diff --git a/.gitattributes b/.gitattributes index 8f61a8e..b41b949 100644 --- a/.gitattributes +++ b/.gitattributes @@ -1,2 +1,3 @@ # SCM syntax highlighting pixi.lock linguist-language=YAML linguist-generated=true +src/sweets/web/frontend/package-lock.json linguist-generated=true diff --git a/.gitignore b/.gitignore index af2c57d..32a6546 100644 --- a/.gitignore +++ b/.gitignore @@ -169,3 +169,4 @@ cython_debug/ *.egg-info .DS_Store *.pdf +docs/ifg_workflow_executed.* diff --git a/docs/ifg-workflow-test-guide.md b/docs/ifg-workflow-test-guide.md new file mode 100644 index 0000000..9d5ee88 --- /dev/null +++ b/docs/ifg-workflow-test-guide.md @@ -0,0 +1,148 @@ +# Running the IFG Workflow: Test Guide + +Quick reference for testing the `IfgWorkflow` on OPERA CSLC data. + +## 1. Create a config YAML + +The minimum config for an OPERA CSLC run: + +```yaml +work_dir: /path/to/output/dir +bbox: + - -118.2295 # xmin (west) + - 34.7939 # ymin (south) + - -116.5642 # xmax (east) + - 35.8195 # ymax (north) + +search: + kind: opera-cslc + out_dir: data + bbox: [-118.2295, 34.7939, -116.5642, 35.8195] + start: "2025-04-01T00:00:00" + end: "2025-06-01T00:00:00" + relativeOrbit: 64 + # Optional: pin burst IDs instead of deriving from bbox each run + burst_ids: + - t064_135521_iw1 + - t064_135521_iw2 + # ... (use opera_utils.get_burst_ids_for_frame(frame_id) to list them) + +network: + max_bandwidth: 2 # nearest-2 network (each date connects to 2 neighbors) + +crossmul: + lines_per_block: 512 + +stitch: + run_stitch: true + crop_to_bbox: true + run_burst_align: true # remove inter-burst seam artifacts + burst_align_degree: 0 # 0 = constant offset per burst; 1 = planar ramp + +unwrap: + run_unwrap: false + +overwrite: false +``` + +To get the burst IDs for a known OPERA DISP frame: + +```python +from opera_utils import get_burst_ids_for_frame +print(get_burst_ids_for_frame(16941)) +``` + +## 2. Run the workflow + +```bash +python -m sweets ifg-run sweets_ifg_config.yaml +``` + +### Re-running from a specific step + +``` +Step 1 — DEM/watermask download + CSLC download +Step 2 — Geometry stitching (LOS east/north/incidence angles) +Step 3 — Crossmul (per-burst complex IFGs + coherence) +Step 4 — Stitch (burst alignment + merge_by_date + wrapped phase) +Step 5 — Unwrap (snaphu, if enabled) +``` + +To skip download and re-run from crossmul onward: + +```bash +python -m sweets ifg-run sweets_ifg_config.yaml --starting-step 3 +``` + +To re-run only the stitch step (crossmul outputs already exist): + +```bash +python -m sweets ifg-run sweets_ifg_config.yaml --starting-step 4 +``` + +When re-running the stitch step, delete the existing stitched outputs first +so `overwrite: false` does not silently reuse them: + +```bash +find /interferograms/stitched -maxdepth 1 -name "*.tif" -delete +``` + +## 3. Output layout + +``` +/ + dem.tif + watermask.tif + geometry/ + los_east.tif los_north.tif incidence_angle.tif ... + data/ + + static_layers/ + interferograms/ + t064_135521_iw1/ + 20250403_20250415/ + 20250403_20250415_ifg.tif # complex64 crossmul output + 20250403_20250415_coherence.tif + ... + stitched/ + 20250403_20250415_ifg.tif # burst-aligned complex + 20250403_20250415_coherence.tif + 20250403_20250415_wrapped_phase.tif # np.angle(ifg), derived after stitch + burst_aligned/ + t064_135521_iw1__20250403_20250415_ifg.aligned.tif + ... +``` + +Key design decisions: +- Crossmul saves **complex64** `_ifg.tif` (not wrapped phase) so that + `merge_by_date` interpolates real+imag independently, avoiding ±π + discontinuities at burst seams. +- Wrapped phase is derived with `np.angle()` **after** stitching. +- Burst alignment runs **per date pair** (27 bursts each), not across all + pairs at once — passing all pairs together caused same-geography bursts + from different epochs to be compared as "overlapping", producing garbage + corrections. + +## 4. Plot and QA + +```python +from sweets.plotting import plot_ifg_pairs, save_ifg_qa_metrics +from pathlib import Path + +stitch_dir = Path("/interferograms/stitched") + +# Thumbnail grid of wrapped phase + coherence +plot_ifg_pairs(stitch_dir, max_pairs=13, output_path="ifgs.png") + +# Per-pair coherence metrics + JSON sidecar +save_ifg_qa_metrics(stitch_dir, output_path="qa.png") +``` + +## 5. Test dataset (frame 16941) + +- **Frame**: OPERA DISP frame 16941, T064 ascending, S California / Mojave +- **AOI**: `POLYGON((-118.2295 34.7939,-116.5642 34.7939,-116.5642 35.8195,-118.2295 35.8195,-118.2295 34.7939))` +- **Dates**: 2025-04-01 to 2025-06-01 (13 acquisitions, 6-day repeat) +- **Bursts**: 27 (9 frames × 3 IW subswaths) +- **Data on**: `/Volumes/WD_BLACK_SN7100_4TB/Documents/Learning/sweets-testing/sweets-f16941/` +- **Config**: `sweets_ifg_config.yaml` in the same directory diff --git a/docs/ifg_workflow.ipynb b/docs/ifg_workflow.ipynb new file mode 100644 index 0000000..aaaafe2 --- /dev/null +++ b/docs/ifg_workflow.ipynb @@ -0,0 +1,452 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "547f49d14a494af5", + "metadata": {}, + "source": "# sweets IFG Workflow — Interactive Notebook\n\nInteractive configuration and step-by-step execution of the `IfgWorkflow`\npipeline, designed for JupyterHub and standalone Jupyter environments.\n\n**What this notebook does**:\n\n1. Let you set up an AOI, date range, and processing options via widgets\n2. Build and save a `sweets_ifg_config.yaml`\n3. Run each workflow step (download → geometry → crossmul → stitch → unwrap)\n4. Display the stitched interferogram thumbnails\n\nDefault values are pre-loaded for **OPERA DISP frame 16941** (T064 ascending,\nS California / Mojave, April–June 2025).\n\n---\n> **Requirements**: `sweets`, `ipywidgets`, `folium` (all in the pixi `default`\n> environment). Run with:\n> ```\n> pixi run jupyter lab\n> ```" + }, + { + "cell_type": "code", + "execution_count": null, + "id": "85a3c14f724e4422", + "metadata": {}, + "outputs": [], + "source": [ + "from __future__ import annotations\n", + "\n", + "import io\n", + "import sys\n", + "from pathlib import Path\n", + "from datetime import date\n", + "\n", + "import ipywidgets as w\n", + "import folium\n", + "from IPython.display import display, clear_output\n", + "\n", + "# Make sure sweets is importable (editable install or src on sys.path)\n", + "_src = Path.cwd().parent / \"src\"\n", + "if _src.exists() and str(_src) not in sys.path:\n", + " sys.path.insert(0, str(_src))" + ] + }, + { + "cell_type": "markdown", + "id": "bdbcf1bda1a34b50", + "metadata": {}, + "source": "## 1. Configure the Workflow\n\nThe tabs below cover every option. Values are pre-filled for frame 16941 —\nchange what you need, then proceed to **Section 2** to build the config." + }, + { + "cell_type": "code", + "execution_count": null, + "id": "380a1dbdc79d46b4", + "metadata": {}, + "outputs": [], + "source": [ + "# ── Frame 16941 defaults (change _WORK_DIR to your own output directory) ──────\n", + "import os as _os\n", + "_WORK_DIR = _os.path.join(_os.path.expanduser(\"~\"), \"sweets-output\", \"frame-16941\")\n", + "_BBOX = (-118.2295, 34.7939, -116.5642, 35.8195)\n", + "_START = date(2025, 4, 1)\n", + "_END = date(2025, 6, 1)\n", + "_TRACK = 64\n", + "_BURST_IDS = \"\\n\".join([\n", + " \"t064_135521_iw1\", \"t064_135521_iw2\", \"t064_135521_iw3\",\n", + " \"t064_135522_iw1\", \"t064_135522_iw2\", \"t064_135522_iw3\",\n", + " \"t064_135523_iw1\", \"t064_135523_iw2\", \"t064_135523_iw3\",\n", + " \"t064_135524_iw1\", \"t064_135524_iw2\", \"t064_135524_iw3\",\n", + " \"t064_135525_iw1\", \"t064_135525_iw2\", \"t064_135525_iw3\",\n", + " \"t064_135526_iw1\", \"t064_135526_iw2\", \"t064_135526_iw3\",\n", + " \"t064_135527_iw1\", \"t064_135527_iw2\", \"t064_135527_iw3\",\n", + " \"t064_135528_iw1\", \"t064_135528_iw2\", \"t064_135528_iw3\",\n", + " \"t064_135529_iw1\", \"t064_135529_iw2\", \"t064_135529_iw3\",\n", + "])\n", + "\n", + "# ── Shared widget styles ──────────────────────────────────────────────────────\n", + "_S = {\"description_width\": \"130px\"}\n", + "_L = w.Layout(width=\"320px\")\n", + "_LW = w.Layout(width=\"460px\")\n", + "\n", + "# ── Tab 1: AOI ────────────────────────────────────────────────────────────────\n", + "w_west = w.BoundedFloatText(value=_BBOX[0], min=-180, max=180, step=0.0001,\n", + " description=\"West (lon)\", style=_S, layout=_L)\n", + "w_south = w.BoundedFloatText(value=_BBOX[1], min=-90, max=90, step=0.0001,\n", + " description=\"South (lat)\", style=_S, layout=_L)\n", + "w_east = w.BoundedFloatText(value=_BBOX[2], min=-180, max=180, step=0.0001,\n", + " description=\"East (lon)\", style=_S, layout=_L)\n", + "w_north = w.BoundedFloatText(value=_BBOX[3], min=-90, max=90, step=0.0001,\n", + " description=\"North (lat)\", style=_S, layout=_L)\n", + "\n", + "_map_out = w.Output(layout=w.Layout(height=\"360px\"))\n", + "\n", + "def _render_map(*_):\n", + " lat_c = (w_south.value + w_north.value) / 2\n", + " lon_c = (w_west.value + w_east.value) / 2\n", + " m = folium.Map(location=[lat_c, lon_c], zoom_start=7)\n", + " folium.Rectangle(\n", + " bounds=[[w_south.value, w_west.value], [w_north.value, w_east.value]],\n", + " color=\"#4285F4\", fill=True, fill_opacity=0.15,\n", + " tooltip=(f\"W={w_west.value:.4f} S={w_south.value:.4f} \"\n", + " f\"E={w_east.value:.4f} N={w_north.value:.4f}\"),\n", + " ).add_to(m)\n", + " with _map_out:\n", + " clear_output(wait=True)\n", + " display(m)\n", + "\n", + "for _wgt in (w_west, w_south, w_east, w_north):\n", + " _wgt.observe(_render_map, names=\"value\")\n", + "_render_map()\n", + "\n", + "_blank = w.Label(\"\")\n", + "_aoi_compass = w.GridBox(\n", + " [_blank, w_north, _blank,\n", + " w_west, _blank, w_east,\n", + " _blank, w_south, _blank],\n", + " layout=w.Layout(\n", + " grid_template_rows=\"auto auto auto\",\n", + " grid_template_columns=\"1fr 1fr 1fr\",\n", + " grid_gap=\"6px\",\n", + " ),\n", + ")\n", + "tab_aoi = w.VBox([\n", + " w.HTML(\"

