Metadata-Version: 2.5
Name: rsplot
Version: 0.4.0
Summary: CLI tool for plotting Remote Sensing data, designed for Agent.
Project-URL: Repository, https://git.lug.ustc.edu.cn/yaoyhu/rsplot
Project-URL: GitHub, https://github.com/yaoyhu/rsplot
Author-email: Yaoyao Hu <yaoyhu@mail.ustc.edu.cn>
License: Apache License
                                   Version 2.0, January 2004
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License-File: LICENSE
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Python: <3.14,>=3.10
Requires-Dist: astropy>=5.3
Requires-Dist: cartopy>=0.21
Requires-Dist: geopandas>=0.13
Requires-Dist: matplotlib>=3.7
Requires-Dist: netcdf4>=1.7.3
Requires-Dist: numpy>=1.24
Requires-Dist: pyproj>=3.1
Requires-Dist: rich>=13.0.0
Requires-Dist: scipy>=1.10
Requires-Dist: shapely>=2.0
Requires-Dist: tomli>=2.0; python_version < '3.11'
Requires-Dist: typer>=0.9.0
Requires-Dist: xarray>=2023.0
Description-Content-Type: text/markdown

# rsplot

`rsplot` is a command-line tool for agents to analyze multi-source
spatiotemporal remote-sensing and air-quality data: TROPOMI and GEMS
satellite retrievals, national monitoring stations and ERA5. Each command
writes a machine-readable JSON result with statistics,
quality flags and data files, plus a map for inspection. It provides a
small, stable CLI surface for
[tianpu-agent](https://git.lug.ustc.edu.cn/yaoyhu/tianpu-agent).


## Installation

Run directly with `uvx`:

```bash
uvx rsplot --help
```

Or install it in a project environment:

```bash
uv add rsplot
uv run rsplot --help
```

### Development releases

Every push to `main` publishes a PEP 440 development release such as
`0.3.1.dev4`. Stable installs continue to ignore these releases. To follow the
latest development build, opt in once:

```bash
uv tool install rsplot --prerelease allow
uv tool upgrade rsplot
```

The prerelease setting is retained by later `uv tool upgrade` commands.

For local development:

```bash
git clone https://github.com/yaoyhu/rsplot.git
cd rsplot
uv sync
uv run rsplot --help
```

## Configuration

Satellite HCHO, O3, and O3PR use the bundled `colormap_22.txt` by
default; NO2 uses the built-in nine-color gradient. These defaults apply to
both TROPOMI and GEMS. Use `--cmap` to select another registered colormap.

`rsplot` does not ship site-specific data paths. Configure local satellite,
station, boundary, and font paths with a TOML file:

```bash
mkdir -p ~/.config/rsplot
cp config.example.toml ~/.config/rsplot/config.toml
```

Then edit `~/.config/rsplot/config.toml`:

```toml
[paths]
geojson_dir = "/path/to/geojson"
font_dir = "/path/to/fonts"

[paths.data_dirs]
no2 = "/path/to/NO2"
o3 = "/path/to/O3"
o3pr = "/path/to/O3PR"
hcho = "/path/to/HCHO"
guokong = "/path/to/guokong_combine"
era5 = "/path/to/era5"
forecast = "/path/to/forecast"
reconstruct = "/path/to/reconstruct"

# Optional lower-level boundary override for a direct-administered city.
# [subdivision_overrides."中山市"]
# path = "/path/to/中山市镇街界线.shp"
# name_field = "镇街名称"
# level = "township"

# Optional satellite basemap key. Leave commented unless you have a real key.
# [tianditu]
# api_key = "your-real-key"
```

You can also point to a different config file:

```bash
export RSPLOT_CONFIG="/path/to/rsplot.toml"
```

Environment variables override TOML values:

```bash
export TIANDITU_API_KEY="your-key"
export RSPLOT_GEOJSON_DIR="/path/to/geojson"
export RSPLOT_FONT_DIR="/path/to/fonts"
export RSPLOT_DATA_DIR_NO2="/path/to/NO2"
export RSPLOT_DATA_DIR_O3="/path/to/O3"
export RSPLOT_DATA_DIR_O3PR="/path/to/O3PR"
export RSPLOT_DATA_DIR_HCHO="/path/to/HCHO"
export RSPLOT_DATA_DIR_GUOKONG="/path/to/guokong_combine"
export RSPLOT_DATA_DIR_ERA5="/path/to/era5"
export RSPLOT_DATA_DIR_FORECAST="/path/to/forecast"
export RSPLOT_DATA_DIR_RECONSTRUCT="/path/to/reconstruct"
```

Data folders come from configuration only; commands have no directory
options. If no TianDiTu API key is configured, use `--basemap none`
to avoid requesting satellite tiles.

