": "age_sd", "y_error": "strength_sd",
+            },
+            {"input": "sample", "x": "age", "y": "fit", "kind": "line"},
+        ]
+        resolved = [
+            {"input": "sample", "x": 0, "y": 1, "x_error": 2, "y_error": 3},
+            {"input": "sample", "x": 0, "y": 4},
+        ]
+        worker._add_xy_plots(layer, {"sample": "worksheet"}, series, resolved)
+        self.assertEqual(layer.calls, [
+            ("worksheet", {"coly": 1, "colx": 0, "type": "s", "colxerr": 2, "colyerr": 3}),
+            ("worksheet", {"coly": 4, "colx": 0, "type": "l"}),
+        ])
+        self.assertFalse(layer.grouped)
+
+    def test_series_support_xyz_and_error_roles(self) -> None:
         resolved, labels = worker._resolve_series(
-            {"sample": (["x", "y", "z", "sd"], [[0, 1, 2, 0.1]])},
+            {"sample": (["x", "y", "z", "x_sd", "y_sd"], [[0, 1, 2, 0.1, 0.2]])},
             [{
                 "input": "sample", "x": "x", "y": "y", "z": "z",
-                "y_error": "sd", "label": "测量值",
+                "x_error": "x_sd", "y_error": "y_sd", "label": "测量值",
             }],
         )
         self.assertEqual(resolved, [{
             "input": "sample", "label": "测量值", "x": 0, "y": 1,
-            "z": 2, "y_error": 3,
+            "z": 2, "x_error": 3, "y_error": 4,
         }])
         self.assertEqual(labels, {("sample", 1): "测量值"})
 