Bounding box (decimal degrees)

\"),\n", + " _aoi_compass,\n", + " w.HTML(\"

Map preview

\"),\n", + " _map_out,\n", + "])\n", + "\n", + "# ── Tab 2: Search & Download ──────────────────────────────────────────────────\n", + "w_source = w.Dropdown(\n", + " options=[\"opera-cslc\", \"safe\", \"nisar-gslc\"], value=\"opera-cslc\",\n", + " description=\"Source type\", style=_S, layout=_L,\n", + ")\n", + "w_start = w.DatePicker(value=_START, description=\"Start date\", style=_S, layout=_L)\n", + "w_end = w.DatePicker(value=_END, description=\"End date\", style=_S, layout=_L)\n", + "w_track = w.BoundedIntText(\n", + " value=_TRACK, min=1, max=175, step=1,\n", + " description=\"Rel. orbit\", style=_S, layout=_L,\n", + ")\n", + "w_burst_ids = w.Textarea(\n", + " value=_BURST_IDS,\n", + " description=\"Burst IDs\",\n", + " placeholder=\"One burst ID per line. Leave empty to derive from bbox.\",\n", + " style={\"description_width\": \"90px\"},\n", + " layout=w.Layout(width=\"500px\", height=\"160px\"),\n", + ")\n", + "w_data_dir = w.Text(value=\"data\", description=\"Data dir\", style=_S, layout=_L)\n", + "\n", + "tab_search = w.VBox([\n", + " w.HTML(\"

Source

\"),\n", + " w_source,\n", + " w.HTML(\"

Date range

\"),\n", + " w_start, w_end,\n", + " w.HTML(\"

Track & burst selection

\"),\n", + " w_track, w_burst_ids,\n", + " w.HTML(\"

Download directory

\"),\n", + " w_data_dir,\n", + "])\n", + "\n", + "# ── Tab 3: Processing options ─────────────────────────────────────────────────\n", + "# Network\n", + "w_bandwidth = w.BoundedIntText(\n", + " value=2, min=0, max=20,\n", + " description=\"Max bandwidth\",\n", + " style=_S, layout=_L,\n", + ")\n", + "w_ref_date = w.Text(\n", + " value=\"\", placeholder=\"YYYY-MM-DD (optional)\",\n", + " description=\"Ref. date\", style=_S, layout=_L,\n", + ")\n", + "w_max_tbl = w.BoundedFloatText(\n", + " value=0.0, min=0.0, step=6.0,\n", + " description=\"Max Δt (days)\", style=_S, layout=_L,\n", + ")\n", + "\n", + "# Crossmul\n", + "w_az_looks = w.BoundedIntText(value=10, min=1, description=\"Az. looks\", style=_S, layout=_L)\n", + "w_rg_looks = w.BoundedIntText(value=40, min=1, description=\"Rg. looks\", style=_S, layout=_L)\n", + "\n", + "# Stitch\n", + "w_run_stitch = w.Checkbox(value=True, description=\"Run stitch\")\n", + "w_crop_bbox = w.Checkbox(value=True, description=\"Crop to bbox\")\n", + "w_burst_align = w.Checkbox(value=True, description=\"Burst alignment\")\n", + "w_align_deg = w.Dropdown(\n", + " options=[(0, 0), (1, 1)], value=0,\n", + " description=\"Align degree\",\n", + " style=_S, layout=w.Layout(width=\"240px\"),\n", + ")\n", + "\n", + "# Unwrap\n", + "w_run_unwrap = w.Checkbox(value=False, description=\"Run unwrap\")\n", + "w_unwrap_method = w.Dropdown(\n", + " options=[\"snaphu\", \"spurt\", \"whirlwind\"], value=\"snaphu\",\n", + " description=\"Method\", style=_S, layout=_L,\n", + ")\n", + "w.dlink((w_run_unwrap, \"value\"), (w_unwrap_method, \"disabled\"), lambda v: not v)\n", + "w_unwrap_method.disabled = True\n", + "\n", + "tab_proc = w.VBox([\n", + " w.HTML(\"