City subdivision overrides replace the county layer only for the configured
city. Their source CRS is converted to the CRS of the standard city boundary.
This lets direct-administered towns or streets appear in maps and spatial
summaries, and makes qualified inputs such as `中山/板芙` resolvable.

## Usage

The examples below assume data paths are configured and readable.

```bash
# Show available commands and options.
rsplot --help

# Plot a single-day TROPOMI raster.
rsplot raster 合肥 20260115 --product no2 --output ./logs/hcho/raster_city_jiujiang_hcho.png

# Plot a 30-day TROPOMI window mean.
rsplot raster 安徽 20260131 --product hcho --days 30 --output hcho_anhui_202601.png

# Plot a TROPOMI ozone-profile tropospheric column raster.
rsplot raster 安徽 20260227 --product o3pr --output o3pr_anhui_20260227.png

# Plot an explicit TROPOMI date range.
rsplot raster 长三角 20260101-20260131 --product no2 --output no2_yrd_202601.png

# Plot ERA5 2 m temperature. Input hours are China standard time; rsplot
# converts them to the matching UTC archive day and hour automatically.
# meteo needs an exact China-time hour (YYYYMMDDHH) in every mode. Each
# layer writes a data file, e.g. meteo_nanjing_t2m.temperature.nc.
rsplot meteo 南京 2026051115 --temp-level 2m --output meteo_nanjing_t2m.png

# Plot black 850 hPa wind arrows; length represents speed and no wind
# colorbar is drawn. The reference arrow gives the speed scale.
rsplot meteo 南京 2026051115 --wind-level 850 --output meteo_nanjing_wind850.png

# Overlay black wind arrows on a temperature background. Only the temperature
# colorbar is drawn.
rsplot meteo 南京 2026051115 --temp-level 850 \
  --wind-level 850 --output meteo_nanjing_t850_wind850.png

# Overlay station observations with black wind arrows.
rsplot meteo 南京 2026051115 --station-var O3 \
  --wind-level 850 --output meteo_nanjing_o3_wind850.png

# Temperature, stations, and wind can be combined. The two colorbars describe
# temperature and station concentration; wind magnitude is encoded by length.
rsplot meteo 南京 2026051115 --temp-level 850 --station-var O3 \
  --wind-level 850 --output meteo_nanjing_t850_o3_wind850.png

# Plot national monitoring station observations at an explicit China-time hour.
rsplot station 合肥 2026041415 --var O3 --output station_hefei_o3.png

# Plot one station's hourly observations over the latest seven days.
rsplot trend 3347A 20260520 --days 7 --var O3 --output trend_3347A_o3_7d.png

# A single day and an explicit date range are also supported.
rsplot trend 3347A 20260520 --days 1 --var O3 --output trend_3347A_o3_day.png
rsplot trend 3347A 20260501-20260507 --var PM2.5 --output trend_3347A_pm25.png

# Plot all regional stations as grey lines plus the hourly station mean.
rsplot trend 重庆 20260520 --days 7 --var O3 --region --output trend_chongqing_o3.png

# Plot only the regional mean and highlight one or more explicit stations.
rsplot trend 重庆 20260520 --days 7 --var O3 --region --view mean \
  --focus-station 3347A --threshold 200 --output trend_chongqing_focus.png
# Each trend also writes <name>.series.nc: value(station, time), whose
# time decodes to the requested hours, plus regional_mean and n_stations
# in region mode. The
# sidecar's station (or regional_mean) layer adds `daily` rows (hours, mean,
# min, max per China-time day) and 24 `diurnal` rows (mean per hour of day).

# Overlay satellite raster data and station observations.
rsplot overlay 合肥 20260414 --product no2 --station-var NO2 \
  --station-datetime 2026041413 --output overlay_hefei_no2.png

# Plot an FNR regime map over the 7 days ending on a date. The sidecar has
# no2, hcho and fnr layers (regime counts in the fnr layer's categories),
# with fnr_hefei.no2.nc, fnr_hefei.hcho.nc and fnr_hefei.fnr.nc.
rsplot fnr 合肥 20260114 --days 7 --output fnr_hefei.png

# Plot an FNR regime map with an explicit date range.
rsplot fnr 长三角 20260101-20260130 --output fnr_yrd_202601.png

# Override FNR regime thresholds for agent-driven sensitivity tests.
rsplot fnr 合肥 20260114 --days 7 --voc-threshold 0.8 --nox-threshold 1.8 \
  --display-max 5 --output fnr_hefei_sensitivity.png
```

`--output` is required and must name a `.png` file (case-insensitive),
not a directory. Invalid output paths are rejected before reading data or
writing artifacts. `rsplot` writes the image to that exact path and a JSON
sidecar with the same base name. Nothing that selects data is implied:
`--product` (satellite maps), `--var` (`station`, `trend`), `--station-var`
(`overlay`) and the window length (`--days` with a single end date for
`trend` and `fnr`, or a `YYYYMMDD-YYYYMMDD` range) must be given.

