Tiling, Python SDK reference

TileService

Generate a grid of tiles covering a GeoJSON polygon.

Parameters:

Name	Type	Description	Default
`polygon`	`dict`	A GeoJSON Polygon object (`{"type": "Polygon", "coordinates": ...}`). Validated and winding-order-normalized on construction.	required
`logger`	`Logger`	Python logger instance.	required
`analysis_type`	`AnalysesName`	Reserved for future per-type tile size differentiation.	`None`
`max_tiles_override`	`int`	Override the default maximum number of non-empty tiles (100 by default). `None` keeps the default.	`None`

polygon instance-attribute

Python

polygon: dict = validate_polygon(polygon)

Validated GeoJSON Polygon.

points instance-attribute

Python

points: List[Point] = [
Point(latitude=pos[1], longitude=pos[0]) for pos in ring[:-1]
]

Internal polygon vertices as Point objects (lat/lon named fields).

logger instance-attribute

Python

logger: Logger = logger

Logger passed to the service.

analysis_type instance-attribute

Python

analysis_type: Optional[Union[AnalysesName, str]] = analysis_type

Analysis type the grid is generated for, or None.

tile_size instance-attribute

Python

tile_size: TileSize = TileSize(
x=self.config.inference_size_m, y=self.config.inference_size_m
)

Tile size in meters, from the tiling config.

max_non_empty instance-attribute

Python

max_non_empty: Optional[int] = max_tiles_override

The caller's override of the maximum non-empty tiles, or None.

config instance-attribute

Python

config: TilingConfig = get_tiling_config(
str(analysis_type) if analysis_type else None
)

Tiling configuration for the analysis type.

generate_tiles_for_polygon

Python

generate_tiles_for_polygon() -> List[List[Tile]]

Generate a grid of tiles covering the polygon's bounding box.

Returns:

Type	Description
`list[list[Tile]]`	2-D grid where `tiles[row][col]` is a `Tile`. Row 0 is the southernmost row; column 0 is the westernmost column. Each tile is marked `empty=True` if it does not intersect the polygon (neither centroid inside nor bbox overlap).

Raises:

Type	Description
`PolygonValidationError`	If the number of non-empty tiles exceeds the cap in force. The message names the tile count, the cap, the grid family and the `max_tiles_override` value that would clear it.

AreaPreview dataclass

Preview and cost estimate for an area analysis before submission.

would_bill_jobs, estimated_time_s and estimated_cost_tokens are priced from the planned number of jobs, never from tile_count alone. Grid analyses submit one job per tile, so would_bill_jobs == tile_count there. A facade (analysis_surfaces) run can split a tile into several billed sub-batches when its estimated sensor count exceeds the server cap. Passing payload= (with buildings= if the geometry is not embedded) runs the same offline batch split run_area submits, so would_bill_jobs reflects the real job count before any HTTP call.

Warnings

Without payload=, would_bill_jobs falls back to tile_count, which is safe when there is no facade geometry to preview yet but an under-estimate for a facade payload.

Attributes:

Name	Type	Description
`tile_count`	`int`	Number of tiles covering the polygon.
`estimated_time_s`	`float`	Estimated run time in seconds.
`estimated_cost_tokens`	`float`	Estimated cost in tokens: `would_bill_jobs` times `tokens_per_job`.
`would_bill_jobs`	`int or None`	Number of jobs the run would submit and bill.
`sensor_count`	`int or None`	Total sensors across the planned batches. `None` for a grid analysis (no facade batching) or when `payload=` was omitted.
`tokens_per_job`	`float or None`	The price of one job from the API price list.
`pricing_version`	`str or None`	The version of the price list, when it names one.
`pricing_source`	`str or None`	`"live"`, `"cached"` (fetched less than 20 minutes ago) or `"stale"` (the fetch failed and the last list was used).

AreaResult dataclass

Bases: _PhysicalGridMixin

Public result from an area analysis.