Interferogram network

\"),\n", + " w_bandwidth, w_ref_date, w_max_tbl,\n", + " w.HTML(\"

Crossmul (multilooking)

\"),\n", + " w.HBox([w_az_looks, w_rg_looks]),\n", + " w.HTML(\"

Stitch

\"),\n", + " w.HBox([w_run_stitch, w_crop_bbox, w_burst_align]),\n", + " w_align_deg,\n", + " w.HTML(\"

Unwrap

\"),\n", + " w.HBox([w_run_unwrap, w_unwrap_method]),\n", + "])\n", + "\n", + "# ── Tab 4: Output ─────────────────────────────────────────────────────────────\n", + "w_work_dir = w.Text(\n", + " value=_WORK_DIR,\n", + " description=\"Work dir\",\n", + " style={\"description_width\": \"80px\"},\n", + " layout=w.Layout(width=\"640px\"),\n", + ")\n", + "w_overwrite = w.Checkbox(value=False, description=\"Overwrite existing outputs\")\n", + "tab_output = w.VBox([\n", + " w.HTML(\"

Working directory

\"),\n", + " w_work_dir, w_overwrite,\n", + "])\n", + "\n", + "# ── Tabbed layout ─────────────────────────────────────────────────────────────\n", + "_tabs = w.Tab([tab_aoi, tab_search, tab_proc, tab_output])\n", + "for _i, _t in enumerate([\"AOI\", \"Search & Download\", \"Processing\", \"Output\"]):\n", + " _tabs.set_title(_i, _t)\n", + "\n", + "display(_tabs)" + ] + }, + { + "cell_type": "markdown", + "id": "b2038f40cc454012", + "metadata": {}, + "source": "## 2. Build & Save Config\n\nClick **Build config** to validate the settings and preview the YAML.\nClick **Save YAML** to write `sweets_ifg_config.yaml` inside your work directory." + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9e750eb9d23446c2", + "metadata": {}, + "outputs": [], + "source": [ + "import pydantic\n", + "from sweets.ifg import IfgWorkflow\n", + "\n", + "_out_cfg = w.Output()\n", + "_btn_build = w.Button(description=\"Build config\", button_style=\"info\", icon=\"check\")\n", + "_btn_save = w.Button(description=\"Save YAML\", button_style=\"success\", icon=\"save\")\n", + "\n", + "workflow: IfgWorkflow | None = None # shared state; set by on_build\n", + "\n", + "\n", + "def _collect() -> dict:\n", + " burst_ids = [b.strip() for b in w_burst_ids.value.strip().splitlines() if b.strip()]\n", + " cfg: dict = {\n", + " \"work_dir\": w_work_dir.value,\n", + " \"bbox\": [w_west.value, w_south.value, w_east.value, w_north.value],\n", + " \"search\": {\n", + " \"kind\": w_source.value,\n", + " \"out_dir\": w_data_dir.value,\n", + " \"start\": str(w_start.value),\n", + " \"end\": str(w_end.value),\n", + " },\n", + " \"network\": {\"max_bandwidth\": w_bandwidth.value},\n", + " \"crossmul\": {\"looks\": [w_az_looks.value, w_rg_looks.value]},\n", + " \"stitch\": {\n", + " \"run_stitch\": w_run_stitch.value,\n", + " \"crop_to_bbox\": w_crop_bbox.value,\n", + " \"run_burst_align\": w_burst_align.value,\n", + " \"burst_align_degree\": int(w_align_deg.value),\n", + " },\n", + " \"unwrap\": {\n", + " \"run_unwrap\": w_run_unwrap.value,\n", + " \"unwrap_method\": w_unwrap_method.value,\n", + " },\n", + " \"overwrite\": w_overwrite.value,\n", + " }\n", + " if w_track.value:\n", + " cfg[\"search\"][\"track\"] = w_track.value\n", + " if burst_ids:\n", + " cfg[\"search\"][\"burst_ids\"] = burst_ids\n", + " if w_ref_date.value.strip():\n", + " cfg[\"network\"][\"reference_date\"] = w_ref_date.value.strip()\n", + " if w_max_tbl.value > 0:\n", + " cfg[\"network\"][\"max_temporal_baseline\"] = float(w_max_tbl.value)\n", + " return cfg\n", + "\n", + "\n", + "def _on_build(b):\n", + " global workflow\n", + " _out_cfg.clear_output(wait=True)\n", + " cfg = _collect()\n", + " try:\n", + " workflow = IfgWorkflow(**cfg)\n", + " buf = io.StringIO()\n", + " workflow.to_yaml(buf)\n", + " yaml_str = buf.getvalue()\n", + " with _out_cfg:\n", + " print(\"Config valid! YAML preview:\\n\" + \"─\" * 60)\n", + " print(yaml_str)\n", + " except pydantic.ValidationError as exc:\n", + " with _out_cfg:\n", + " print(f\"Validation error:\\n{exc}\")\n", + "\n", + "\n", + "def _on_save(b):\n", + " _out_cfg.clear_output(wait=True)\n", + " if workflow is None:\n", + " with _out_cfg:\n", + " print(\"Click 'Build config' first.\")\n", + " return\n", + " cfg_path = Path(w_work_dir.value) / \"sweets_ifg_config.yaml\"\n", + " cfg_path.parent.mkdir(parents=True, exist_ok=True)\n", + " workflow.save(cfg_path)\n", + " with _out_cfg:\n", + " print(f\"Saved: {cfg_path}\")\n", + "\n", + "\n", + "_btn_build.on_click(_on_build)\n", + "_btn_save.on_click(_on_save)\n", + "\n", + "# Auto-build on first load so the YAML preview is visible without clicking\n", + "_on_build(None)\n", + "\n", + "display(w.HBox([_btn_build, _btn_save]), _out_cfg)" + ] + }, + { + "cell_type": "markdown", + "id": "06da5c8c9ee247d6", + "metadata": {}, + "source": "## 3. Run the Workflow\n\nSelect a starting step and click **Run**. All steps from the selected point\nonward will execute in sequence.\n\n| Step | What happens |\n|------|-------------|\n| 1 — Download | DEM, water mask, OPERA CSLCs |\n| 2 — Geometry | Stitch CSLC-STATIC look-angle layers |\n| 3 — Crossmul | Per-burst multilooked interferograms |\n| 4 — Stitch | Burst-align + merge to single frame |\n| 5 — Unwrap | SNAPHU/SPURT (only if `run_unwrap=True`) |\n\n> **Tip**: If data already exists, start from step 3 or 4 to skip the download." + }, + { + "cell_type": "code", + "execution_count": null, + "id": "de4592284a5e462a", + "metadata": {}, + "outputs": [], + "source": [ + "_out_run = w.Output(layout=w.Layout(\n", + " border=\"1px solid #ccc\",\n", + " height=\"400px\",\n", + " overflow_y=\"scroll\",\n", + " padding=\"6px\",\n", + "))\n", + "_step_sel = w.BoundedIntText(\n", + " value=4, min=1, max=5, step=1,\n", + " description=\"Starting step\",\n", + " style={\"description_width\": \"110px\"},\n", + " layout=w.Layout(width=\"240px\"),\n", + ")\n", + "_btn_run = w.Button(\n", + " description=\"Run workflow\",\n", + " button_style=\"danger\",\n", + " icon=\"play\",\n", + " layout=w.Layout(width=\"160px\"),\n", + ")\n", + "\n", + "def _on_run(b):\n", + " _out_run.clear_output(wait=True)\n", + " if workflow is None:\n", + " with _out_run:\n", + " print(\"Build and save config first (Section 2).\")\n", + " return\n", + " _btn_run.disabled = True\n", + " _btn_run.description = \"Running...\"\n", + " try:\n", + " with _out_run:\n", + " workflow.run(starting_step=_step_sel.value)\n", + " finally:\n", + " _btn_run.disabled = False\n", + " _btn_run.description = \"Run workflow\"\n", + "\n", + "_btn_run.on_click(_on_run)\n", + "\n", + "display(\n", + " w.VBox([\n", + " w.HBox([_step_sel, _btn_run]),\n", + " w.HTML(\"Output log\"),\n", + " _out_run,\n", + " ])\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "4553bcdd51c84a8b", + "metadata": {}, + "source": "## 4. View Results\n\nAfter the workflow finishes, run this cell to display wrapped-phase and\ncoherence thumbnails for all stitched date pairs." + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b9d28a60487d4d17", + "metadata": {}, + "outputs": [], + "source": [ + "import matplotlib\n", + "matplotlib.use(\"Agg\") # safe for JupyterHub environments without a GUI display\n", + "import matplotlib.pyplot as plt\n", + "from IPython.display import display as _ipy_display\n", + "from sweets.plotting import plot_ifg_pairs\n", + "\n", + "_stitch_dir = Path(w_work_dir.value) / \"interferograms\" / \"stitched\"\n", + "\n", + "if not _stitch_dir.exists():\n", + " print(f\"Stitch directory not found: {_stitch_dir}\")\n", + " print(\"Run the workflow (step 4) first.