Regions are named in Chinese; there is no `--level` option and no pinyin.
A full name selects its own level (`吉林市` is the city, `吉林省` the
province). A short name that fits different places at two levels, such as
`吉林` or `海南` (海南省 and 海南藏族自治州), is rejected with error code
`region_ambiguous` and the candidate full names. Autonomous areas can be
named without their ethnic groups: `广西`, `新疆`, `宁夏`, `楚雄`. 北京市, 上海市 and 天津市 are mapped as cities and 重庆市 as a
province. Counties and townships are written with their city, e.g.
`合肥/蜀山`. `中国`/`China` and the key regions (`长三角`/`YRD`, `京津冀`/`BTH`,
`珠三角`/`PRD`, `成渝`/`SCB`) are also accepted.

### Result sidecars

Every successful command writes the agent-oriented sidecar specified in
[docs/result-schema.md](docs/result-schema.md) and validated by the shipped
JSON Schema `src/rsplot/schemas/result.schema.json`. `rsplot_version` names
the release that wrote it; there is no separate format number.

```bash
rsplot raster 合肥 20260919 --product no2 --days 7 --output out/hefei_no2_week.png
# out/hefei_no2_week.png            image
# out/hefei_no2_week.json           sidecar
# out/hefei_no2_week.satellite.nc   statistical grid: value, counted, valid_days
```

| Question an agent asks | Where to read it |
| --- | --- |
| Did it work? | Exit 0 and a sidecar; on failure exit 1 and one `rsplot error <code>` line on stderr |
| How far can I trust it? | `layers[0].coverage` and `quality.flags` (code, severity and the measured `evidence`; no prose verdict) |
| What was measured, in which unit? | `layers[0].quantity` (`unit` and `scale`) |
| Over which time? | `layers[0].time`, including `days` for windows |
| From which files? | `layers[0].source` (`data_root`, `files_total`, `failed_files`; names are not listed) |
| How was it processed? | `layers[0].method` |
| Regional result | `layers[0].coverage`, `stats`, `by_admin`, `by_member`, `extremes` |
| Full values | the NetCDF in `layers[0].data` / `artifacts.data` |
| How to reproduce it | `request`, the command on one line; effective values that change the numbers are in `method` |

A failed run exits 1, prints one line such as
`rsplot error region_ambiguous: … {"region": "吉林", "candidates": ["吉林省", "吉林市"]}`
on stderr, and leaves no PNG, JSON or data file. For example, the real
Hefei 7-day NO2 window above
covers only 2.9 % of the city's cells, so it carries a critical
`very_low_coverage` flag with evidence `valid` 35, `total` 1209, `fraction`
0.029 and `threshold` 0.1.

The `forecast` and `reconstruct` commands are disabled and no longer part of
the CLI. Their `forecast` and `reconstruct` data-directory keys remain valid
in configuration but are unused.

`station REGION YYYYMMDDHH` requires an exact hour in China standard time
(`Asia/Shanghai`). Date-only input (`YYYYMMDD`), invalid dates, and hours outside
00–23 are rejected with exit code 1 before configuration or data access.
The command reads only the requested hour; it never selects the latest hour
or falls back to another file when that hour is missing. Existing date-only
`station` calls must supply an explicit hour. Its sidecar
has one `station` layer (statistics over in-region stations, exceedances,
per-district rows, and AQI bands in `categories` for AQI) and a
`<name>.station.csv` listing every station read around the region with
`in_region`.

## Raster dates and temporal aggregation

`rsplot raster REGION DATE` defaults to TROPOMI. `DATE` selects satellite
observations, not a ground-station hour:

| Input | TROPOMI | GEMS (`--sensor gems`) |
| --- | --- | --- |
| `YYYYMMDD` | Merge matching orbit files for that filename date, then grid their pixels | Equal-scan daily mean for that date in China standard time |
| `YYYYMMDD --days N` | Average daily grids over N days ending on DATE, including DATE | Average daily scan means over the same inclusive window |
| `YYYYMMDD-YYYYMMDD` | Average daily grids over the inclusive date range | Average daily scan means over the inclusive date range |
| `YYYYMMDDHHMM` | Not supported | One exact nominal scan in China standard time |

A date range and `--days` cannot be used together. TROPOMI dates match the
UTC start date in standard S5P filenames; they do not select an hourly
observation or convert a China-time day into an observation-time window.
Without `--processing`, all matching files in the selected directory are
eligible. `--processing nrti` restricts selection to NRTI and deduplicates
overlapping observations using orbit, observation time and ground-pixel ID.