Attributes:

Name	Type	Description
`merged_grid`	`Any`	The merged grid, a READ-ONLY numpy array in the wire dtype of the run: `float16` (solar radiation, sky view factor, thermal comfort statistics, wind), `float32` (direct sun hours, daylight availability, and the class codes of a categorical result), `int16` (UTCI saved before 2026-10-07; UTCI is `float16` since then: stored value = physical value x `value_divisor`), or `float64` (a run that mixes dtypes). NaN is no value for the float dtypes; `valid` tells it for `int16`. Use `physical_grid()` for physical values: an old `int16` UTCI grid read without the divisor is 10 times too large; it handles both.
`value_divisor`	`int`	`int16` grids only: physical value = stored value / `value_divisor` (10 for UTCI/TCI). 1 for the float dtypes.
`valid`	`ndarray or None`	`int16` grids only: the validity bitmap (`uint8`, one bit per cell in row-major order, least significant bit first). `None` for the float dtypes.
`polygon`	`dict`	The source GeoJSON polygon.
`analysis_type`	`str`	Which analysis type was run.
`grid_shape`	`tuple[int, int]`	(num_rows, num_cols) of the merged grid.
`bounds`	`tuple[float, float, float, float] \	None`	Geographic extent of `merged_grid` as `(min_lng, min_lat, max_lng, max_lat)`. When the input polygon is not an integer multiple of `step_m`, the actual grid extent is padded north and east to the next step boundary; this field reports that true extent so visualisers can place the bitmap without a SW-anchored squash. `None` when no grid was produced (e.g. empty schedule).
`failed_jobs`	`list[str]`	Job IDs where the job status was Failed.
`skipped_jobs`	`list[str]`	Job IDs where download failed (succeeded job but network error), or jobs that were still pending/running when merge was called.
`total_jobs`	`int`	Total number of jobs.
`succeeded_jobs`	`int`	Number of jobs that succeeded.
`min_legend, max_legend`	`float or None`	The exact value range measured over `merged_grid`, not a fold of the per-tile backend estimates. `None` for a categorical result, an empty grid, or when the grid holds no finite value.
`legend`	`list[str] or None`	The class labels of a categorical result (wind-comfort classes), sorted and indexed by the class codes in `merged_grid`. `None` for a numeric result.
`failed_tiles`	`list[TileFailure]`	Per-tile failure records classified by `TileFailurePhase` (submit / compute / download / skipped). Same tile_id never appears twice; first-seen phase wins (submit > compute > download > skipped). Empty when every tile produced usable output.

to_dict

Python

to_dict() -> dict

Serialise to a plain dict.

merged_grid holds the PHYSICAL values as a nested list (None for no value), as before 1.0.0: a dict reader needs no divisor. value_dtype and value_divisor record the wire dtype, so from_dict() gives back the same dtype and the same values.

Returns:

Type	Description
`dict`	A JSON-compatible dict that `from_dict()` turns back into an equivalent result.

from_dict classmethod

Python

from_dict(data: dict) -> AreaResult

Reconstruct from a dict produced by to_dict().

Unknown keys are silently ignored for forward compatibility.

Parameters:

Name	Type	Description	Default
`data`	`dict`	A dict produced by `to_dict()`.	required

Returns:

Type	Description
`AreaResult`	The reconstructed result. `merged_grid` has the stored `value_dtype` (`float64` for a dict without one).

Raises:

Type	Description
`KeyError`	If a required key (`polygon`, `analysis_type` or `grid_shape`) is missing.

AreaSchedule dataclass

Schedule of submitted jobs for an area analysis.

Produced by run_area() and consumed by check_area_state(), merge_area_jobs(), and run_area_and_wait(). Use to_dict() and from_dict() to persist a schedule and resume it later.