\")\n", + "else:\n", + " fig = plot_ifg_pairs(_stitch_dir, max_pairs=13, subsample=3)\n", + " _ipy_display(fig) # embeds the figure inline (works with Agg backend)\n", + " plt.close(fig)\n", + " print(f\"Plotted from: {_stitch_dir}\")" + ] + }, + { + "cell_type": "markdown", + "id": "68296ddccb004cdb", + "metadata": {}, + "source": "## Appendix: Programmatic Usage\n\nYou can also create and run the workflow entirely without the widgets:" + }, + { + "cell_type": "code", + "execution_count": null, + "id": "86be37ecb8b94765", + "metadata": {}, + "outputs": [], + "source": [ + "# Construct directly from a YAML file saved in Section 2\n", + "# (or hand-craft the dict here)\n", + "\n", + "\n", + "wf = IfgWorkflow.load(\n", + " Path(w_work_dir.value) / \"sweets_ifg_config.yaml\"\n", + ")\n", + "\n", + "# Inspect any field\n", + "print(\"Pairs in network:\", wf.network.max_bandwidth, \"nearest-neighbor(s)\")\n", + "print(\"Crossmul looks:\", wf.crossmul.looks)\n", + "print(\"Burst alignment:\", wf.stitch.run_burst_align)\n", + "\n", + "# Run from stitch step\n", + "# wf.run(starting_step=4)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "name": "python", + "version": "3.11.0" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/pixi.lock b/pixi.lock index c491bdc..99ff945 100644 --- a/pixi.lock +++ b/pixi.lock @@ -1,129 +1,74 @@ -version: 6 +version: 7 +platforms: +- name: linux-64 +- name: osx-arm64 environments: - 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Use `pixi run -e web sweets-server` instead of +# remembering the host/port flags. +sweets-server = "sweets server --reload" +# Frontend dev server. Vite proxies /api -> backend on :8000. +web-dev = { cmd = "npm run dev", cwd = "src/sweets/web/frontend" } +# Install npm deps. Run this once before web-dev / web-build. +web-install = { cmd = "npm install", cwd = "src/sweets/web/frontend" } +# Production build -> src/sweets/web/frontend/dist (served by FastAPI). +web-build = { cmd = "npm run build", cwd = "src/sweets/web/frontend" } +# Refresh docs/web/screenshots/. Builds the frontend, boots uvicorn, drives +# Playwright through every tab, kills the server. Requires `playwright +# install chromium` once. +web-screenshots = "python scripts/web_screenshots.py" + [tool.pixi.feature.plotting.dependencies] cartopy = "*" matplotlib = "*" @@ -227,6 +257,13 @@ default = { features = ["test", "plotting", "cpu"], solve-group = "default" } test = { features = ["test", "plotting", "cpu"], solve-group = "default" } plotting = { features = ["plotting", "cpu"], solve-group = "default" } minimal = { features = ["cpu"], solve-group = "default" } +# `web` adds the FastAPI backend + React/Vite/node toolchain on top of the +# default scientific stack. Run `pixi install -e web` once, then `pixi run +# -e web sweets-server` to launch uvicorn. +web = { features = ["test", "plotting", "cpu", "web"], solve-group = "default" } +# `all` mirrors `default` + web — a convenient catch-all for users who +# want everything in one solve. +all = { features = ["test", "plotting", "cpu", "web"], solve-group = "default" } # GPU environment: same extras as `default` but swaps isce3 -> isce3-cuda. # `solve-group` is deliberately separate so pixi doesn't try to reconcile # the CPU and GPU isce3 builds in a single resolution. diff --git a/scripts/compare_burst_alignment.py b/scripts/compare_burst_alignment.py new file mode 100644 index 0000000..7596ca1 --- /dev/null +++ b/scripts/compare_burst_alignment.py @@ -0,0 +1,213 @@ +"""Stitch per-burst IFGs with and without burst alignment, then plot a comparison. + +Writes: + /interferograms/stitched_no_align/ — plain merge_by_date + /interferograms/stitched_aligned/ — with sweets burst alignment + /burst_align_comparison.png — full-frame side-by-side wrapped phase + /burst_align_seam_zoom.png — zoomed seam + difference panel +""" + +from __future__ import annotations + +from pathlib import Path + +import matplotlib.pyplot as plt +import numpy as np +from dolphin.io import load_gdal +from dolphin.stitching import merge_by_date +from opera_utils import group_by_date + +from sweets._burst_alignment import align_bursts + +BASE = Path( + "/Volumes/WD_BLACK_SN7100_4TB/Documents/Learning/sweets-testing/sweets-f16941" +) +IFG_DIR = BASE / "interferograms" +# Number of pairs to show in the full-frame comparison figure. +N_SHOW = 4 +# Half-height (rows) of the seam zoom window. +SEAM_HALF_HEIGHT = 60 + + +def _collect_burst_ifgs() -> list[Path]: + return sorted(p for p in IFG_DIR.glob("*/*/*_ifg.tif") if "stitched" not in p.parts) + + +def _stitched_tifs(out_dir: Path) -> list[Path]: + return sorted(p for p in out_dir.glob("*.tif") if "burst_aligned" not in str(p)) + + +def stitch_no_align(ifg_files: list[Path], out_dir: Path) -> list[Path]: + out_dir.mkdir(parents=True, exist_ok=True) + merge_by_date(ifg_files, output_dir=out_dir, driver="GTiff") + return _stitched_tifs(out_dir) + + +def stitch_aligned(ifg_files: list[Path], out_dir: Path) -> list[Path]: + out_dir.mkdir(parents=True, exist_ok=True) + align_dir = out_dir / "burst_aligned" + align_dir.mkdir(exist_ok=True) + + aligned: list[Path] = [] + for _dates, group in group_by_date(ifg_files).items(): + out, _ = align_bursts(group, align_dir, degree=0) + aligned.extend(out) + + merge_by_date(aligned, output_dir=out_dir, driver="GTiff") + return _stitched_tifs(out_dir) + + +def _wrapped_phase(ifg_path: Path) -> np.ndarray: + arr = load_gdal(ifg_path) + phase = np.angle(arr) + phase[arr == 0] = np.nan + return phase + + +def _wrap(x: np.ndarray) -> np.ndarray: + return (x + np.pi) % (2 * np.pi) - np.pi + + +def _find_seam_rows(diff: np.ndarray, n_seams: int = 3) -> list[int]: + """Return row indices with the highest column-wise phase variance in diff.""" + valid = np.where(~np.isnan(diff), diff, 0.0) + # Row-wise absolute mean — seams appear as sudden jumps so use abs mean. + row_signal = np.nanmean(np.abs(valid), axis=1) + # Smooth to avoid picking two adjacent rows from the same seam. + kernel = np.ones(SEAM_HALF_HEIGHT) / SEAM_HALF_HEIGHT + smoothed = np.convolve(row_signal, kernel, mode="same") + # Find local maxima separated by at least SEAM_HALF_HEIGHT rows. + peaks = [] + min_sep = SEAM_HALF_HEIGHT * 2 + for _ in range(n_seams): + r = int(np.argmax(smoothed)) + peaks.append(r) + lo = max(0, r - min_sep) + hi = min(len(smoothed), r + min_sep) + smoothed[lo:hi] = 0.0 + return sorted(peaks) + + +def plot_comparison( + no_align_ifgs: list[Path], + aligned_ifgs: list[Path], + out_png: Path, + n_show: int = N_SHOW, +) -> None: + indices = np.linspace(0, len(no_align_ifgs) - 1, n_show, dtype=int) + pairs_no = [no_align_ifgs[i] for i in indices] + stem_to_aligned = {p.stem: p for p in aligned_ifgs} + pairs_al = [stem_to_aligned[p.stem] for p in pairs_no if p.stem in stem_to_aligned] + pairs_no = [p for p in pairs_no if p.stem in stem_to_aligned] + + fig, axes = plt.subplots( + n_show, 2, figsize=(12, 3.5 * n_show), constrained_layout=True + ) + if n_show == 1: + axes = axes[np.newaxis, :] + + for row, (p_no, p_al) in enumerate(zip(pairs_no, pairs_al)): + dates = p_no.stem + for col, (path, label) in enumerate( + [(p_no, "no alignment"), (p_al, "burst aligned")] + ): + phase = _wrapped_phase(path) + ax = axes[row, col] + row_im = ax.imshow( + phase, cmap="RdBu", vmin=-np.pi, vmax=np.pi, aspect="auto" + ) + ax.set_title(f"{dates} [{label}]", fontsize=9) + ax.axis("off") + if col == 1: + fig.colorbar(row_im, ax=axes[row, :], label="phase (rad)", shrink=0.6) + + fig.suptitle("Burst alignment comparison — wrapped phase", fontsize=11) + fig.savefig(out_png, dpi=150) + print(f"Saved {out_png}") + + +def