TROPOMI processing filters QA/clouds and invalid values, converts units, and
averages pixels in each target grid cell. Window mode grids each day, then
averages valid daily values with equal day weights. Statistics, coverage,
extremes, station colocation and the `.satellite.nc` data file use observed
cells only, for every sensor and time mode. Gap filling and smoothing are
display-only: a single TROPOMI day fills small gaps (nearest neighbour
within 3 cells) in the image alone, and `--smooth` never changes a number in
the sidecar. `render.layers.satellite` records `display_gap_fill` and
`display_smoothing_sigma`.

A window keeps every cell with at least one valid day: its value is the
mean of that cell's valid daily values, each weighted equally. Missing or
invalid days are skipped, never treated as zero-valued observations, and a
cell with no valid day stays nodata. There is no minimum-valid-days option;
`time.days.valid_days_per_cell` in the sidecar shows how many days support
each cell, and missing days are recorded in `time.days.failed`.

`raster` always saves an image, a same-basename JSON sidecar and a
`<name>.satellite.nc` data file. Use `-o` for an explicit PNG path; otherwise
files are saved under `/tmp`.

## Satellite and station overlays

`rsplot overlay REGION DATE` draws one satellite layer and one hour of
national monitoring-station observations on the same map. `DATE` selects
satellite time exactly as `raster` does, including `YYYYMMDD-YYYYMMDD`,
`--days N`, and GEMS `YYYYMMDDHHMM` scans. TROPOMI remains daily:
the orbits for one filename date are merged, and there is no hourly
TROPOMI selector.

Station observations are always one concrete China-time hour, never a
temporal mean. rsplot never picks the latest available hour and never falls
back to another file.

| Satellite request | Station hour |
| --- | --- |
| TROPOMI day or window | `--station-datetime YYYYMMDDHH` is required |
| GEMS daily mean or window | `--station-datetime YYYYMMDDHH` is required |
| GEMS scan `YYYYMMDDHHMM` | Nearest station hour (at most 30 minutes, ties forward); `--station-datetime` overrides it |

```bash
# TROPOMI 7-day NO2 mean with 13:00 China-time station observations.
rsplot overlay 合肥 20260919 --product no2 --days 7 --station-var NO2 \
  --station-datetime 2026091913 --output overlay_hefei_no2_week.png
```

`--station-var` is required and names the station variable explicitly;
there is no product-to-station-variable default.
Satellite columns and station concentrations keep independent colorbars and
units; the map shows spatial juxtaposition, not a column-to-surface
conversion.

The sidecar has two layers. `satellite` is the same layer
`raster` writes, with its period in `time` (calendar days, like every rsplot
time in China time). `station` holds the station hour in
`time.at`, statistics over in-region stations, exceedances against the
variable's limit, and per-district rows. Next to the image are
`<name>.satellite.nc` and `<name>.station.csv`; the CSV lists every station
read around the region with `in_region`, its value, and the satellite value
of the cell it falls in.

`relations.time_matching` says how the two times were paired:
`nominal_scan_time` for GEMS scans (with the difference in minutes),
`daily_mean_with_explicit_station_hour` for GEMS daily means, and
`period_mean_with_explicit_station_hour` for TROPOMI days and all windows
(difference null, because a daily or window mean has no single observation
time). `relations.colocation` counts stations that fall in a valid satellite
cell and gives the Spearman rank correlation of satellite and station values
(null with fewer than 3 pairs). It measures spatial agreement only;
`comparable_units` is always false.

## Station map color scales

Station layers in `station`, `overlay`, `meteo`, and
`radius --station-var` share fixed O3 and NO2 color scales. Concentrations
at or below the threshold use a green–yellow–orange gradient. Values strictly
above the threshold are red, including values beyond the colorbar maximum;
a red upper extension marks this overflow. Equality is not exceedance.

| Station variable | Threshold (μg/m³) | Colorbar range (μg/m³) |
| --- | --- | --- |
| `O3_8h`, `O3_8h_24h` (8h O3 / MDA8 O3) | 160 | 0–180 |
| `O3` (hourly) | 200 | 0–220 |
| `O3_24h` (existing hourly-limit mapping) | 200 | 0–220 |
| `NO2` (hourly) | 200 | 0–220 |
| `NO2_24h` (daily) | 80 | 0–100 |

AQI retains its existing discrete bands. Other station variables retain their
P5–P95 scales. These station rules do not change satellite or temperature
colorbars. No station `--vmin` or `--vmax` options are added.
Fixed station-scale metadata appears in `render.layers.station` for
`station`, `overlay`, `radius` and `meteo`.
Original observations, summary statistics and exceedance counts are preserved.