Attributes:

Name	Type	Description
`jobs`	`dict[str, str]`	Mapping of tile_id to job_id.
`polygon`	`dict`	The source GeoJSON polygon.
`analysis_type`	`str`	Which analysis type was run.
`config_hash`	`str`	SHA-256 hash of the payload's config-relevant fields.
`tile_positions`	`dict[str, tuple[int, int]]`	Mapping of tile_id to (row, col) grid position.
`grid_shape`	`tuple[int, int]`	(num_rows, num_cols) of the tile grid.
`webhook_url`	`str or None`	Webhook URL used for this submission.
`webhook_events`	`tuple[str, ...] or None`	Webhook events subscribed to.
`failed_submissions`	`tuple[str, ...]`	Tile IDs where job submission failed in a way that is SAFE to retry -- the server either never saw the request or answered with a definitive rejection.
`uncertain_submissions`	`tuple[str, ...]`	Tile IDs whose submission outcome is UNKNOWN: the request may already have been accepted and queued server-side (a lost/timed-out response, or a 2xx reply whose body didn't parse into a job). Deliberately a SEPARATE bucket from `failed_submissions`, not a variant of it: `run_area(..., retry_from=schedule)` builds its resubmission set from `failed_submissions` alone, so an uncertain tile is never automatically resubmitted -- the SDK cannot tell whether that would create a second billed job, so it does not decide for the caller. Resolving one requires a deliberate step outside this field (check job history for the tile, then start a fresh, non-retry submission if nothing exists). It is carried forward unchanged across a `retry_from` run and can never appear in a retry's own result.
`config`	`TilingConfig or None`	The tiling configuration (tile size, step and context margins) the tiles were built with.
`submission_abort_status`	`int or None`	HTTP status that fail-fasted the submission batch, or `None` when submission ran to completion. Currently only 402 (insufficient credits): the condition is account-global, so the SDK stops submitting remaining tiles after the first one — those tiles land in `failed_submissions` without an HTTP call. Consumers should treat `402` as "don't retry, top up credits"; plain `failed_submissions` entries with status `None` keep their usual transient-retry semantics.
`surface_fields`	`bool`	`True` when the submitted payload carried facade or bring-your-own-sensor fields (`analysis_surfaces` / `sensor_points`); the merge uses it to choose the surface merge.
`buildings_hash`	`str or None`	Fingerprint of the buildings/geometries map that produced this schedule. Geometry drives sub-tile batch boundaries but is not part of `config_hash`, so the retry guard compares this separately. `None` on schedules built before the field existed.
`terrain_context_margin_m`	`float or None`	The terrain reach these tiles were sliced to, in metres — the FLOORED value actually used (`max(config.context_margin_m, requested)`), not the value passed to `run_area`. So a default solar run reads back `128.0`, not `0.0`. Guarded on retry and on `merge`. `None` on schedules built before the field existed.
`max_sensors_per_job`	`float or None`	The facade per-job cap that planned this schedule. Its unit depends on `batching_policy_version`: on an exact v2 schedule it is the caller's cap in RETAINED sensors, `None` for the default target; on a legacy v1 schedule it is the resolved estimate-policy cap. A missing saved policy version means legacy v1 for compatibility. Guarded on retry and on `merge` when present.
`batching_policy_version`	`int or None`	Facade batching policy that planned the batches: 2 is the exact retained-sensor policy (it requires complete `batch_membership` and `batch_sensor_counts`); `None` or 1 is the legacy estimate policy.
`batch_count_contract_version`	`int or None`	Version of the sensor-counting rules the batch sensor counts were computed under. A retry of a schedule counted under an older version is refused by name.
`batch_membership`	`dict[str, tuple[str, ...]] or None`	Building IDs in each facade batch, keyed by batch key (`{tile_id}#batch{i}`). `None` on a grid schedule.
`batch_sensor_counts`	`dict[str, int] or None`	Retained sensor count of each facade batch, keyed by batch key. `None` on a grid schedule.
`transport`	`str or None`	Transport the jobs were submitted with (`"json"` or `"binary"`). `None` on schedules built before the field existed.
`wire_version`	`int or None`	Binary wire version of the submission (`1` for the binary transport), `None` for a JSON submission.
`binary_acknowledgements`	`dict[str, dict] or None`	The server's acknowledgement of each binary submission, keyed by schedule key (tile ID or batch key). `None` for a JSON submission.
`weather_identity`	`str or None`	The weather these tiles submitted — the columns, the payload latitude and longitude and the window — as a digest, or `None` for an analysis that reads no weather array. `config_hash` covers none of that, so it alone tells two runs of one window against two climates apart. Guarded on retry and `merge`; never sent.
`schedule_contract_version`	`int or None`	Version of this client-side record; 4 is the run identity described under `weather_identity`. Versions 2 and 3 held an EPW FILE identity and are refused by name on a weather-bearing resume. `None` predates the field.
`site_identity`	`str or None`	Digest of the raw site inputs (buildings with their per-building overrides, trees, ground materials, context and terrain geometry). Guarded on retry and `merge`; never sent. `None` on schedules built before the field existed.
`run_id`	`str or None`	Random ID made once per schedule and kept across every retry of it. Client-side only; never sent.
`attempts`	`dict[str, int] or None`	Attempt number of the current job or submission of each schedule key; a missing key is attempt 1. Client-side only; never sent.
`submission_errors`	`dict[str, str] or None`	Why a key has no result, by schedule key: why the SDK stopped its submission (for example a tile the encoder refused, or HTTP 429 until the area timeout), or the server's error text of its failed job. Only keys that have a reason. Client-side only; never sent.
`failures`	`dict[str, dict] or None`	Why a key has no result, by schedule key: `{"kind": ..., "status": ...}` (`status` only when an HTTP answer decided it). The source of `TileFailure.kind` and `TileFailure.status`. Client-side only; never sent.