plot_seam_zoom( + no_align_ifgs: list[Path], + aligned_ifgs: list[Path], + out_png: Path, + pair_index: int = 0, + n_seams: int = 3, +) -> None: + """Plot zoomed windows around detected burst seams for one pair. + + Each seam row shows: no-align | aligned | wrapped difference (aligned - no-align). + """ + stem_to_aligned = {p.stem: p for p in aligned_ifgs} + p_no = no_align_ifgs[pair_index] + p_al = stem_to_aligned[p_no.stem] + dates = p_no.stem + + phase_no = _wrapped_phase(p_no) + phase_al = _wrapped_phase(p_al) + diff = _wrap(phase_al - phase_no) + + seam_rows = _find_seam_rows(diff, n_seams=n_seams) + n_rows = len(seam_rows) + nrows_img, ncols_img = phase_no.shape + + fig, axes = plt.subplots( + n_rows, 3, figsize=(14, 4 * n_rows), constrained_layout=True + ) + if n_rows == 1: + axes = axes[np.newaxis, :] + + for row, sr in enumerate(seam_rows): + r0 = max(0, sr - SEAM_HALF_HEIGHT) + r1 = min(nrows_img, sr + SEAM_HALF_HEIGHT) + + crops = { + "no alignment": phase_no[r0:r1, :], + "burst aligned": phase_al[r0:r1, :], + "difference (aligned - no-align)": diff[r0:r1, :], + } + cmaps = ["RdBu", "RdBu", "PiYG"] + vlims = [(-np.pi, np.pi), (-np.pi, np.pi), (-np.pi, np.pi)] + + for col, (label, crop) in enumerate(crops.items()): + ax = axes[row, col] + im = ax.imshow( + crop, + cmap=cmaps[col], + vmin=vlims[col][0], + vmax=vlims[col][1], + aspect="auto", + ) + ax.set_title(label, fontsize=9) + ax.axhline(SEAM_HALF_HEIGHT, color="yellow", lw=0.8, ls="--", alpha=0.7) + ax.axis("off") + fig.colorbar(im, ax=ax, label="rad", shrink=0.7, pad=0.02) + + axes[row, 0].set_ylabel(f"seam ~row {sr}", fontsize=8) + + fig.suptitle( + f"Seam zoom — {dates} (rows ±{SEAM_HALF_HEIGHT} around seam centre)", + fontsize=11, + ) + fig.savefig(out_png, dpi=150) + print(f"Saved {out_png}") + + +if __name__ == "__main__": + ifg_files = _collect_burst_ifgs() + print( + f"Found {len(ifg_files)} per-burst IFGs across {len(group_by_date(ifg_files))} pairs" + ) + + no_align_dir = IFG_DIR / "stitched_no_align" + aligned_dir = IFG_DIR / "stitched_aligned" + + print("Stitching without alignment...") + no_align_ifgs = stitch_no_align(ifg_files, no_align_dir) + print(f" -> {len(no_align_ifgs)} stitched IFGs in {no_align_dir}") + + print("Stitching with burst alignment...") + aligned_ifgs = stitch_aligned(ifg_files, aligned_dir) + print(f" -> {len(aligned_ifgs)} stitched IFGs in {aligned_dir}") + + plot_comparison(no_align_ifgs, aligned_ifgs, BASE / "burst_align_comparison.png") + plot_seam_zoom(no_align_ifgs, aligned_ifgs, BASE / "burst_align_seam_zoom.png") diff --git a/scripts/make_ifg_notebook.py b/scripts/make_ifg_notebook.py new file mode 100644 index 0000000..1e8af4a --- /dev/null +++ b/scripts/make_ifg_notebook.py @@ -0,0 +1,507 @@ +"""Generate docs/ifg_workflow.ipynb from source strings.""" + +from __future__ import annotations + +import json +import uuid +from pathlib import Path + +OUT = Path(__file__).parent.parent / "docs" / "ifg_workflow.ipynb" + + +def cell_id() -> str: + return uuid.uuid4().hex[:16] + + +def md(source: str) -> dict: + return { + "cell_type": "markdown", + "id": cell_id(), + "metadata": {}, + "source": source, + } + + +def code(source: str) -> dict: + # Strip any accidental trailing backslash from raw-string cell sources. + return { + "cell_type": "code", + "execution_count": None, + "id": cell_id(), + "metadata": {}, + "outputs": [], + "source": source.rstrip("\\"), + } + + +# ── cell sources ────────────────────────────────────────────────────────────── + +TITLE = """\ +# sweets IFG Workflow — Interactive Notebook + +Interactive configuration and step-by-step execution of the `IfgWorkflow` +pipeline, designed for JupyterHub and standalone Jupyter environments. + +**What this notebook does**: + +1. Let you set up an AOI, date range, and processing options via widgets +2. Build and save a `sweets_ifg_config.yaml` +3. Run each workflow step (download → geometry → crossmul → stitch → unwrap) +4. Display the stitched interferogram thumbnails + +Default values are pre-loaded for **OPERA DISP frame 16941** (T064 ascending, +S California / Mojave, April–June 2025). + +--- +> **Requirements**: `sweets`, `ipywidgets`, `folium` (all in the pixi `default` +> environment). Run with: +> ``` +> pixi run jupyter lab +> ```\ +""" + +IMPORTS = """\ +from __future__ import annotations + +import io +import sys +from pathlib import Path +from datetime import date + +import ipywidgets as w +import folium +from IPython.display import display, clear_output + +# Make sure sweets is importable (editable install or src on sys.path) +_src = Path.cwd().parent / "src" +if _src.exists() and str(_src) not in sys.path: + sys.path.insert(0, str(_src))\ +""" + +SECTION_CONFIGURE = """\ +## 1. Configure the Workflow + +The tabs below cover every option. Values are pre-filled for frame 16941 — +change what you need, then proceed to **Section 2** to build the config.\ +""" + +WIDGETS = """\ +# ── Frame 16941 defaults (change _WORK_DIR to your own output directory) ────── +import os as _os +_WORK_DIR = _os.path.join(_os.path.expanduser("~"), "sweets-output", "frame-16941") +_BBOX = (-118.2295, 34.7939, -116.5642, 35.8195) +_START = date(2025, 4, 1) +_END = date(2025, 6, 1) +_TRACK = 64 +_BURST_IDS = "\\n".join([ + "t064_135521_iw1", "t064_135521_iw2", "t064_135521_iw3", + "t064_135522_iw1", "t064_135522_iw2", "t064_135522_iw3", + "t064_135523_iw1", "t064_135523_iw2", "t064_135523_iw3", + "t064_135524_iw1", "t064_135524_iw2", "t064_135524_iw3", + "t064_135525_iw1", "t064_135525_iw2", "t064_135525_iw3", + "t064_135526_iw1", "t064_135526_iw2", "t064_135526_iw3", + "t064_135527_iw1", "t064_135527_iw2", "t064_135527_iw3", + "t064_135528_iw1", "t064_135528_iw2", "t064_135528_iw3", + "t064_135529_iw1", "t064_135529_iw2", "t064_135529_iw3", +]) + +# ── Shared widget styles ────────────────────────────────────────────────────── +_S = {"description_width": "130px"} +_L = w.Layout(width="320px") +_LW = w.Layout(width="460px") + +# ── Tab 1: AOI ──────────────────────────────────────────────────────────────── +w_west = w.BoundedFloatText(value=_BBOX[0], min=-180, max=180, step=0.0001, + description="West (lon)", style=_S, layout=_L) +w_south = w.BoundedFloatText(value=_BBOX[1], min=-90, max=90, step=0.0001, + description="South (lat)", style=_S, layout=_L) +w_east = w.BoundedFloatText(value=_BBOX[2], min=-180, max=180, step=0.0001, + description="East (lon)", style=_S, layout=_L) +w_north = w.BoundedFloatText(value=_BBOX[3], min=-90, max=90, step=0.0001, + description="North (lat)", style=_S, layout=_L) + +_map_out = w.Output(layout=w.Layout(height="360px")) + +def _render_map(*_): + lat_c = (w_south.value + w_north.value) / 2 + lon_c = (w_west.value + w_east.value) / 2 + m = folium.Map(location=[lat_c, lon_c], zoom_start=7) + folium.Rectangle( + bounds=[[w_south.value, w_west.value], [w_north.value, w_east.value]], + color="#4285F4", fill=True, fill_opacity=0.15, + tooltip=(f"W={w_west.value:.4f} S={w_south.value:.4f} " + f"E={w_east.value:.4f} N={w_north.value:.4f}"), + ).add_to(m) + with _map_out: + clear_output(wait=True) + display(m) + +for _wgt in (w_west, w_south, w_east, w_north): + _wgt.observe(_render_map, names="value") +_render_map() + +_blank = w.Label("") +_aoi_compass = w.GridBox( + [_blank, w_north, _blank, + w_west, _blank, w_east, + _blank, w_south, _blank], + layout=w.Layout( + grid_template_rows="auto auto auto", + grid_template_columns="1fr 1fr 1fr", + grid_gap="6px", + ), +) +tab_aoi = w.VBox([ + w.HTML("