+    def test_series_support_second_batch_roles(self) -> None:
+        resolved, _ = worker._resolve_series(
+            {
+                "sample": (
+                    ["x", "mean", "size", "lower", "upper"],
+                    [[0, 1, 2, 0.5, 1.5]],
+                )
+            },
+            [{
+                "input": "sample", "x": "x", "y": "mean", "size": "size",
+                "lower": "lower", "upper": "upper",
+            }],
+        )
+        self.assertEqual(resolved, [{
+            "input": "sample", "label": None, "x": 0, "y": 1,
+            "size": 2, "lower": 3, "upper": 4,
+        }])
+
+    def test_second_batch_value_validation_rejects_invalid_data(self) -> None:
+        input_data = {
+            "sample": (["x", "y", "size", "lower", "upper"], [[0, 1, 0, 2, 1]])
+        }
+        resolved = [{
+            "input": "sample", "x": 0, "y": 1, "size": 2, "lower": 3, "upper": 4,
+        }]
+        with self.assertRaisesRegex(ValueError, "SIZE_VALUE_NOT_POSITIVE"):
+            worker._validate_bubble_values(input_data, resolved)
+        with self.assertRaisesRegex(ValueError, "BAND_BOUNDS_INVERTED"):
+            worker._validate_band_values(input_data, resolved)
+
+    def test_band_graph_adds_bounds_fill_and_center_line(self) -> None:
+        class FakePlot:
+            def __init__(self):
+                self.fill = None
+
+            def set_fill_area(self, **arguments):
+                self.fill = arguments
+
+        class FakeLayer:
+            def __init__(self):
+                self.calls = []
+
+            def add_plot(self, worksheet, **arguments):
+                plot = FakePlot()
+                self.calls.append((worksheet, arguments, plot))
+                return plot
+
+        class FakeGraph:
+            def __init__(self):
+                self.layer = FakeLayer()
+
+            def __getitem__(self, index):
+                self.assert_index = index
+                return self.layer
+
+        class FakeOp:
+            def __init__(self):
+                self.graph = FakeGraph()
+
+            def new_graph(self, *, template):
+                self.template = template
+                return self.graph
+
+        op = FakeOp()
+        graph, layer, centers, legend = worker._build_band_graph(
+            op,
+            {"sample": "worksheet"},
+            [{"input": "sample", "x": "x", "y": "mean", "label": "95% CI"}],
+            [{"input": "sample", "x": 0, "y": 1, "lower": 2, "upper": 3}],
+        )
+        self.assertIs(graph, op.graph)
+        self.assertIs(layer, op.graph.layer)
+        self.assertEqual(op.template, "line")
+        self.assertEqual([item[1]["coly"] for item in layer.calls], [3, 2, 1])
+        self.assertEqual(layer.calls[0][2].fill, {"type": 9})
+        self.assertEqual(centers, [layer.calls[2][2]])
+        self.assertEqual(legend, r"\l(3) 95% CI")
+
+    def test_second_batch_plot_ids_and_templates_are_fixed(self) -> None:
+        self.assertEqual(worker.PLOT_CONFIG["box"], ("box", 206))
+        self.assertEqual(worker.PLOT_CONFIG["histogram"], ("hist", 219))
+        self.assertEqual(worker.PLOT_CONFIG["stacked_column"], ("StackColumn", 213))
+        self.assertEqual(worker.PLOT_CONFIG["bubble"], ("scatter", "s"))
+
+    def test_bubble_execution_parameters(self) -> None:
+        class FakeOp:
+            @staticmethod
+            def modi_col(offset):
+                return ("modifier", offset)
+
+        class FakePlot:
+            symbol_size = None
+            symbol_sizefactor = None
+
+        plot = FakePlot()
+        worker._configure_bubble_plot(
+            FakeOp(), plot, {"style": {"symbol_size": 12}}, {"y": 1, "size": 4}
+        )
+        self.assertEqual(plot.symbol_size, ("modifier", 3))
+        self.assertEqual(plot.symbol_sizefactor, 12)
+
+    def test_stacked_graph_uses_one_native_xyy_range(self) -> None:
+        class FakeSheet:
+            def __init__(self):
+                self.columns = []
+
+            def from_list(self, index, values, *, lname):
+                self.columns.append((index, values, lname))
+
+            @staticmethod
+            def lt_range(_use_name):
+                return "[Book1]1"
+
+        class FakeLayer:
+            def __init__(self):
+                self.calls = []
+                self.obj = self
+
+            def add_plot(self, data_range, *, type):
+                self.calls.append((data_range, type))
+
+            def activate(self):
+                self.activated = True
+
+            def group(self, enabled, begin, end):
+                self.group_call = (enabled, begin, end)
+
+            def LT_execute(self, command):
+                self.command = command
+
+            @staticmethod
+            def plot_list():
+                return ["a", "b"]
+
+        class FakeGraph:
+            def __init__(self):
+                self.layer = FakeLayer()
+
+            def __getitem__(self, index):
+                self.index = index
+                return self.layer
+
+        class FakeOp:
+            def __init__(self):
+                self.sheet = FakeSheet()
+                self.graph = FakeGraph()
+
+            def new_sheet(self, kind, *, lname):
+                self.sheet_call = (kind, lname)
+                return self.sheet
+
+            def new_graph(self, *, template):
+                self.template = template
+                return self.graph
+
+        op = FakeOp()
+        graph, layer, plots = worker._build_stacked_graph(
+            op,
+            {"sample": (["x", "a", "b"], [[1, 10, 5], [2, 12, 6]])},
+            [
+                {"input": "sample", "x": "x", "y": "a", "label": "A"},
+                {"input": "sample", "x": "x", "y": "b", "label": "B"},
+            ],
+            [
+                {"input": "sample", "x": 0, "y": 1},
+                {"input": "sample", "x": 0, "y": 2},
+            ],
+            "StackColumn",
+            213,
+        )
+        self.assertIs(graph, op.graph)
+        self.assertIs(layer, op.graph.layer)
+        self.assertEqual(plots, ["a", "b"])
+        self.assertEqual(op.template, "StackColumn")
+        self.assertEqual(layer.calls, [("[Book1]1!(1,2:3)", 213)])
+        self.assertEqual(layer.group_call, (True, 0, 1))
+        self.assertTrue(layer.activated)
+        self.assertEqual(layer.command, "layer -b s 1")
+        self.assertEqual(op.sheet.columns[1:], [
+            (1, [10, 12], "A"), (2, [5, 6], "B"),
+        ])
+
+    def test_stacked_graph_rejects_mismatched_x_values(self) -> None:
+        with self.assertRaisesRegex(ValueError, "STACKED_PLOT_X_VALUES_MISMATCH"):
+            worker._build_stacked_graph(
+                object(),
+                {
+                    "a": (["x", "y"], [[1, 10], [2, 12]]),
+                    "b": (["x", "y"], [[1, 5], [3, 6]]),
+                },
+                [
+                    {"input": "a", "x": "x", "y": "y"},
+                    {"input": "b", "x": "x", "y": "y"},
+                ],
+                [
+                    {"input": "a", "x": 0, "y": 1},
+                    {"input": "b", "x": 0, "y": 1},
+                ],
+                "StackColumn",
+                213,
+            )
+
+    def test_third_batch_plot_ids_and_templates_are_fixed(self) -> None:
+        self.assertEqual(worker.PLOT_CONFIG["area"], ("area", 204))
+        self.assertEqual(worker.PLOT_CONFIG["stacked_area"], ("stackarea", 214))
+        self.assertEqual(worker.PLOT_CONFIG["polar"], ("polar", 192))
+        self.assertEqual(worker.PLOT_CONFIG["pie"], ("pie", 225))
+        self.assertEqual(worker.PLOT_CONFIG["stacked_bar"], ("bar", 216))
+
+    def test_stacked_legend_only_contains_requested_series(self) -> None:
+        class Label:
+            text = ""
+
+        class Layer:
+            legend = Label()
+
+            def label(self, name):
+                self.name = name
+                return self.legend
+
+        layer = Layer()
+        worker._replace_series_legend(layer, [
+            {"y": "a", "label": "Phase A"},
+            {"y": "phase_b"},
+        ])
+        self.assertEqual(layer.name, "Legend")
+        self.assertEqual(layer.legend.text, r"\l(1) Phase A" "\n" r"\l(2) phase_b")
+
     def test_heatmap_matrix_accepts_complete_unordered_grid(self) -> None:
         matrix, xy_map = worker._heatmap_matrix(
             [[1, 20, 4], [0, 10, 1], [1, 10, 2], [0, 20, 3]],

tests/test_software_contracts.py

@@ -7,8 +7,8 @@ from pathlib import Path
 from shutil import copy2
 
 from core.software_contracts import (
-    DEFAULT_CAPABILITIES,
     CONTRACT_ROOT,
+    DEFAULT_CAPABILITIES,
     _ContractRegistry,
     get_contract,
     node_supports_request,
@@ -66,6 +66,52 @@ class SoftwareContractTests(unittest.TestCase):
         self.assertTrue(node_supports_request(contract, _request("heatmap"), current_runtime))
         self.assertFalse(node_supports_request(contract, _request("bar"), current_runtime))
 