merge

Python

merge(other: AreaSchedule) -> AreaSchedule

Merge another schedule into this one (e.g. after retry).

Validates that both schedules refer to the same polygon (via fingerprint), analysis_type, and config_hash. Overlapping tile_ids in other override this schedule's jobs. Failures that are now covered by other are removed.

Parameters:

Name	Type	Description	Default
`other`	`AreaSchedule`	The retry schedule to merge in.	required

Returns:

Type	Description
`AreaSchedule`	A new merged schedule.

Raises:

Type	Description
`ValueError`	If polygon, analysis_type, or config_hash do not match.

to_dict

Python

to_dict() -> dict

Serialise to a plain dict for persistence.

Tuple fields are converted to lists for JSON compatibility.

Returns:

Type	Description
`dict`	A JSON-compatible dict that `from_dict()` turns back into an equal schedule.

from_dict classmethod

Python

from_dict(data: dict) -> AreaSchedule

Reconstruct from a dict produced by to_dict().

Unknown keys are silently ignored for forward compatibility.

Parameters:

Name	Type	Description	Default
`data`	`dict`	A dict produced by `to_dict()`.	required

Returns:

Type	Description
`AreaSchedule`	The reconstructed schedule.

Raises:

Type	Description
`KeyError`	If a required key (`jobs`, `polygon`, `analysis_type`, `config_hash` or `grid_shape`) is missing.
`ValueError`	If the saved batch records are inconsistent.

AreaState dataclass

Snapshot of area-level job status.

Produced by check_area_state() and consumed by run_area_and_wait() callbacks.

Attributes:

Name	Type	Description
`status`	`str`	Derived status: `"empty"` (no jobs), `"pending"`, `"running"`, `"completed"`, `"failed"`, or `"partial"`.
`job_states`	`dict[str, JobStatus]`	Mapping of job_id to its current status.
`succeeded`	`int`	Count of succeeded jobs.
`failed`	`int`	Count of failed jobs.
`running`	`int`	Count of running jobs.
`pending`	`int`	Count of pending jobs.
`total`	`int`	Total number of jobs.
`is_complete`	`bool`	True when all jobs are in a terminal state. Also True when the schedule has no job but has uncertain tiles: nothing is in flight and an uncertain tile is never resubmitted, so waiting cannot change the state. The merge then reports each uncertain tile.
`uncertain`	`int`	Count of tiles whose submission outcome is unknown: the SDK has no job id to poll for them. The merge reports each as a `TileFailure`; resolve them through job history.

from_job_states classmethod

Python

from_job_states(
job_states: Dict[str, JobStatus], *, uncertain: int = 0
) -> AreaState

Compute an AreaState from a mapping of job_id to JobStatus.

