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z>2I)(AuWWT#%^kIPya$vwA^eksE?p|6wPWhkD*zEW*wRhX88C;?>q-v$CdezwJS5j z%7JRJ1if6F;DAKVOny6Xiqe>QGBR{HQ!=t4R5Q?o*oCC-MKg-#1e&X8E~EJy%^fr+ zFnI*cAqH1HfJQqfOwl`LcGjGkx$0kL7@n06M~^Kdf5I2Xq<;ai;37i+ diff --git a/docs/_sources/modules/models_hydrographnet.rst.txt b/docs/_sources/modules/models_hydrographnet.rst.txt deleted file mode 100644 index 58a32f90..00000000 --- a/docs/_sources/modules/models_hydrographnet.rst.txt +++ /dev/null @@ -1,39 +0,0 @@ -hydrographnet -============= - -Description ------------ - -``hydrographnet`` is a physics-informed graph neural network for flood forecasting with -interpretable KAN-style components, residual message passing, and delta-state decoding. - -The model summary follows Taghizadeh et al. (2025): -`Interpretable physics-informed graph neural networks for flood forecasting `_. - -In PyHazards, this module is built from the model registry and is typically used with the -ERA5-based hydrograph adapter ``load_hydrograph_data`` for end-to-end validation. - -Example of how to use it ------------------------- - -.. code-block:: python - - import torch - from pyhazards.data.load_hydrograph_data import load_hydrograph_data - from pyhazards.datasets import graph_collate - from pyhazards.models import build_model - - data = load_hydrograph_data("pyhazards/data/era5_subset", max_nodes=50) - sample = data.splits["train"].inputs[0] - batch = graph_collate([sample]) - - model = build_model( - name="hydrographnet", - task="regression", - node_in_dim=2, - edge_in_dim=3, - out_dim=1, - ) - - y = model(batch) - print(y.shape) diff --git a/docs/_sources/modules/models_wildfire_aspp.rst.txt b/docs/_sources/modules/models_wildfire_aspp.rst.txt deleted file mode 100644 index b5cca925..00000000 --- a/docs/_sources/modules/models_wildfire_aspp.rst.txt +++ /dev/null @@ -1,32 +0,0 @@ -wildfire_aspp -============= - -Description ------------ - -``wildfire_aspp`` is an explainable CNN segmentation model with an ASPP mechanism for next-day -wildfire spread prediction. - -The model summary follows Marjani et al. (2024): -`Application of Explainable Artificial Intelligence in Predicting Wildfire Spread: An ASPP-Enabled CNN Approach `_. - -In PyHazards, this module is built from the model registry and can be used directly for wildfire -segmentation experiments. - -Example of how to use it ------------------------- - -.. code-block:: python - - import torch - from pyhazards.models import build_model - - model = build_model( - name="wildfire_aspp", - task="segmentation", - in_channels=12, - ) - - x = torch.randn(2, 12, 64, 64) - logits = model(x) - print(logits.shape) # (2, 1, 64, 64) diff --git a/docs/_sources/pyhazards_datasets.rst.txt b/docs/_sources/pyhazards_datasets.rst.txt index 92356e6f..a62ec73a 100644 --- a/docs/_sources/pyhazards_datasets.rst.txt +++ b/docs/_sources/pyhazards_datasets.rst.txt @@ -81,42 +81,11 @@ Notes (MERRA-2) - ``--var T2M`` to choose the plotted surface variable (default: ``T2M``) -Dataloader (v3) +Dataloader --------------- -Minimal API with a structured request object for multi-source fusion -(e.g., FIRMS + ERA5). - -API -~~~ - -.. literalinclude:: ../../pyhazards/datasets/dataloader/README.md - :language: markdown - :start-after: ## API - :end-before: ## `GeoLoadInput` - -GeoLoadInput -~~~~~~~~~~~~ - -.. literalinclude:: ../../pyhazards/datasets/dataloader/README.md - :language: markdown - :start-after: ## `GeoLoadInput` - :end-before: ## Optional - -Optional fields -~~~~~~~~~~~~~~~ - -.. literalinclude:: ../../pyhazards/datasets/dataloader/README.md - :language: markdown - :start-after: ## Optional - :end-before: ## Example - -Example -~~~~~~~ - .. literalinclude:: ../../pyhazards/datasets/dataloader/README.md :language: markdown - :start-after: ## Example Example skeleton diff --git a/docs/pyhazards_datasets.html b/docs/pyhazards_datasets.html index f7e63a87..6629a6fa 100644 --- a/docs/pyhazards_datasets.html +++ b/docs/pyhazards_datasets.html @@ -355,13 +355,14 @@

Notes (MERRA-2) -

Dataloader (v3)

-

Minimal API with a structured request object for multi-source fusion -(e.g., FIRMS + ERA5).