+        multi_panel = _request("line")
+        multi_panel["operation"]["plot"] = {
+            "type": "multi_panel",
+            "layout": {"rows": 1, "columns": 1},
+            "panels": [{
+                "key": "main",
+                "series": [{
+                    "input": "sample", "x": "x", "y": "y", "kind": "line",
+                }],
+            }],
+        }
+        normalized, _ = contract.normalize_request(multi_panel)
+        self.assertEqual(normalized, multi_panel)
+        current_runtime["capability_runtime"]["origin.plot@v2"].update({
+            "adapter_version": "0.6.0",
+            "features": ["multi_panel"],
+        })
+        self.assertTrue(node_supports_request(contract, multi_panel, current_runtime))
+
+        bubble = _request("line")
+        bubble["operation"]["plot"] = {
+            "type": "bubble",
+            "series": [{
+                "input": "sample", "x": "x", "y": "y", "size": "particle_size",
+            }],
+        }
+        normalized, _ = contract.normalize_request(bubble)
+        self.assertEqual(normalized, bubble)
+        self.assertFalse(node_supports_request(contract, bubble, current_runtime))
+        current_runtime["capability_runtime"]["origin.plot@v2"].update({
+            "adapter_version": "0.7.0",
+            "features": ["bubble"],
+        })
+        self.assertTrue(node_supports_request(contract, bubble, current_runtime))
+
+        area = _request("line")
+        area["operation"]["plot"]["type"] = "area"
+        normalized, _ = contract.normalize_request(area)
+        self.assertEqual(normalized, area)
+        self.assertFalse(node_supports_request(contract, area, current_runtime))
+        current_runtime["capability_runtime"]["origin.plot@v2"].update({
+            "adapter_version": "0.8.0",
+            "features": ["area"],
+        })
+        self.assertTrue(node_supports_request(contract, area, current_runtime))
+
     def test_semantic_version_comparison_is_numeric(self) -> None:
         self.assertTrue(version_at_least("0.10.0", "0.4.0"))
         self.assertFalse(version_at_least("0.3.9", "0.4.0"))

tests/test_software_nodes.py

@@ -404,6 +404,31 @@ class SoftwareJobProtocolTests(unittest.TestCase):
             "surface_3d": [{"input": "sample", "x": "x", "y": "y", "z": "value"}],
             "ternary": [{"input": "sample", "x": "a", "y": "b", "z": "c"}],
             "heatmap": [{"input": "sample", "x": "x", "y": "y", "z": "value"}],
+            "box": [{"input": "sample", "y": "strength"}],
+            "histogram": [{"input": "sample", "y": "particle_size"}],
+            "stacked_column": [
+                {"input": "sample", "x": "sample_name", "y": "phase_a"},
+                {"input": "sample", "x": "sample_name", "y": "phase_b"},
+            ],
+            "bubble": [{
+                "input": "sample", "x": "temperature", "y": "strength",
+                "size": "particle_size",
+            }],
+            "band": [{
+                "input": "sample", "x": "age", "y": "mean",
+                "lower": "ci_lower", "upper": "ci_upper",
+            }],
+            "area": [{"input": "sample", "x": "age", "y": "strength"}],
+            "stacked_area": [
+                {"input": "sample", "x": "age", "y": "phase_a"},
+                {"input": "sample", "x": "age", "y": "phase_b"},
+            ],
+            "polar": [{"input": "sample", "x": "angle", "y": "intensity"}],
+            "pie": [{"input": "sample", "x": "phase", "y": "fraction"}],
+            "stacked_bar": [
+                {"input": "sample", "x": "sample_name", "y": "phase_a"},
+                {"input": "sample", "x": "sample_name", "y": "phase_b"},
+            ],
         }
         for plot_type, series in cases.items():
             request = {
@@ -417,6 +442,55 @@ class SoftwareJobProtocolTests(unittest.TestCase):
                 self.assertEqual(normalized, request)
                 self.assertEqual(len(digest), 64)
 
+    def test_origin_request_accepts_multi_panel_mixed_series_and_dual_y(self) -> None:
+        request = {
+            "schema_version": 2,
+            "inputs": [{"key": "sample", "artifact_id": str(uuid4())}],
+            "operation": {"plot": {
+                "type": "multi_panel",
+                "layout": {"rows": 1, "columns": 2, "share_x": False},
+                "canvas": {"width_mm": 180, "height_mm": 90},
+                "panels": [
+                    {
+                        "key": "mechanical",
+                        "panel_label": "(a)",
+                        "title": "Mechanical properties",
+                        "series": [
+                            {
+                                "input": "sample", "x": "age", "y": "strength",
+                                "kind": "column", "y_error": "strength_sd",
+                            },
+                            {
+                                "input": "sample", "x": "age", "y": "modulus",
+                                "kind": "line_scatter", "y_axis": "right",
+                            },
+                        ],
+                        "x_axis": {"title": "Age", "unit": "d"},
+                        "y_axis": {"title": "Strength", "unit": "MPa"},
+                        "right_y_axis": {"title": "Modulus", "unit": "GPa"},
+                    },
+                    {
+                        "key": "fit",
+                        "panel_label": "(b)",
+                        "series": [
+                            {
+                                "input": "sample", "x": "measured", "y": "predicted",
+                                "kind": "scatter", "x_error": "measured_sd",
+                            },
+                            {
+                                "input": "sample", "x": "measured", "y": "reference",
+                                "kind": "line",
+                            },
+                        ],
+                    },
+                ],
+            }},
+            "outputs": [{"key": "figure_svg", "type": "figure", "format": "svg"}],
+        }
+        normalized, digest = _canonical_request("origin.plot@v2", request)
+        self.assertEqual(normalized, request)
+        self.assertEqual(len(digest), 64)
+
     def test_origin_request_rejects_roles_that_do_not_match_plot_type(self) -> None:
         base = {
             "schema_version": 2,
@@ -425,9 +499,18 @@ class SoftwareJobProtocolTests(unittest.TestCase):
         }
         invalid_plots = (
             {"type": "line", "series": [{"input": "sample", "x": "x", "y": "y", "z": "z"}]},
+            {"type": "line", "series": [{
+                "input": "sample", "x": "x", "y": "y", "size": "size",
+            }]},
             {"type": "y_error", "series": [{"input": "sample", "x": "x", "y": "y"}]},
             {"type": "contour", "series": [{"input": "sample", "x": "x", "y": "y"}]},
             {"type": "grouped_column", "series": [{"input": "sample", "x": "x", "y": "y"}]},
+            {"type": "box", "series": [{"input": "sample", "x": "x", "y": "y"}]},
+            {"type": "stacked_column", "series": [{"input": "sample", "x": "x", "y": "y"}]},
+            {"type": "bubble", "series": [{"input": "sample", "x": "x", "y": "y"}]},
+            {"type": "band", "series": [{"input": "sample", "x": "x", "y": "y"}]},
+            {"type": "stacked_area", "series": [{"input": "sample", "x": "x", "y": "y"}]},
+            {"type": "polar", "series": [{"input": "sample", "x": "x", "y": "y"}], "x_axis": {"title": "Angle"}},
         )
         for plot in invalid_plots:
             with self.subTest(plot_type=plot["type"]), self.assertRaises(SoftwareJobError):

