_version: 1

# Simplified Chinese (zh-CN) -- viz Data Schematic UI.
# TODO: native-speaker review before release. The pending review is about wording
# and register, not encoding (this file is UTF-8).
# Keys missing here fall back to en (see `fallback = "en"` in src/main.rs).
#
# SIMPLIFIED, not Traditional. The tag is zh-CN for two reasons: plotly ships only
# `plotly-locale-zh-cn` (internal id "zh-CN") with no generic `zh`, and DataTables'
# bare `zh.json` -- which this vendors -- is Simplified, with Traditional published
# separately as `zh-HANT`. `--language zh` resolves here through an alias, while
# `zh-Hant` deliberately does NOT, so a Traditional request can never silently be
# answered in Simplified.
#
# ORDERING RULE: in `hover`, every `%{q_*}` must stay AHEAD of any plotly token
# containing a literal `%` inside its braces (`%{x:.0%}`), or it is left
# unsubstituted. See the header of en.yml.
viz:
  chrome:
    theme_toggle: "\U0001F313 主题"
    theme_toggle_aria: "切换浅色/深色模式"
    toggle_fullscreen: "切换全屏"
    toggle_legend: "切换图例"
    logo_alt: "datHere 出品的 qsv"
    credits_charts: "图表:"
    credits_table: "表格:"
    credits_notices: "声明"
  meta:
    description: "说明:"
    rows: "行数:"
    columns: "列数:"
    completeness: "完整度:"
    compiled: "生成时间:"
    generated_by: "生成工具:"
    pid: "PID:"
  viewer:
    link_explore: "(浏览)"
    link_preview: "(预览)"
    title_all: "数据 — 全部 %{q_rows} 行"
    title_preview: "数据 — 共 %{q_total} 行中的前 %{q_shown} 行(预览)"
    export_csv: "CSV"
    export_csv_preview: "CSV(预览)"
  map:
    cluster_point_one: " 个点"
    cluster_point_many: " 个点"
    cluster_click_to_zoom: " - 点击放大"
    row_not_in_preview: "该行不在预览范围内"
    row_is_filtered_out: "该行已被筛选排除"
    selected_row: "已选中的行"
    row_not_plotted: "该行不在已绘制的点中"
    row_has_no_coordinates: "该行没有地图坐标"
    region_filter_applied: "已筛选出 %{q_region} 的行"
    region_filter_cleared: "已清除区域筛选"
    extent_points: "范围点"
    spatial_extent: "空间范围"
    full_extent: "完整范围(含离群点)"
    geographic_outliers: "地理离群点"
    geo_extent_caption: "空间范围: %{q_summary}"
    geo_outlier_one: "个离群点"
    geo_outlier_many: "个离群点"
    geo_outliers: "%{q_core} — %{q_n} %{q_noun}"
    geo_outliers_where: "%{q_core} — %{q_n} %{q_noun}(%{q_where})"
    geo_n_countries: "%{q_n} 个国家"
    geo_n_regions: "%{q_n} 个地区%{q_suffix}"
    geo_n_areas: "%{q_n} 个区域"
  photo:
    alt: "鼠标悬停地图点的照片"
    close: "关闭"
    enlarge: "放大"
    enlarge_aria: "放大照片"
    shrink: "缩小"
    shrink_aria: "缩小照片"
    previous: "上一张照片"
    next: "下一张照片"
    unavailable: "图片不可用"
    unavailable_suffix: " - 不可用"
  dict:
    notable_characteristics: "值得注意的特征"
    title: "数据字典"
    open_own_tab: "在新标签页中打开"
    close_esc: "关闭(Esc)"
    field_type: "类型"
    field_content_type: "内容类型"
    field_role: "角色"
    field_concept: "概念"
    field_range: "取值范围"
    field_cardinality: "基数"
    field_null_count: "空值数量"
    field_values: "值"
    field_examples: "示例"
    role_unknown: "角色未知"
    grain: "粒度:"
    export_tooltip: "将该数据字典下载为 JSON Schema"
    export_label: "导出 JSONSchema"
    export_short: "schema"
    view_chart: "查看图表 "
    back_to_dashboard: "返回 Data Schematic"
    sidecar_download_tooltip: "下载 %{q_file},即构建该 Data Schematic 所依据的附属文件"
    prov_generated_by: "由 %{q_tool} describegpt 生成"
    prov_command_line: "命令行:"
    prov_prompt_file: "提示词文件:"
    prov_model: "模型:"
    prov_llm_api_url: "LLM API URL:"
    prov_language: "语言:"
    prov_timestamp: "时间戳:"
    prov_warning_dictionary_content_type: "警告: 标签、说明和内容类型由 LLM 生成,可能包含不准确之处。使用前请核实!"