## Satellite maps around a monitoring station

`radius STATION_ID DATE --km KM` draws a square centered on a national
monitoring station, extending KM kilometers north, south, east, and west.
For example, `--km 5` produces a 10 km × 10 km square in a station-centered
WGS84 azimuthal equidistant projection. All stations within the square,
including its corners, use the same markers and ID labels. The square fills
the map axes without exterior padding or an extra dashed outline. City boundaries
and county/township names remain visible across administrative borders;
configured city-specific township layers are reused.

```bash
# GEMS daily satellite mean, station locations from one explicit hour
uv run rsplot radius 1379A 20260907 --km 5 \
  --sensor gems --product no2 --station-datetime 2026090713 \
  --output /tmp/radius_positions.png

# The same satellite mean plus ONE station observation hour
uv run rsplot radius 1379A 20260907 --km 5 \
  --sensor gems --product no2 \
  --station-var NO2 --station-datetime 2026090713 \
  --output /tmp/radius_no2.png

# Exact GEMS scan: 12:45 China time matches the 13:00 station file
uv run rsplot radius 1379A 202609071245 --km 5 \
  --sensor gems --product no2 --station-var NO2 \
  --output /tmp/radius_scan.png
```

- `--km` is required and accepts positive fractional kilometers measured
  from the center to each side, not the full side length. Satellite
  options (`--sensor`, `--product`, `--days`, `--res`, `--cf`,
  `--qa`, color limits and smoothing) follow `raster`. Defaults are
  TROPOMI/O3, county product plotting settings, and `--basemap none`.
- Without `--station-var`, only station IDs and coordinates are read, from
  the hour given by the required `--station-datetime YYYYMMDDHH`; rsplot
  never picks the latest hour. No pollutant field is needed.
- With `--station-var`, daily/window satellite maps require an explicit
  station hour. GEMS exact scans automatically match the nearest hour,
  with half-hour ties rounded forward; an explicit hour overrides this.
  Missing hourly files are errors, not a request to select another hour.
- Station observations are **never averaged across hours**. `NO2`, `O3`,
  `PM2.5`, `PM10`, `SO2`, `CO`, `AQI`, and the existing derived fields are
  supported. Fields such as `O3_8h` are read as stored in the selected file.
  The station archive and satellite files come from the configured
  `guokong` and product folders.
- GEMS dates mean equal-weight averages of the day's available valid scans,
  not a 24-hour mean. Actual scan counts vary; archive filenames are UTC,
  while command dates and station hours are China time. Titles distinguish
  satellite aggregation from the selected station hour. Scan matching uses
  the nominal scan time, not each pixel's actual observation time.
- Satellite and station values have independent colorbars and units.
  Missing station values retain hollow location markers. No extra center
  ring or lower-right legend is drawn. No station colorbar is drawn when all
  observations are missing.
- Statistics count strictly interior grid centers; intersecting valid cells
  are displayed and clipped to the square. GEMS defaults to 0.05° and `--res`
  changes both analysis and display spacing. Small squares can contain no grid
  centers while still showing portions of intersecting cells: counts are
  then zero and statistical summaries null. Coverage is a center count,
  not a fraction of polygon area.

A PNG, a sidecar, `<name>.satellite.nc` and
`<name>.station.csv` are saved (under `/tmp` by default). The region has
`kind: station_radius` and a `radius` block: `center_station`, centre
coordinates, `km` (the centre-to-side distance), `side_length_km` (twice
that), `shape: square`, and `administrative_context` (cities containing the
centre, visible cities and subdivisions). The `satellite` layer matches
`raster`. The `station` layer is `location` without `--station-var` (no
values, no relations) or the chosen variable with statistics, exceedances,
`relations.time_matching` and `relations.colocation`, as for `overlay`. The
station CSV lists the stations in the square with `is_center`,
`distance_km` (geodesic, so corner stations can exceed `--km`) and the
east/north offsets `dx_km`/`dy_km` used for selection. Daily/window versus
hourly comparisons have a null time difference; scan comparisons record the
nominal time difference.

## Select multiple regions without configuration

`raster`, `overlay`, `station`, `meteo` and `fnr` accept a quoted,
comma-separated region argument.
Use English or Chinese commas; surrounding whitespace and embedded line
breaks are ignored in a list. Province, city, and qualified county/township
names can be mixed. County and township names still require their city,
e.g. `中山市/东区街道`. `trend --region` summarizes one region per run
and rejects a list; run it once per region.

```bash
# One map covering three selected townships.
uv run rsplot raster \
  "中山市/东区街道,中山市/南区街道,中山市/石岐街道" 20260907 \
  --sensor gems --product o3pr --cf 1 --res 0.075 --smooth 0 \
  --basemap none --output ./logs/zhongshan/three_streets_raster.png

# The same daily satellite field with observations at 19:00 China time.
uv run rsplot overlay \
  "中山市/东区街道,中山市/南区街道,中山市/石岐街道" 20260907 \
  --sensor gems --product o3pr --station-var O3_8h_24h \
  --station-datetime 2026090719 \
  --cf 1 --res 0.075 --smooth 0 --basemap none \
  --output ./logs/zhongshan/three_streets_overlay.png
```

These examples use your configured product/station data paths; no named
region group needs to be added to configuration.