windows-node/README.md

@@ -12,7 +12,7 @@ windows-node\package-windows-node.bat
 
 产物位于 `windows-node\dist\zcbot-windows-node-<version>-win-x64.zip`，旁边同时生成 SHA-256 文件。默认不包含 .NET Runtime，目标机器需预装 .NET 10 Desktop Runtime；需要免安装 .NET 的离线包时执行 `package-windows-node.bat --self-contained`。打包脚本是纯 BAT，使用 .NET SDK 以及 Windows 自带的 `tar.exe`、`certutil.exe`。
 
-固定 Origin Worker 通过统一的 `origin.plot@v2` / `series[]` 数据角色模型支持 `line`、`scatter`、`line_scatter`、`column`、`bar`、`grouped_column`、`y_error`、`contour`、`surface_3d`、`ternary` 和 `heatmap`，并支持毫米画布、轴范围/尺度/刻度排版、标题、图例及逐系列样式，生成 OPJU、PNG、SVG、PDF、plot spec、provenance 与原子 `terminal.json`。热图输入必须是完整、等间距且坐标不重复的规则 XYZ 网格。运行时独立于 zcbot 服务端 Python。发布目录包含统一安装入口；使用实际运行 Node 的专用 Windows 账号直接双击：
+固定 Origin Worker 通过统一的 `origin.plot@v2` / `series[]` 数据角色模型支持 `line`、`scatter`、`line_scatter`、`column`、`bar`、`grouped_column`、`y_error`、`contour`、`surface_3d`、`ternary` 和 `heatmap`，并支持毫米画布、轴范围/尺度/刻度排版、标题、图例及逐系列样式。adapter 0.6.0 提供 `multi_panel`：可组成 1–4 个二维 panel，在每个 panel 混合基础二维系列、绑定左右 Y 轴并添加对称 X/Y 误差列；adapter 0.7.0 增加 `box`、`histogram`、`stacked_column`、`bubble` 和 `band`，adapter 0.8.0 再增加 `area`、`stacked_area`、`polar`、`pie` 和 `stacked_bar`。Worker 生成 OPJU、PNG、SVG、PDF、plot spec、provenance 与原子 `terminal.json`。热图输入必须是完整、等间距且坐标不重复的规则 XYZ 网格；所有堆叠系列必须逐行共享相同 X 值。运行时独立于 zcbot 服务端 Python。发布目录包含统一安装入口；使用实际运行 Node 的专用 Windows 账号直接双击：
 
 日常只更新 adapter 时运行 `package-origin-adapter.bat`，无需编译 Node。退出托盘 Node 后，整体替换安装目录中的 `adapters\origin.plot@v2\` 再启动即可；不要在任务执行期间覆盖文件。只有依赖清单变化才需要重新运行统一安装器。
 

windows-node/adapters/origin.plot@v2/adapter.json

@@ -1,6 +1,6 @@
 {
   "capability": "origin.plot@v2",
-  "adapter_version": "0.5.0",
+  "adapter_version": "0.8.0",
   "runtime": "python",
   "runtime_id": "origin",
   "entrypoint": "worker.py",

windows-node/origin-worker/worker.py

@@ -15,6 +15,7 @@ import re
 import sys
 from datetime import datetime, timezone
 from importlib.metadata import PackageNotFoundError, version
+from itertools import pairwise
 from pathlib import Path
 from typing import Any
 
@@ -29,8 +30,25 @@ PLOT_CONFIG = {
     "contour": ("TriContour", 243),
     "surface_3d": ("glCMAP", 103),
     "ternary": ("ternary", 245),
+    "box": ("box", 206),
+    "histogram": ("hist", 219),
+    "stacked_column": ("StackColumn", 213),
+    "bubble": ("scatter", "s"),
+    "band": ("line", "l"),
+    "area": ("area", 204),
+    "stacked_area": ("stackarea", 214),
+    "polar": ("polar", 192),
+    "pie": ("pie", 225),
+    "stacked_bar": ("bar", 216),
 }
+STACKED_PLOT_TYPES = {"stacked_column", "stacked_area", "stacked_bar"}
+_CUMULATIVE_STACK_COMMAND = "layer -b s 1"
 XYZ_PLOT_TYPES = {"contour", "surface_3d", "ternary", "heatmap"}
+PANEL_TEMPLATES = {
+    (1, 2): "PAN2HORZ",
+    (2, 1): "PAN2VERT",
+    (2, 2): "PAN4",
+}
 FORMATS = {"opju", "png", "svg", "pdf"}
 LINE_STYLES = {
     "solid": 1,
@@ -53,7 +71,7 @@ LEGEND_POSITIONS = {
     "bottom_left": (700, 7200),
     "bottom_right": (6800, 7200),
 }
-ADAPTER_VERSION = "0.5.0"
+ADAPTER_VERSION = "0.8.0"
 
 
 def _server_executable(command: str) -> Path:
@@ -183,6 +201,7 @@ def _probe() -> int:
         if sys.platform != "win32":
             raise RuntimeError("Origin adapter requires Windows")
         import winreg
+
         import originpro
 