Bounding box (decimal degrees)

"), + _aoi_compass, + w.HTML("

Map preview

"), + _map_out, +]) + +# ── Tab 2: Search & Download ────────────────────────────────────────────────── +w_source = w.Dropdown( + options=["opera-cslc", "safe", "nisar-gslc"], value="opera-cslc", + description="Source type", style=_S, layout=_L, +) +w_start = w.DatePicker(value=_START, description="Start date", style=_S, layout=_L) +w_end = w.DatePicker(value=_END, description="End date", style=_S, layout=_L) +w_track = w.BoundedIntText( + value=_TRACK, min=1, max=175, step=1, + description="Rel. orbit", style=_S, layout=_L, +) +w_burst_ids = w.Textarea( + value=_BURST_IDS, + description="Burst IDs", + placeholder="One burst ID per line. Leave empty to derive from bbox.", + style={"description_width": "90px"}, + layout=w.Layout(width="500px", height="160px"), +) +w_data_dir = w.Text(value="data", description="Data dir", style=_S, layout=_L) + +tab_search = w.VBox([ + w.HTML("

Source

"), + w_source, + w.HTML("

Date range

"), + w_start, w_end, + w.HTML("

Track & burst selection

"), + w_track, w_burst_ids, + w.HTML("

Download directory

"), + w_data_dir, +]) + +# ── Tab 3: Processing options ───────────────────────────────────────────────── +# Network +w_bandwidth = w.BoundedIntText( + value=2, min=0, max=20, + description="Max bandwidth", + style=_S, layout=_L, +) +w_ref_date = w.Text( + value="", placeholder="YYYY-MM-DD (optional)", + description="Ref. date", style=_S, layout=_L, +) +w_max_tbl = w.BoundedFloatText( + value=0.0, min=0.0, step=6.0, + description="Max Δt (days)", style=_S, layout=_L, +) + +# Crossmul +w_az_looks = w.BoundedIntText(value=10, min=1, description="Az. looks", style=_S, layout=_L) +w_rg_looks = w.BoundedIntText(value=40, min=1, description="Rg. looks", style=_S, layout=_L) + +# Stitch +w_run_stitch = w.Checkbox(value=True, description="Run stitch") +w_crop_bbox = w.Checkbox(value=True, description="Crop to bbox") +w_burst_align = w.Checkbox(value=True, description="Burst alignment") +w_align_deg = w.Dropdown( + options=[(0, 0), (1, 1)], value=0, + description="Align degree", + style=_S, layout=w.Layout(width="240px"), +) + +# Unwrap +w_run_unwrap = w.Checkbox(value=False, description="Run unwrap") +w_unwrap_method = w.Dropdown( + options=["snaphu", "spurt", "whirlwind"], value="snaphu", + description="Method", style=_S, layout=_L, +) +w.dlink((w_run_unwrap, "value"), (w_unwrap_method, "disabled"), lambda v: not v) +w_unwrap_method.disabled = True + +tab_proc = w.VBox([ + w.HTML("