    prov_warning_dictionary: "警告: 标签和说明由 LLM 生成,可能包含不准确之处。使用前请核实!"
    prov_warning_description: "警告: 说明由 LLM 生成,可能包含不准确之处。使用前请核实!"
    prov_warning_tags: "警告: 标记由 LLM 生成,可能包含不准确之处。使用前请核实!"
    prov_warning_generic: "警告: 由 LLM 生成,可能包含不准确之处。使用前请核实!"
  drawer:
    row_selected_one: " 行已选中"
    row_selected_many: " 行已选中"
    close_viewer: "关闭数据查看器"
    clear_filters: "清除筛选"
    clear_filters_prefix: "清除筛选("
    viewer_failed: "qsv viz: 数据查看器启动失败:"
    advanced_filter: "高级筛选"
    advanced_filter_counted: "高级筛选(%d)"
  cycle:
    # Keep these SHORT: they ring a polar chart and plotly neither wraps nor
    # elides them.
    day_mon: "周一"
    day_tue: "周二"
    day_wed: "周三"
    day_thu: "周四"
    day_fri: "周五"
    day_sat: "周六"
    day_sun: "周日"
    month_jan: "1月"
    month_feb: "2月"
    month_mar: "3月"
    month_apr: "4月"
    month_may: "5月"
    month_jun: "6月"
    month_jul: "7月"
    month_aug: "8月"
    month_sep: "9月"
    month_oct: "10月"
    month_nov: "11月"
    month_dec: "12月"
  menu:
    # KEEP THE LEADING GLYPH (`▶` U+25B6, `⏸` U+23F8, `⇅` U+21C5) and the space
    # after it -- they are part of the control, not words.
    play: "▶ 播放"
    pause: "⏸ 暂停"
    category_order: "⇅ 类别顺序"
    node_order: "⇅ 节点顺序"
    extent_core: "核心范围"
    extent_full: "完整范围"
    cluster_toggle: "聚类/散点"
    basemap_labels: "底图标注"
  chart:
    log_axis_count: "计数(对数)"
    log_axis_value: "对数刻度"
    null_bucket: "(空值)"
    other_bucket: "其他(%{q_count})"
    records: "条记录"
    count: "计数"
    trace_correlation: "相关性"
    trace_rank_correlation: "秩相关"
    trace_association: "关联度"
  title:
    data_overview: "%{q_dataset} — 数据概览"
    map: "地图"
    distribution_by: "按 %{q_dim} 划分的 %{q_measure} 分布"
    measure_by_dim: "按 %{q_dim} 划分的 %{q_measure}(%{q_agg},可解释 %{q_pct}% 的方差)"
    top_n: " — 前 %{q_n} 项"
    agg_sum: "求和"
    agg_mean: "平均值"
    sampled: "%{q_name}(抽样)"
    dominated_by: "(以 %{q_value} 为主,%{q_pct}%)"
    # `r` and `ρ` are statistical symbols -- leave them literal.
    pair_r: "%{q_x} 与 %{q_y}(r=%{q_r})"
    pair_r_nonlinear: "%{q_x} 与 %{q_y}(r=%{q_r}, ρ=%{q_rho} — 非线性)"
    pair_over_time: "%{q_pair} 随时间变化"
    pair_size: "%{q_name} · 大小: %{q_col}"
    # `x` / `y` are plotly axis identifiers -- literal in every locale.
    pair_log_x: "%{q_name} · log x"
    pair_log_y: "%{q_name} · log y"
    pair_log_xy: "%{q_name} · log x/y"
    bubble_over_time: "按 %{q_entity} 划分的 %{q_y} 与 %{q_x} 随时间变化"
    locations_over_time: "位置随时间变化"
    pair_log_scale: "%{q_name} · 对数刻度"
    pair_log_scale_positive: "%{q_name} · 对数刻度,仅正值(已省略 %{q_share} 的行)"
    trend_raw: "按 %{q_date} 的 %{q_y}"
    trend_agg: "按 %{q_date} 的 %{q_y}(%{q_agg})"
    trend_count: "按 %{q_date} 的 %{q_unit}"
    trend_axis_agg: "%{q_y}(%{q_agg}/%{q_bucket})"
    trend_axis_count: "每%{q_bucket} %{q_unit}"
    bucket_day: "天"
    bucket_week: "周"
    bucket_month: "月"
    bucket_quarter: "季度"
    bucket_year: "年"
    corr_spearman: "相关性(斯皮尔曼 ρ — 基于秩,对离群值稳健)"
    corr_pearson: "相关性(皮尔逊 r)"
    scatter3d: "%{q_x} / %{q_y} / %{q_z}(3D)"