Every member is resolved before reading data. Repeated aliases are removed
in first-occurrence order; empty items and unknown names fail with an explicit
error instead of silently omitting regions. The map reads and processes the
combined extent once, but colors only the union of the selected geometries,
preserving holes and gaps between disconnected regions. Each member retains
its boundary and label. Defaults use the coarsest selected level; combined
maps use automatic geographic ticks. Explicit plot options still take
precedence. Far-apart selections share one map with intervening whitespace.

Combined maps use `联合区域（N个）` as their default name. The JSON adds
`region.members` with canonical qualified names, administrative levels and
extents. Existing overall statistics operate on the geometric union, without
double-counting parent/child overlaps. `raster` summarizes each selected
member in the satellite layer's `by_member`, using that same statistical grid;
overlay also adds `by_member` to its station layer. A member with no valid data
remains in the list with zero valid counts and null numeric summaries.
Members may overlap, so their counts must not be added to recover the union
count. Grid centers exactly on a member boundary are excluded from that
member's statistics, even if they lie inside the combined region. Station
selection retains the existing boundary-tolerance rule. `spatial_summary`
continues to describe subdivisions, independently of selected-member stats.
Single-region inputs retain their existing output contract.

## Raster boundaries and regional statistics

`raster` and `overlay` prepare separate display and statistics grids:

- **Display:** retain valid grid cells that intersect the administrative
  geometry, even when their centers are outside. Clip the colored layer to
  the actual boundary, including holes and disconnected islands. Display
  smoothing uses surrounding values but preserves the input valid-cell mask.
- **Statistics:** select grid centers **strictly inside** the geometry;
  centers exactly on the boundary are excluded. Each valid selected cell has
  equal weight. Coverage is the valid selected-cell count divided by the
  total selected-cell count, not the percentage of colored land area.
  Statistics use the observed grid: no gap filling and no smoothing.

`raster` records the statistics rules in the satellite layer's `method`
(`cell_selection`, `cell_weighting`) and the display rules in
`render.layers.satellite` (`display_selection`, `display_clip`,
`display_valid_cells`); `overlay` and `radius` record the same fields for
their satellite layer.
A small region can display overlapping cells while having no interior grid
centers: its statistics then report zero valid cells and null summaries.
This change does not increase the satellite's native resolution or fill
missing observations.

## TROPOMI NRTI processing stream

Use `--processing nrti` with `raster`, `radius`, `overlay`, or `fnr`.
Keep `--sensor tropomi` for commands with
a sensor option; FNR is already TROPOMI-only and has no sensor option. All four
products are supported: `no2`, `hcho`, `o3`, and `o3pr`. Omitting
`--processing` preserves the existing directories and reading behavior.
The NRTI option cannot be combined with GEMS.

Configure independent archive roots under `[paths.data_dirs]`:

```toml
[paths.data_dirs]
tropomi_nrti_no2 = "/path/to/NO2/NRT"
tropomi_nrti_hcho = "/path/to/HCHO/NRT"
tropomi_nrti_o3 = "/path/to/O3/NRT"
tropomi_nrti_o3pr = "/path/to/O3PR/NRT"
```

The corresponding environment variables are `RSPLOT_DATA_DIR_TROPOMI_NRTI_NO2`,
`RSPLOT_DATA_DIR_TROPOMI_NRTI_HCHO`, `RSPLOT_DATA_DIR_TROPOMI_NRTI_O3`, and
`RSPLOT_DATA_DIR_TROPOMI_NRTI_O3PR`. Missing NRTI configuration or files
produce an error; rsplot does not fall back to another processing stream.

Each root directly contains `S5P_NRTI_L2__*.nc` or `.nc.zip` files. The checked
NRT archive's `.nc.zip` files are HDF5/NetCDF containers despite the extension;
rsplot opens them directly, without ZIP extraction. Dates retain the existing
TROPOMI filename-start-date selection in UTC. NRTI does not introduce an
hourly satellite selector; overlay/radius station-hour rules stay unchanged.

```bash
rsplot raster 安徽 20260918 --product no2 --processing nrti \
  --basemap none --output /tmp/anhui_no2_nrti.png

rsplot overlay 安徽 20260918 --product no2 --processing nrti \
  --station-var NO2 --station-datetime 2026091812 --basemap none --output /tmp/anhui_no2_nrti_overlay.png

rsplot radius 1379A 20260918 --km 20 --product no2 --processing nrti \
  --station-var NO2 --station-datetime 2026091812 \
  --basemap none --output /tmp/station_no2_nrti.png

rsplot fnr 安徽 20260917-20260919 --processing nrti --n-min 1 \
  --basemap none --output /tmp/anhui_fnr_nrti.png
```