         with winreg.OpenKey(winreg.HKEY_CLASSES_ROOT, r"Origin.ApplicationSI\CLSID"):
@@ -208,32 +227,72 @@ def _validate_semantics(request: dict[str, Any]) -> None:
     input_keys = {item["key"] for item in request["inputs"]}
     plot = request["operation"]["plot"]
     plot_type = plot["type"]
-    series = plot["series"]
+    if plot_type == "multi_panel":
+        panels = plot["panels"]
+        layout = plot["layout"]
+        grid = (layout["rows"], layout["columns"])
+        valid_grids = {
+            1: {(1, 1)},
+            2: {(1, 2), (2, 1)},
+            3: {(2, 2)},
+            4: {(2, 2)},
+        }
+        if grid not in valid_grids[len(panels)]:
+            raise ValueError("PANEL_LAYOUT_TOO_SMALL")
+        panel_keys = [panel["key"] for panel in panels]
+        if len(set(panel_keys)) != len(panel_keys):
+            raise ValueError("PANEL_KEYS_MUST_BE_UNIQUE")
+        series = [item for panel in panels for item in panel["series"]]
+        if len(series) > 16:
+            raise ValueError("SERIES_COUNT_EXCEEDED")
+        for panel in panels:
+            if not any(item.get("y_axis", "left") == "left" for item in panel["series"]):
+                raise ValueError("PANEL_LEFT_AXIS_REQUIRES_SERIES")
+            for axis_name in ("x_axis", "y_axis", "right_y_axis"):
+                _validate_axis(panel.get(axis_name), axis_name)
+        for axis_name, share_name in (("x_axis", "share_x"), ("y_axis", "share_y")):
+            if layout.get(share_name):
+                settings = [panel.get(axis_name) or {} for panel in panels]
+                if any(value != settings[0] for value in settings[1:]):
+                    raise ValueError(f"SHARED_{axis_name.upper()}_CONFIG_MISMATCH")
+    else:
+        series = plot["series"]
     used_inputs = {item["input"] for item in series}
     if used_inputs != input_keys:
         raise ValueError("INPUT_BINDINGS_MUST_BE_USED_EXACTLY")
+    if plot_type == "multi_panel":
+        return
     if plot_type == "grouped_column" and len(series) < 2:
         raise ValueError("GROUPED_COLUMN_REQUIRES_MULTIPLE_SERIES")
+    if plot_type in STACKED_PLOT_TYPES and len(series) < 2:
+        raise ValueError("STACKED_PLOT_REQUIRES_MULTIPLE_SERIES")
     if plot_type in XYZ_PLOT_TYPES and len(series) != 1:
         raise ValueError("XYZ_PLOT_REQUIRES_ONE_SERIES")
     required_roles = (
         ("x", "y", "z") if plot_type in XYZ_PLOT_TYPES
         else ("x", "y", "y_error") if plot_type == "y_error"
+        else ("y",) if plot_type in {"box", "histogram"}
+        else ("x", "y", "size") if plot_type == "bubble"
+        else ("x", "y", "lower", "upper") if plot_type == "band"
         else ("x", "y")
     )
     for item in series:
         if any(role not in item for role in required_roles):
             raise ValueError("SERIES_REQUIRED_ROLE_MISSING")
     for axis_name in ("x_axis", "y_axis", "z_axis"):
-        axis = plot.get(axis_name) or {}
+        _validate_axis(plot.get(axis_name), axis_name)
-        minimum = axis.get("minimum")
+
-        maximum = axis.get("maximum")
+
-        if minimum is not None and maximum is not None and minimum >= maximum:
+def _validate_axis(value: Any, name: str) -> None:
-            raise ValueError(f"{axis_name.upper()}_LIMITS_INVALID")
+    axis = value if isinstance(value, dict) else {}
-        if axis.get("scale") in {"log10", "ln", "log2"} and (
+    minimum = axis.get("minimum")
-            minimum is not None and minimum <= 0 or maximum is not None and maximum <= 0
+    maximum = axis.get("maximum")
-        ):
+    if minimum is not None and maximum is not None and minimum >= maximum:
-            raise ValueError(f"{axis_name.upper()}_LOG_LIMIT_INVALID")
+        raise ValueError(f"{name.upper()}_LIMITS_INVALID")
+    if axis.get("scale") in {"log10", "ln", "log2"} and (
+        minimum is not None and minimum <= 0 or maximum is not None and maximum <= 0
+    ):
+        raise ValueError(f"{name.upper()}_LOG_LIMIT_INVALID")
 
 
 def _atomic_json(path: Path, value: Any) -> None:
@@ -348,7 +407,7 @@ def _apply_axis(layer: Any, name: str, spec: Any, fallback: str) -> None:
     if "tick_label_font_size" in settings:
         layer.set_float(f"{name}.label.pt", float(settings["tick_label_font_size"]))
     if "title_font_size" in settings:
-        title_object = {"x": "xb", "y": "yl", "z": "zf"}[name]
+        title_object = {"x": "xb", "y": "yl", "y2": "yr", "z": "zf"}[name]
         layer.label(title_object).set_int("fsize", round(settings["title_font_size"]))
     if "grid" in settings:
         grid_value = {"none": 0, "major": 1, "major_minor": 3}[settings["grid"]]
@@ -372,7 +431,7 @@ def _apply_series_style(origin_plot: Any, style: Any) -> None:
         origin_plot.transparency = int(style["transparency"])
 