Status priority: 1. If no jobs -> "empty" (distinct from "completed"; submission may have failed wholesale or been short-circuited) 2. If all jobs pending -> "pending" 3. If any non-terminal job exists (pending or running) -> "running" 4. If all terminal and all succeeded -> "completed", or "partial" when a submission is uncertain 5. If all terminal and all failed -> "failed" 6. If all terminal with mixed results -> "partial"

Parameters:

Name	Type	Description	Default
`job_states`	`dict[str, JobStatus]`	Mapping of job_id to its current status.	required
`uncertain`	`int`	Number of tiles whose submission outcome is unknown. Default 0.	`0`

Returns:

Type	Description
`AreaState`	The derived snapshot.

AreaTimeoutError

Bases: Exception

Raised when run_area_and_wait exceeds its area_timeout.

Attributes:

Name	Type	Description
`area_state`	`AreaState`	The state snapshot at the time of timeout.
`message`	`str`	Human-readable timeout message.

TileGrid dataclass

Immutable wrapper around a 2-D grid of tiles.

Produced by tile generation for a polygon and consumed by downstream composable methods (run_area, get_by_tiles).

Tile IDs are deterministic UUIDs derived from the polygon geometry and grid position — the same polygon always produces the same IDs.

Attributes:

Name	Type	Description
`tiles`	`list[list[Tile]]`	2-D grid where `tiles[row][col]` is a `Tile`. Row 0 is the southernmost row; column 0 is the westernmost column.
`num_rows`	`int`	Number of rows in the grid.
`num_cols`	`int`	Number of columns in the grid.
`polygon`	`dict`	The source GeoJSON polygon used to generate this grid.
`config`	`TilingConfig or None`	The tiling configuration (tile size, step and context margins) the grid was generated with.

non_empty_tiles property

Python

non_empty_tiles: List[Tuple[int, int, Tile]]

Return non-empty tiles with their grid positions.

Returns:

Type	Description
`list[tuple[int, int, Tile]]`	Each element is `(row, col, tile)` for tiles where `tile.empty` is `False`.

TiledResult dataclass

Bases: _PhysicalGridMixin

Aggregated result from a tiled analysis run.

Attributes:

Name	Type	Description
`merged_grid`	`Any`	Merged, blended, clipped grid: a READ-ONLY numpy array in the wire dtype of the run (`float16`, `float32`, `int16` or `float64`; see `AreaResult.merged_grid`). Use `physical_grid()` for physical values. Typed as Any to avoid import-time numpy dependency.
`value_divisor`	`int`	`int16` grids only: physical value = stored value / `value_divisor`. 1 for the float dtypes.
`valid`	`ndarray or None`	`int16` grids only: the validity bitmap (`uint8`, one bit per cell, least significant bit first). `None` for the float dtypes, where NaN is no value.
`polygon`	`dict`	Original input GeoJSON polygon.
`tile_count`	`int`	Number of tiles that were executed.
`grid_shape`	`tuple[int, int]`	(rows, cols) of the merged grid.
`failed_tiles`	`list[TileFailure]`	Tiles that failed after all retries.
`skipped_tiles`	`list[str]`	Tile IDs that were skipped.
`execution_time`	`float`	Total wall-clock seconds for the tiled run.
`per_tile_results`	`list[[TileResult](#infrared_sdk.tiling.TileResult)]`	Raw per-tile results.
`analysis_type`	`str`	Which analysis type was run.
`min_legend, max_legend`	`float or None`	The exact value range measured over `merged_grid`, not a fold of the per-tile backend estimates. `None` for a categorical result, an empty grid, or when the grid holds no finite value.
`legend`	`list[str] or None`	The class labels of a categorical result (wind-comfort classes), sorted and indexed by the class codes in `merged_grid`. `None` for a numeric result.

TileResult dataclass

Raw result from a single analysis tile.

Attributes:

Name	Type	Description
`tile_id`	`str`	Unique identifier of the tile.
`row`	`int`	Row index in the tile grid.
`col`	`int`	Column index in the tile grid.
`data`	`dict or None`	The raw result payload for the tile, or `None` when the tile produced no result.