NRTI uses the existing TROPOMI QA/cloud filters, unit conversions, plotting
settings and statistical masks. Before gridding, overlapping granules are
deduplicated by orbit, UTC observation time and ground-pixel index. Among
valid copies of an observation, the newest file production time wins; ties
use ascending filename order. Observations from different orbits remain
separate. Negative valid retrievals remain available to the existing science
rules. Missing identity fields cause a file failure, not unverified merging.

Daily grids average the deduplicated pixels; windows weight valid daily grids
equally. FNR still averages NO2 and HCHO separately before division. The latest
date may contain only the granules received so far: a successful read does not
mean the archive contains a complete day, and results can change as files arrive.

In `raster` and `overlay` sidecars, NRTI appears as
`source.processing: "nrti"`, with the deduplication rule and
`duplicates_removed` in the satellite layer's `method`. The other commands'
sidecars identify `sensor: "tropomi"` and `processing: "nrti"`. Swath/daily metadata records source files, failed
files, processor/product versions, retained observation time range, valid
pixel counts before and after deduplication, and `n_duplicates_removed`.
Window results retain daily diagnostics; FNR records `window.daily_no2` and
`window.daily_hcho`. Default titles and output filenames identify NRTI;
explicit `--title` and `--output` still take precedence.

## GEMS satellite products

Use `--sensor gems` with `raster`, `radius`, and `overlay`. Omitting
`--sensor` retains TROPOMI behavior. GEMS FNR and satellite trend curves are
not included in this release.

Configure the three archive roots in `[paths.data_dirs]`:

```toml
gems_no2 = "/path/to/GEMS/NO2"
gems_hcho = "/path/to/GEMS/HCHO"
gems_o3 = "/path/to/GEMS/O3"
```

Alternatively set `RSPLOT_DATA_DIR_GEMS_NO2`, `RSPLOT_DATA_DIR_GEMS_HCHO`,
and `RSPLOT_DATA_DIR_GEMS_O3`. Each root contains `YYYYMM/DD/*.nc`.

| Product | GEMS variable | Display unit |
| --- | --- | --- |
| `no2` | `Data Fields/ColumnAmountNO2Trop` | 10¹⁵ molecules/cm² |
| `hcho` | `Data Fields/ColumnAmount` | 10¹⁵ molecules/cm² |
| `o3` | `product/total_ozone_column` | DU |
| `o3pr` | `product/troposphere_ozone_column` | DU |

Both ozone quantities use the O3P files in `gems_o3`; `o3pr` reads the
provided tropospheric column without reintegrating the profile. Neither
quantity represents surface ozone concentration.

GEMS dates and scan requests use **Asia/Shanghai**. `YYYYMMDDHHMM` selects
an exact nominal scan; `YYYYMMDD` computes the day's valid-scan mean.
For example, `202609010845` selects the `20260901_0045` UTC archive scan.
The filename is the nominal scan time, not a simultaneous observation time
for every pixel: GEMS scans begin at :45 UTC and take about 30 minutes
([NESC operation schedule](https://nesc.nier.go.kr/en/html/satellite/operation.do)).
Missing scan requests report available local times instead of selecting a
replacement. Duplicate files for one nominal scan are rejected; use a root
containing one archive version.

```bash
# Exact scan, daily mean, and multi-day mean.
rsplot raster 安徽 202609011145 --sensor gems --product no2 \
  --basemap none --output /tmp/gems_no2_scan.png
rsplot raster 安徽 20260901 --sensor gems --product hcho \
  --basemap none --output /tmp/gems_hcho_daily.png
rsplot raster 安徽 20260901-20260902 --sensor gems --product o3pr \
  --basemap none --output /tmp/gems_o3pr_window.png

# 11:45 China-time scan with observations at the nearest hour, 12:00.
rsplot overlay 安徽 202609011145 --sensor gems --product no2 \
  --station-var NO2 --basemap none --output /tmp/gems_no2_overlay.png
# Use --station-datetime YYYYMMDDHH for an intentional time override.
```

Each scan is first remapped by pixel/target overlap area in the equal-area
EPSG:6933 projection, directly onto a **globally aligned target grid selected
by `--res`**. GEMS defaults to 0.05° at every administrative level. This is
numerical grid spacing, not native satellite resolution; finer grids cannot
recover variation within a native pixel. Daily means
weight valid scans equally at each grid cell; multi-day means then weight
valid days equally. A daily cell needs at least one valid scan, and a window
cell at least one valid day. These are means of available daytime scans,
not full 24-hour means. Empty scans and failed files do not contribute zeros.