 
-def _apply_legend(layer: Any, legend: Any) -> None:
+def _apply_legend(layer: Any, legend: Any, vertical_offset: int = 0) -> None:
     if not isinstance(legend, dict):
         return
     label = layer.label("Legend")
@@ -381,8 +440,26 @@ def _apply_legend(layer: Any, legend: Any) -> None:
         label.set_int("fsize", round(legend["font_size"]))
     if "position" in legend:
         left, top = LEGEND_POSITIONS[legend["position"]]
+        if vertical_offset and legend["position"].startswith("bottom"):
+            vertical_offset = -vertical_offset
         label.set_int("left", left)
-        label.set_int("top", top)
+        label.set_int("top", top + vertical_offset)
+
+
+def _replace_series_legend(layer: Any, series_specs: list[dict[str, Any]]) -> None:
+    layer.label("Legend").text = "\n".join(
+        f"\\l({index}) {item.get('label') or item['y']}"
+        for index, item in enumerate(series_specs, start=1)
+    )
+
+
+def _apply_title(layer: Any, value: Any, style: Any, *, top: int = 120) -> None:
+    if not value:
+        return
+    title = layer.add_label(str(value))
+    title.set_int("fsize", round((style or {}).get("font_size", 18)))
+    title.set_int("left", 2200)
+    title.set_int("top", top)
 
 
 def _input_file(job_dir: Path, key: str) -> Path:
@@ -404,7 +481,9 @@ def _resolve_series(
         headers, _ = input_data[input_key]
         role_indexes = {
             role: _column_index(headers, series[role], role)
-            for role in ("x", "y", "z", "y_error") if role in series
+            for role in (
+                "x", "y", "z", "size", "lower", "upper", "x_error", "y_error"
+            ) if role in series
         }
         y_index = role_indexes["y"]
         label = series.get("label")
@@ -429,6 +508,37 @@ def _number(value: Any, role: str) -> float:
     return number
 
 
+def _validate_bubble_values(
+    input_data: dict[str, tuple[list[str], list[list[Any]]]],
+    resolved_series: list[dict[str, Any]],
+) -> None:
+    for resolved in resolved_series:
+        _, rows = input_data[resolved["input"]]
+        for row in rows:
+            try:
+                size = _number(row[resolved["size"]], "size")
+            except IndexError as exc:
+                raise ValueError("BUBBLE_ROW_INCOMPLETE") from exc
+            if size <= 0:
+                raise ValueError("SIZE_VALUE_NOT_POSITIVE")
+
+
+def _validate_band_values(
+    input_data: dict[str, tuple[list[str], list[list[Any]]]],
+    resolved_series: list[dict[str, Any]],
+) -> None:
+    for resolved in resolved_series:
+        _, rows = input_data[resolved["input"]]
+        for row in rows:
+            try:
+                lower = _number(row[resolved["lower"]], "lower")
+                upper = _number(row[resolved["upper"]], "upper")
+            except IndexError as exc:
+                raise ValueError("BAND_ROW_INCOMPLETE") from exc
+            if lower > upper:
+                raise ValueError("BAND_BOUNDS_INVERTED")
+
+
 def _is_evenly_spaced(values: list[float]) -> bool:
     if len(values) <= 2:
         return True
@@ -436,7 +546,7 @@ def _is_evenly_spaced(values: list[float]) -> bool:
     tolerance = max(abs(step) * 1e-9, 1e-12)
     return all(
         math.isclose(current - previous, step, rel_tol=1e-9, abs_tol=tolerance)
-        for previous, current in zip(values[1:-1], values[2:], strict=True)
+        for previous, current in pairwise(values[1:])
     )
 
 
@@ -480,6 +590,199 @@ def _validate_artifact(path: Path, extension: str) -> None:
         raise RuntimeError("OPJU_EXPORT_INVALID")
 