    # NMI = normalized mutual information; the acronym stays literal.
    assoc_heatmap: "关联度(NMI)"
    top_relationships: "主要关联(NMI)"
    us_states: "美国各州"
    countries: "国家"
    count_by_region: "按 %{q_region} 的计数"
    # `≤` / `>` are math symbols, `km` is SI, and `--no-snap` (which arrives as
    # `%{q_why}`) is a FLAG NAME -- all literal.
    regions: "地区"
    regions_with: "地区(%{q_parts})"
    snap_snapped: "%{q_n} 个已吸附 ≤%{q_km} km"
    snap_dropped: "%{q_total} 个中有 %{q_n} 个被丢弃,%{q_why}"
    snap_why_over: ">%{q_km} km"
    category_flow: "类别流向: %{q_dims}"
    kpi_mean: "%{q_label} 平均值"
    kpi_total: "%{q_label} 总计"
    cyclic_records_by: "按 %{q_axis} 的记录数(%{q_date})"
    cyclic_hour_of_day: "一天中的小时"
    cyclic_day_of_week: "星期"
    cyclic_month: "月份"
  notes:
    box_null: "%{q_pct}% 为空值"
    box_zeros: "%{q_pct}% 为零"
    box_right_skewed: "右偏"
    box_left_skewed: "左偏"
    box_outliers: "%{q_pct}% 为离群值"
    box_heavy_tails: "厚尾"
    box_mean_impact: "离群值使均值偏移 %{q_pct}%"
    box_gini: "Gini %{q_gini}"
    lorenz_unit: "除非各行是可比较的单位,否则出现集中是正常的"
    lorenz_zeros: "平缓段 = %{q_pct}% 为零,而非小数值 · %{q_unit}"
    funnel_complete: "n = %{q_n} 个完整样本(占全部行的 %{q_pct}%)"
    funnel_violation: "在 %{q_pct}% 的行中 %{q_here} 超过 %{q_prev}"
    funnel_bridge: "各阶段并非逐层包含 — 属于桥接而非漏斗"
    funnel_inverted: "%{q_here} 的总计超过 %{q_prev} — 属于超出而非流失"
    # `--no-snap` and `--snap-max-dist` are FLAG NAMES: keep them verbatim.
    snap_coverage: "%{q_total} 个点中有 %{q_n} 个已吸附到最近的地区(≤%{q_km} km,%{q_basis})。"
    drop_coverage: "%{q_total} 个点中有 %{q_n} 个距离任何地区都超过 %{q_km} km,已被丢弃。"
    drop_coverage_no_snap: "--no-snap: %{q_total} 个点中有 %{q_n} 个落在所有 GeoJSON 地区之外,已被丢弃。"
    snap_basis_explicit: "--snap-max-dist"
    snap_basis_region_precision: "根据地区大小和坐标精度自动推导"
    snap_basis_region: "根据地区大小自动推导"
    snap_basis_precision: "根据坐标精度自动推导"
    snap_basis_default: "默认值"
  hover:
    # `%{x:.3s}` / `%{z:,}` / `%{x:.0%}` are PLOTLY tokens -- leave them exactly
    # as they are. In `lorenz`, `%{q_label}` and `%{q_gini}` MUST stay ahead of
    # `%{x:.0%}` (see the ORDERING RULE in this file's header).
    contour: "%{q_x}: %{x:.3s}<br>%{q_y}: %{y:.3s}<br>%{z:,} 行<extra></extra>"
    lorenz: "%{q_label}(Gini %{q_gini})<br>后 %{x:.0%} 的记录占有 %{y:.0%}<extra></extra>"
    ohlc: "开盘: %{open}<br>最高: %{high}<br>最低: %{low}<br>收盘: %{close}<extra></extra>"
    count_by_label: "%{hovertext}<br>计数: %{y:,}<extra></extra>"
    histogram: "%{q_col}: %{x:,.3f}<br>计数: %{y:,}<extra></extra>"
    polar_records: "%{theta}<br>记录数: %{r:,.0f}<extra></extra>"
    pct_of_total: "占总量的 %{q_pct}%"
    rank_of: "%{q_total} 个中排名第 %{q_rank}"
    snap_includes: "其中 %{q_n} 个从外部吸附而来"