For GEMS `raster`, `radius`, and `overlay`, **`--res` controls the actual
analysis grid**. No fixed 0.05° intermediate grid is used. Raster and overlay
draw that grid directly, clipped to its valid-cell union and the administrative
boundary. Changing `--res` may change grid-center selection, coverage, and
regional statistics; use the same spacing for comparisons. `--smooth` affects
display only and preserves the target grid's valid mask; statistics remain
unfilled and unsmoothed. DPI and map graticules are independent of grid spacing.
TROPOMI keeps its existing resolution behavior.

For example, compare Zhongshan O3PR at two target spacings without smoothing:

```bash
rsplot raster 中山市 20260907 --sensor gems --product o3pr --cf 1 \
  --res 0.05 --smooth 0 --basemap none --output /tmp/gems_o3pr_res005.png
rsplot raster 中山市 20260907 --sensor gems --product o3pr --cf 1 \
  --res 0.01 --smooth 0 --basemap none --output /tmp/gems_o3pr_res001.png
```

When available, GEMS pixel boundaries use file `CornerLongitude` and
`CornerLatitude` arrays. The checked O3P and NO2 files have centers only;
their quadrilateral boundaries are **estimates from adjacent unfiltered
native centers**, with linear extrapolation at the outer scan edge. Missing
geolocation is not interpolated, and rejected retrievals do not contribute
values. This is not a recovery of official footprints or extra observations.
Analysis cells need positive-area overlap with valid footprints; their
coverage percentage counts valid analysis centers, not precisely observed
land area. Gaps smaller than the selected target cells remain unresolved.

Sidecars record `footprint_source` per scan, `spatial_aggregation`,
`area_crs`, `analysis_resolution_deg`, `display_resolution_deg`, and
`display_support`. The compatibility `swath.resolution_deg` describes the
analysis grid; `analysis_resolution_deg` and `display_resolution_deg` both
record the selected target spacing. `display_support` is `analysis_valid_cells`.
Statistics may change with `--res`, but remain unchanged by smoothing or DPI.

The initial GEMS filter retains final quality flag **0**, finite coordinates
and columns, SZA/VZA below 70°, and a nonnegative cloud measure no greater
than `--cf` (default 0.5). The cloud measures differ: NO2 uses `CloudFraction`,
HCHO uses `CloudRadianceFraction`, and O3P uses `effective_cloud_fraction`.
`--qa` applies only to TROPOMI and is rejected for GEMS. Quality-filtered
negative columns are retained; HCHO gap-filled flag classes are excluded.
This explicit filter is recorded with each file's version and variable in
JSON; quality flag meanings must not be transferred between products.

In `raster` and `overlay` sidecars, GEMS scan counts, footprint source, area CRS and
spatial aggregation are in the satellite layer's `method`, and the scan or
day in its `time`; the field names in this section describe the other
commands' sidecars.

GEMS JSON statistics, spatial summaries, and hotspots use the **unfilled,
unsmoothed** regional grid. Smoothing affects the map only and cannot create
new valid cells. Sidecars include `sensor`, `quantity`, the requested local
time, nominal UTC/local scan times, actual observation time ranges, filter
settings, file failures, and scan-count summaries. Window metadata retains
per-day diagnostics. Existing TROPOMI fields remain compatible; the boundary
policy block described above is additive.

GEMS `overlay` accepts an exact scan, a daily mean or a window. Station-hour
rules, default station variables and `time_matching` are described in
[Satellite and station overlays](#satellite-and-station-overlays).

## License

This project is distributed under the license in `LICENSE`.

## Publishing

The package version is derived from Git by `hatch-vcs`; do not add a static
`project.version` or make version-bump commits. The latest `vX.Y.Z` tag is the
stable version. Commits after it build as the next patch development series:

```text
v0.3.0           -> 0.3.0
first commit     -> 0.3.1.dev1
second commit    -> 0.3.1.dev2
v0.3.1           -> 0.3.1
```

GitHub Actions publishes every `main` push through the `pypi-dev` environment
and every `v*` tag through `pypi`. Configure two PyPI Trusted Publishers with
the same owner, repository, and workflow, differing only by environment:

```text
Owner: yaoyhu
Repository: rsplot
Workflow: publish.yml
Environment: pypi-dev
Environment: pypi
```

Leave `pypi-dev` automatic for continuous development uploads. Protect the
`pypi` GitHub environment with required reviewers so stable releases need an
explicit approval.

To make a stable release after the desired commit is on GitHub:

```bash
git tag -a v0.3.1 -m v0.3.1
git push github v0.3.1
```