Interferogram network

"), + w_bandwidth, w_ref_date, w_max_tbl, + w.HTML("

Crossmul (multilooking)

"), + w.HBox([w_az_looks, w_rg_looks]), + w.HTML("

Stitch

"), + w.HBox([w_run_stitch, w_crop_bbox, w_burst_align]), + w_align_deg, + w.HTML("

Unwrap

"), + w.HBox([w_run_unwrap, w_unwrap_method]), +]) + +# ── Tab 4: Output ───────────────────────────────────────────────────────────── +w_work_dir = w.Text( + value=_WORK_DIR, + description="Work dir", + style={"description_width": "80px"}, + layout=w.Layout(width="640px"), +) +w_overwrite = w.Checkbox(value=False, description="Overwrite existing outputs") +tab_output = w.VBox([ + w.HTML("

Working directory

"), + w_work_dir, w_overwrite, +]) + +# ── Tabbed layout ───────────────────────────────────────────────────────────── +_tabs = w.Tab([tab_aoi, tab_search, tab_proc, tab_output]) +for _i, _t in enumerate(["AOI", "Search & Download", "Processing", "Output"]): + _tabs.set_title(_i, _t) + +display(_tabs)\ +""" + +SECTION_CONFIG = """\ +## 2. Build & Save Config + +Click **Build config** to validate the settings and preview the YAML. +Click **Save YAML** to write `sweets_ifg_config.yaml` inside your work directory.\ +""" + +CONFIG_BUILDER = """\ +import pydantic +from sweets.ifg import IfgWorkflow + +_out_cfg = w.Output() +_btn_build = w.Button(description="Build config", button_style="info", icon="check") +_btn_save = w.Button(description="Save YAML", button_style="success", icon="save") + +workflow: IfgWorkflow | None = None # shared state; set by on_build + + +def _collect() -> dict: + burst_ids = [b.strip() for b in w_burst_ids.value.strip().splitlines() if b.strip()] + cfg: dict = { + "work_dir": w_work_dir.value, + "bbox": [w_west.value, w_south.value, w_east.value, w_north.value], + "search": { + "kind": w_source.value, + "out_dir": w_data_dir.value, + "start": str(w_start.value), + "end": str(w_end.value), + }, + "network": {"max_bandwidth": w_bandwidth.value}, + "crossmul": {"looks": [w_az_looks.value, w_rg_looks.value]}, + "stitch": { + "run_stitch": w_run_stitch.value, + "crop_to_bbox": w_crop_bbox.value, + "run_burst_align": w_burst_align.value, + "burst_align_degree": int(w_align_deg.value), + }, + "unwrap": { + "run_unwrap": w_run_unwrap.value, + "unwrap_method": w_unwrap_method.value, + }, + "overwrite": w_overwrite.value, + } + if w_track.value: + cfg["search"]["track"] = w_track.value + if burst_ids: + cfg["search"]["burst_ids"] = burst_ids + if w_ref_date.value.strip(): + cfg["network"]["reference_date"] = w_ref_date.value.strip() + if w_max_tbl.value > 0: + cfg["network"]["max_temporal_baseline"] = float(w_max_tbl.value) + return cfg + + +def _on_build(b): + global workflow + _out_cfg.clear_output(wait=True) + cfg = _collect() + try: + workflow = IfgWorkflow(**cfg) + buf = io.StringIO() + workflow.to_yaml(buf) + yaml_str = buf.getvalue() + with _out_cfg: + print("Config valid! YAML preview:\\n" + "─" * 60) + print(yaml_str) + except pydantic.ValidationError as exc: + with _out_cfg: + print(f"Validation error:\\n{exc}") + + +def _on_save(b): + _out_cfg.clear_output(wait=True) + if workflow is None: + with _out_cfg: + print("Click 'Build config' first.") + return + cfg_path = Path(w_work_dir.value) / "sweets_ifg_config.yaml" + cfg_path.parent.mkdir(parents=True, exist_ok=True) + workflow.save(cfg_path) + with _out_cfg: + print(f"Saved: {cfg_path}") + + +_btn_build.on_click(_on_build) +_btn_save.on_click(_on_save) + +# Auto-build on first load so the YAML preview is visible without clicking +_on_build(None) + +display(w.HBox([_btn_build, _btn_save]), _out_cfg)\ +""" + +SECTION_RUN = """\ +## 3. Run the Workflow + +Select a starting step and click **Run**. All steps from the selected point +onward will execute in sequence. + +| Step | What happens | +|------|-------------| +| 1 — Download | DEM, water mask, OPERA CSLCs | +| 2 — Geometry | Stitch CSLC-STATIC look-angle layers | +| 3 — Crossmul | Per-burst multilooked interferograms | +| 4 — Stitch | Burst-align + merge to single frame | +| 5 — Unwrap | SNAPHU/SPURT (only if `run_unwrap=True`) | + +> **Tip**: If data already exists, start from step 3 or 4 to skip the download.\ +""" + +RUN_CELL = """\ +_out_run = w.Output(layout=w.Layout( + border="1px solid #ccc", + height="400px", + overflow_y="scroll", + padding="6px", +)) +_step_sel = w.BoundedIntText( + value=4, min=1, max=5, step=1, + description="Starting step", + style={"description_width": "110px"}, + layout=w.Layout(width="240px"), +) +_btn_run = w.Button( + description="Run workflow", + button_style="danger", + icon="play", + layout=w.Layout(width="160px"), +) + +def _on_run(b): + _out_run.clear_output(wait=True) + if workflow is None: + with _out_run: + print("Build and save config first (Section 2).") + return + _btn_run.disabled = True + _btn_run.description = "Running..." + try: + with _out_run: + workflow.run(starting_step=_step_sel.value) + finally: + _btn_run.disabled = False + _btn_run.description = "Run workflow" + +_btn_run.on_click(_on_run) + +display( + w.VBox([ + w.HBox([_step_sel, _btn_run]), + w.HTML("Output log"), + _out_run, + ]) +)\ +""" + +SECTION_RESULTS = """\ +## 4. View Results + +After the workflow finishes, run this cell to display wrapped-phase and +coherence thumbnails for all stitched date pairs.\ +""" + +RESULTS_CELL = """\ +import matplotlib +matplotlib.use("Agg") # safe for JupyterHub environments without a GUI display +import matplotlib.pyplot as plt +from IPython.display import display as _ipy_display +from sweets.plotting import plot_ifg_pairs + +_stitch_dir = Path(w_work_dir.value) / "interferograms" / "stitched" + +if not _stitch_dir.exists(): + print(f"Stitch directory not found: {_stitch_dir}") + print("Run the workflow (step 4) first.") +else: + fig = plot_ifg_pairs(_stitch_dir, max_pairs=13, subsample=3) + _ipy_display(fig) # embeds the figure inline (works with Agg backend) + plt.close(fig) + print(f"Plotted from: {_stitch_dir}")\ +""" + +SECTION_ADVANCED = """\ +## Appendix: Programmatic Usage + +You can also create and run the workflow entirely without the widgets:\ +""" + +ADVANCED_CELL = """\ +# Construct directly from a YAML file saved in Section 2 +# (or hand-craft the dict here) + +from sweets.ifg import IfgWorkflow + +wf = IfgWorkflow.load( + Path(w_work_dir.value) / "sweets_ifg_config.yaml" +) + +# Inspect any field +print("Pairs in network:", wf.network.max_bandwidth, "nearest-neighbor(s)") +print("Crossmul