 
+def _add_xy_plots(
+    layer: Any,
+    worksheets: dict[str, Any],
+    series_specs: list[dict[str, Any]],
+    resolved_series: list[dict[str, Any]],
+) -> list[Any]:
+    plots = []
+    for series_spec, resolved in zip(series_specs, resolved_series, strict=True):
+        kind = series_spec["kind"]
+        arguments = {
+            "coly": resolved["y"],
+            "colx": resolved["x"],
+            "type": PLOT_CONFIG[kind][1],
+        }
+        if "x_error" in resolved:
+            arguments["colxerr"] = resolved["x_error"]
+        if "y_error" in resolved:
+            arguments["colyerr"] = resolved["y_error"]
+        plot = layer.add_plot(worksheets[resolved["input"]], **arguments)
+        _apply_series_style(plot, series_spec.get("style"))
+        plots.append(plot)
+    if len(plots) > 1 and all(item["kind"] == "column" for item in series_specs):
+        layer.group()
+    return plots
+
+
+def _configure_bubble_plot(
+    op: Any,
+    origin_plot: Any,
+    series_spec: dict[str, Any],
+    resolved: dict[str, Any],
+) -> None:
+    origin_plot.symbol_size = op.modi_col(resolved["size"] - resolved["y"])
+    origin_plot.symbol_sizefactor = float(
+        (series_spec.get("style") or {}).get("symbol_size", 10)
+    )
+
+
+def _build_stacked_graph(
+    op: Any,
+    input_data: dict[str, tuple[list[str], list[list[Any]]]],
+    series_specs: list[dict[str, Any]],
+    resolved_series: list[dict[str, Any]],
+    template: str,
+    plot_type: int,
+) -> tuple[Any, Any, list[Any]]:
+    first = resolved_series[0]
+    _, first_rows = input_data[first["input"]]
+    x_values = [row[first["x"]] for row in first_rows]
+    y_columns: list[list[Any]] = []
+    for resolved in resolved_series:
+        _, rows = input_data[resolved["input"]]
+        current_x = [row[resolved["x"]] for row in rows]
+        if current_x != x_values:
+            raise ValueError("STACKED_PLOT_X_VALUES_MISMATCH")
+        y_columns.append([row[resolved["y"]] for row in rows])
+
+    staging = op.new_sheet("w", lname="stacked_plot_data")
+    staging.from_list(0, x_values, lname=str(series_specs[0]["x"]))
+    for index, (series_spec, values) in enumerate(
+        zip(series_specs, y_columns, strict=True), start=1
+    ):
+        staging.from_list(
+            index,
+            values,
+            lname=str(series_spec.get("label") or series_spec["y"]),
+        )
+
+    graph = op.new_graph(template=template)
+    layer = graph[0]
+    data_range = f"{staging.lt_range(False)}!(1,2:{len(series_specs) + 1})"
+    layer.add_plot(data_range, type=plot_type)
+    layer.group(True, 0, len(series_specs) - 1)
+    layer.activate()
+    layer.obj.LT_execute(_CUMULATIVE_STACK_COMMAND)
+    return graph, layer, list(layer.plot_list())
+
+
+def _share_axis_limits(layers: list[Any], name: str) -> None:
+    limits = [getattr(layer, f"{name}lim") for layer in layers]
+    begin = min(item[0] for item in limits)
+    end = max(item[1] for item in limits)
+    for layer in layers:
+        getattr(layer, f"set_{name}lim")(begin, end)
+
+
+def _build_multi_panel_graph(
+    op: Any,
+    plot_spec: dict[str, Any],
+    worksheets: dict[str, Any],
+    resolved_series: list[dict[str, Any]],
+) -> Any:
+    panels = plot_spec["panels"]
+    layout = plot_spec["layout"]
+    grid = (layout["rows"], layout["columns"])
+    if len(panels) == 1:
+        template = PLOT_CONFIG[panels[0]["series"][0]["kind"]][0]
+    else:
+        template = PANEL_TEMPLATES[grid]
+    graph = op.new_graph(template=template)
+    primary_layers = list(graph)[:len(panels)]
+    for unused_layer in list(graph)[len(panels):]:
+        unused_layer.show = False
+
+    resolved_offset = 0
+    for index, (panel, layer) in enumerate(zip(panels, primary_layers, strict=True)):
+        panel_series = panel["series"]
+        resolved_panel = resolved_series[
+            resolved_offset:resolved_offset + len(panel_series)
+        ]
+        resolved_offset += len(panel_series)
+        left_pairs = [
+            (spec, resolved)
+            for spec, resolved in zip(panel_series, resolved_panel, strict=True)
+            if spec.get("y_axis", "left") == "left"
+        ]
+        right_pairs = [
+            (spec, resolved)
+            for spec, resolved in zip(panel_series, resolved_panel, strict=True)
+            if spec.get("y_axis", "left") == "right"
+        ]
+        left_specs = [item[0] for item in left_pairs]
+        left_resolved = [item[1] for item in left_pairs]
+        _add_xy_plots(layer, worksheets, left_specs, left_resolved)
+        layer.rescale()
+        _apply_axis(layer, "x", panel.get("x_axis"), str(left_specs[0]["x"]))
+        _apply_axis(layer, "y", panel.get("y_axis"), "Y")
+        legend = {"enabled": True, "position": "top_right", **(panel.get("legend") or {})}
+        _apply_legend(layer, legend)
+        _apply_title(layer, panel.get("title"), panel.get("title_style"))
+        if panel.get("panel_label"):
+            panel_label = layer.add_label(str(panel["panel_label"]))
+            panel_label.set_int("fsize", round((panel.get("title_style") or {}).get("font_size", 12)))
+            panel_label.set_int("left", 120)
+            panel_label.set_int("top", 120)
+
+        if right_pairs:
+            layer.activate()
+            right_layer = graph.add_layer(2)
+            right_specs = [item[0] for item in right_pairs]
+            right_resolved = [item[1] for item in right_pairs]
+            _add_xy_plots(right_layer, worksheets, right_specs, right_resolved)
+            right_layer.rescale()
+            _apply_axis(right_layer, "y2", panel.get("right_y_axis"), "Right Y")
+            _apply_legend(right_layer, legend, vertical_offset=700)
+
+        if index == 0:
+            _apply_title(
+                layer,
+                plot_spec.get("title"),
+                plot_spec.get("title_style"),
+                top=-360,
+            )
+
+    if layout.get("share_x") and len(primary_layers) > 1:
+        _share_axis_limits(primary_layers, "x")
+    if layout.get("share_y") and len(primary_layers) > 1:
+        _share_axis_limits(primary_layers, "y")
+    return graph
+
+
+def _build_band_graph(
+    op: Any,
+    worksheets: dict[str, Any],
+    series_specs: list[dict[str, Any]],
+    resolved_series: list[dict[str, Any]],
+) -> tuple[Any, Any, list[Any], str]:
+    graph = op.new_graph(template="line")
+    layer = graph[0]
+    center_plots = []
+    legend_entries = []
+    for index, (series_spec, resolved) in enumerate(
+        zip(series_specs, resolved_series, strict=True)
+    ):
+        worksheet = worksheets[resolved["input"]]
+        upper_plot = layer.add_plot(
+            worksheet, coly=resolved["upper"], colx=resolved["x"], type="l"
+        )
+        lower_plot = layer.add_plot(
+            worksheet, coly=resolved["lower"], colx=resolved["x"], type="l"
+        )
+        upper_plot.set_fill_area(type=9)
+        _apply_series_style(upper_plot, series_spec.get("style"))
+        _apply_series_style(lower_plot, series_spec.get("style"))
+        center_plot = layer.add_plot(
+            worksheet, coly=resolved["y"], colx=resolved["x"], type="l"
+        )
+        center_plots.append(center_plot)
+        label = series_spec.get("label") or series_spec["y"]
+        legend_entries.append(f"\\l({index * 3 + 3}) {label}")
+    return graph, layer, center_plots, "\n".join(legend_entries)
+
+
 def run(job_dir: Path) -> list[dict[str, Any]]:
     job_dir = job_dir.resolve(strict=True)
     request_record = json.loads((job_dir / "request" / "request.json").read_text(encoding="utf-8"))
@@ -496,10 +799,18 @@ def run(job_dir: Path) -> list[dict[str, Any]]:
     }
     plot_spec = request["operation"]["plot"]
     plot_type = plot_spec["type"]
-    if plot_type not in PLOT_CONFIG and plot_type != "heatmap":
+    if plot_type not in PLOT_CONFIG and plot_type not in {"heatmap", "multi_panel"}:
         raise ValueError("PLOT_TYPE_NOT_IMPLEMENTED")
-    series_specs = plot_spec["series"]
+    series_specs = (
+        [item for panel in plot_spec["panels"] for item in panel["series"]]
+        if plot_type == "multi_panel"
+        else plot_spec["series"]
+    )
     resolved_series, labels = _resolve_series(input_data, series_specs)
+    if plot_type == "bubble":
+        _validate_bubble_values(input_data, resolved_series)
+    if plot_type == "band":
+        _validate_band_values(input_data, resolved_series)
 