-
-

API

-
```python
+

+
Dataloader

+
# Dataloader V3
+
+Minimal API with a structured request object.
+
+## API
+```python
 from dataloader_v3 import (
     GeoLoadInput,
     load_data,
@@ -370,35 +371,26 @@ 
API
to_torch_batch,
 )
 ```
-

-

-

-

-
GeoLoadInput

-
- `data_sources: list[str]`  
+
+## `GeoLoadInput` (required format)
+- `data_sources: list[str]`  
   Example: `["FIRMS", "ERA5"]`
 - `temporal_window: tuple[str, str]`  
   Format: `("YYYY-MM-DD", "YYYY-MM-DD")` or `("YYYY-MM-DD HH:MM:SS", "...")`
 - `area_of_interest_bbox: tuple[float, float, float, float]`  
   Order: `(min_lon, min_lat, max_lon, max_lat)`
-

-

-

-

-
Optional fields

-
- `spatial_resolution_deg: float = 0.1`
+
+## Optional
+- `spatial_resolution_deg: float = 0.1`
 - `root_dir: str = "/home/yangshuang"`
 - `synthetic_time: bool = False`
 - `temporal_cadence: str = "D"` (`"D"`, `"H"`, `"15min"`, ...)
 - `target_hazards: list[str] | None = None` (if set and no mapping, default code is `1`)
 - `label_source: str | None = None` (`"firms" | "noaa" | "mtbs"`, else auto-infer)
 - `label_mapping: dict[str, int] | None = None`
-

-

-

-

-
Example

-
```python
+
+## Example
+```python
 from dataloader_v3 import GeoLoadInput, load_data, save_sample_h5
 
 req = GeoLoadInput(
@@ -418,7 +410,6 @@ 
Example

 

 

-

Example skeleton

A “nice” skeleton should make it explicit what data you load and how it flows into @@ -546,13 +537,7 @@

Developer noteNotes (MERRA-2) -
  • Dataloader (v3) -
    • +
  • Dataloader
  • Example skeleton
  • Inspection entrypoints (convention for all datasets)
  • Developer note
    • diff --git a/docs/searchindex.js b/docs/searchindex.js index 2c818176..98bb6741 100644 --- a/docs/searchindex.js +++ b/docs/searchindex.js @@ -1 +1 @@ -Search.setIndex({"alltitles": {"API": [[21, "api"]], "Access": [[8, "access"], [9, "access"], [10, "access"], [11, "access"], [12, "access"], [13, "access"], [14, "access"], [15, "access"]], "Acknowledgments": [[27, "acknowledgments"]], "At-a-glance (Quick Facts)": [[8, null], [9, null], [10, null], [11, null], [12, null], [13, null], [14, null], [15, null]], "Basic Usage": [[26, "basic-usage"]], "Build a built-in model": [[24, "build-a-built-in-model"]], "Build and register custom model": [[24, "build-and-register-custom-model"]], "Core Components": [[17, "core-components"]], "Core Contributors": [[28, "core-contributors"]], "Core Team": [[28, null]], "Core classes": [[23, "core-classes"]], "Core modules": [[22, "core-modules"]], "Custom Module": [[17, "custom-module"]], "Data Characteristics": [[8, "data-characteristics"], [9, 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../../pyhazards/datasets/dataloader/README.md - :language: markdown - :start-after: ## API - :end-before: ## `GeoLoadInput` - -GeoLoadInput -~~~~~~~~~~~~ - -.. literalinclude:: ../../pyhazards/datasets/dataloader/README.md - :language: markdown - :start-after: ## `GeoLoadInput` - :end-before: ## Optional - -Optional fields -~~~~~~~~~~~~~~~ - -.. literalinclude:: ../../pyhazards/datasets/dataloader/README.md - :language: markdown - :start-after: ## Optional - :end-before: ## Example - -Example -~~~~~~~ - .. literalinclude:: ../../pyhazards/datasets/dataloader/README.md :language: markdown - :start-after: ## Example Example skeleton