     import originpro as op
 
@@ -521,7 +832,18 @@ def run(job_dir: Path) -> list[dict[str, Any]]:
                     [row[index] if index < len(row) else None for row in rows],
                     lname=column_label,
                 )
-        if plot_type == "heatmap":
+        band_legend = None
+        if plot_type == "multi_panel":
+            graph = _build_multi_panel_graph(
+                op, plot_spec, worksheets, resolved_series
+            )
+            layer = graph[0]
+            origin_plots = []
+        elif plot_type == "band":
+            graph, layer, origin_plots, band_legend = _build_band_graph(
+                op, worksheets, series_specs, resolved_series
+            )
+        elif plot_type == "heatmap":
             import numpy as np
 
             resolved = resolved_series[0]
@@ -536,43 +858,67 @@ def run(job_dir: Path) -> list[dict[str, Any]]:
             graph = op.new_graph(template="heatmap")
             layer = graph[0]
             origin_plots = [layer.add_mplot(matrix_sheet, 0, type=105)]
+        elif plot_type in STACKED_PLOT_TYPES:
+            template, origin_plot_type = PLOT_CONFIG[plot_type]
+            graph, layer, origin_plots = _build_stacked_graph(
+                op,
+                input_data,
+                series_specs,
+                resolved_series,
+                template,
+                origin_plot_type,
+            )
         else:
             template, origin_plot_type = PLOT_CONFIG[plot_type]
             graph = op.new_graph(template=template)
             layer = graph[0]
             origin_plots = []
-            for resolved in resolved_series:
+            for series_spec, resolved in zip(
+                series_specs, resolved_series, strict=True
+            ):
                 arguments = {
                     "coly": resolved["y"],
-                    "colx": resolved["x"],
                     "type": origin_plot_type,
                 }
+                if "x" in resolved:
+                    arguments["colx"] = resolved["x"]
                 if plot_type in XYZ_PLOT_TYPES:
                     arguments["colz"] = resolved["z"]
                 if plot_type == "y_error":
                     arguments["colyerr"] = resolved["y_error"]
-                origin_plots.append(layer.add_plot(worksheets[resolved["input"]], **arguments))
+                origin_plot = layer.add_plot(
+                    worksheets[resolved["input"]], **arguments
+                )
+                if plot_type == "bubble":
+                    _configure_bubble_plot(op, origin_plot, series_spec, resolved)
+                origin_plots.append(origin_plot)
             if plot_type == "grouped_column":
                 layer.group()
-        layer.rescale()
         _apply_canvas(graph, plot_spec.get("canvas"))
-        _apply_axis(
+        if plot_type != "multi_panel":
-            layer, "x", plot_spec.get("x_axis"), str(series_specs[0].get("x") or "X")
+            layer.rescale()
-        )
+            if plot_type not in {"polar", "pie"}:
-        _apply_axis(layer, "y", plot_spec.get("y_axis"), "Y")
+                _apply_axis(
-        if plot_type == "surface_3d":
+                    layer, "x", plot_spec.get("x_axis"),
-            _apply_axis(
+                    str(series_specs[0].get("x") or "X")
-                layer, "z", plot_spec.get("z_axis"), str(series_specs[0].get("z") or "Z")
+                )
-            )
+                _apply_axis(layer, "y", plot_spec.get("y_axis"), "Y")
-        for origin_plot, series_spec in zip(origin_plots, series_specs, strict=True):
+            if plot_type == "surface_3d":
-            _apply_series_style(origin_plot, series_spec.get("style"))
+                _apply_axis(
-        _apply_legend(layer, plot_spec.get("legend"))
+                    layer, "z", plot_spec.get("z_axis"),
-        if plot_spec.get("title"):
+                    str(series_specs[0].get("z") or "Z")
-            title = layer.add_label(str(plot_spec["title"]))
+                )
-            title_font_size = (plot_spec.get("title_style") or {}).get("font_size", 18)
+            for origin_plot, series_spec in zip(origin_plots, series_specs, strict=True):
-            title.set_int("fsize", round(title_font_size))
+                style = series_spec.get("style")
-            title.set_int("left", 2200)
+                if plot_type == "bubble" and style:
-            title.set_int("top", 120)
+                    style = {key: value for key, value in style.items() if key != "symbol_size"}
+                _apply_series_style(origin_plot, style)
+            if plot_type in STACKED_PLOT_TYPES:
+                _replace_series_legend(layer, series_specs)
+            _apply_legend(layer, plot_spec.get("legend"))
+            if band_legend is not None:
+                layer.label("Legend").text = band_legend
+            _apply_title(layer, plot_spec.get("title"), plot_spec.get("title_style"))
         requested_outputs = request["outputs"]
         formats = [item["format"] for item in requested_outputs]
         if any(item not in FORMATS for item in formats):