looks:", wf.crossmul.looks) +print("Burst alignment:", wf.stitch.run_burst_align) + +# Run from stitch step +# wf.run(starting_step=4)\ +""" + +# ── assemble notebook ───────────────────────────────────────────────────────── + +cells = [ + md(TITLE), + code(IMPORTS), + md(SECTION_CONFIGURE), + code(WIDGETS), + md(SECTION_CONFIG), + code(CONFIG_BUILDER), + md(SECTION_RUN), + code(RUN_CELL), + md(SECTION_RESULTS), + code(RESULTS_CELL), + md(SECTION_ADVANCED), + code(ADVANCED_CELL), +] + +nb = { + "cells": cells, + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3", + }, + "language_info": { + "name": "python", + "version": "3.11.0", + }, + }, + "nbformat": 4, + "nbformat_minor": 5, +} + +OUT.parent.mkdir(parents=True, exist_ok=True) +OUT.write_text(json.dumps(nb, indent=1, ensure_ascii=False)) +print(f"Wrote {OUT}") diff --git a/scripts/notebook_screenshots.py b/scripts/notebook_screenshots.py new file mode 100644 index 0000000..52454b1 --- /dev/null +++ b/scripts/notebook_screenshots.py @@ -0,0 +1,238 @@ +"""Take screenshots of the IFG workflow notebook in JupyterLab. + +Boots a temporary JupyterLab server, drives Playwright through the notebook +interface, executes key cells, and saves PNGs to ``docs/screenshots/``. + +Prerequisites +------------- +- ``pixi run -e web playwright install chromium`` +- Notebook must exist at ``docs/ifg_workflow.ipynb`` + +Usage +----- +:: + + pixi run -e web python scripts/notebook_screenshots.py +""" + +from __future__ import annotations + +import os +import socket +import subprocess +import sys +import time +import urllib.error +import urllib.request +from pathlib import Path + +REPO_ROOT = Path(__file__).resolve().parent.parent +NOTEBOOK = REPO_ROOT / "docs" / "ifg_workflow.ipynb" +OUT_DIR = REPO_ROOT / "docs" / "screenshots" +TOKEN = "sweets-nb-token" + + +def free_port() -> int: + with socket.socket() as s: + s.bind(("127.0.0.1", 0)) + return s.getsockname()[1] + + +def wait_for_server(url: str, timeout: float = 40.0) -> None: + deadline = time.monotonic() + timeout + while time.monotonic() < deadline: + try: + with urllib.request.urlopen(url, timeout=2) as r: + if r.status in (200, 302, 403): + return + except (urllib.error.URLError, ConnectionError, TimeoutError): + pass + time.sleep(0.5) + msg = f"JupyterLab at {url} did not start within {timeout}s" + raise RuntimeError(msg) + + +def take_shots(port: int) -> None: + from playwright.sync_api import sync_playwright + + OUT_DIR.mkdir(parents=True, exist_ok=True) + base = f"http://127.0.0.1:{port}" + # Open the notebook directly via the /lab/tree URL with the token + nb_url = f"{base}/lab/tree/docs/ifg_workflow.ipynb?token={TOKEN}" + + with sync_playwright() as p: + browser = p.chromium.launch() + ctx = browser.new_context(viewport={"width": 1400, "height": 900}) + page = ctx.new_page() + + # ── 1. Load notebook ────────────────────────────────────────────────── + page.goto(nb_url, wait_until="networkidle") + # Wait for JupyterLab to fully render the notebook editor + page.wait_for_selector(".jp-NotebookPanel", timeout=30_000) + time.sleep(2) + + # Dismiss "Select Kernel" dialog if it appears — pick the first option + try: + dialog = page.locator(".jp-Dialog") + if dialog.is_visible(timeout=3_000): + # Click the first kernel option in the select/list + try: + page.get_by_role("button", name="Select").click(timeout=2_000) + except Exception: + pass + try: + page.keyboard.press("Enter") + except Exception: + pass + time.sleep(1) + except Exception: + pass + + page.screenshot(path=str(OUT_DIR / "nb-01-loaded.png")) + print("nb-01-loaded.png") + + # ── 2. Run all cells ────────────────────────────────────────────────── + # Use the Run menu > Run All Cells + # First dismiss any lingering dialog with Escape + page.keyboard.press("Escape") + time.sleep(0.3) + + page.get_by_role("menubar").get_by_text("Run").click(timeout=10_000) + time.sleep(0.5) + page.get_by_role("menuitem", name="Run All Cells", exact=True).click( + timeout=5_000 + ) + # Dismiss any "restart kernel?" dialog + try: + page.get_by_role("button", name="Restart").click(timeout=3_000) + except Exception: + pass + # Wait for cells to execute (widgets render after kernel execution) + time.sleep(8) + page.screenshot(path=str(OUT_DIR / "nb-02-after-run.png")) + print("nb-02-after-run.png") + + # Helper: scroll the JupyterLab notebook panel to a specific pixel offset. + # JupyterLab windowed notebook uses jp-WindowedPanel-outer as the scroller. + def nb_scroll(px: int) -> None: + page.evaluate( + """(px) => { + // Try the windowed panel outer container first (JLab 4.x) + const candidates = [ + document.querySelector('.jp-WindowedPanel-outer'), + document.querySelector('.jp-NotebookPanel-notebook'), + document.querySelector('.jp-Notebook'), + document.querySelector('.lm-ScrollPanel'), + document.scrollingElement, + ]; + const el = candidates.find(e => e && e.scrollHeight > e.clientHeight); + if (el) { el.scrollTop = px; } + }""", + px, + ) + time.sleep(0.8) + + # ── 3. Scroll to top — title + config section ───────────────────────── + nb_scroll(0) + page.screenshot(path=str(OUT_DIR / "nb-03-top-config.png")) + print("nb-03-top-config.png") + + # ── 4. Scroll slightly to show the widget tabs fully ────────────────── + nb_scroll(400) + time.sleep(0.5) + page.screenshot(path=str(OUT_DIR / "nb-04-widget-tabs.png")) + print("nb-04-widget-tabs.png") + + # ── 5. Click "Search & Download" tab (ipywidgets renders as role=tab) ─ + try: + # ipywidgets tab bar titles are
  • with class jp-TabBar-tab + # Try clicking by text content + page.locator( + ".widget-tab-bar .p-TabBar-tab", has_text="Search & Download" + ).first.click(timeout=4_000) + time.sleep(1) + nb_scroll(400) + page.screenshot(path=str(OUT_DIR / "nb-05-search-tab.png")) + print("nb-05-search-tab.png") + except Exception as exc: + print(f" (search tab: {exc})", file=sys.stderr) + + # ── 6. Click "Processing" tab ───────────────────────────────────────── + try: + page.locator( + ".widget-tab-bar .p-TabBar-tab", has_text="Processing" + ).first.click(timeout=4_000) + time.sleep(1) + nb_scroll(400) + page.screenshot(path=str(OUT_DIR / "nb-06-processing-tab.png")) + print("nb-06-processing-tab.png") + except Exception as exc: + print(f" (processing tab: {exc})", file=sys.stderr) + + # ── 7. Config builder section ───────────────────────────────────────── + nb_scroll(1600) + page.screenshot(path=str(OUT_DIR / "nb-07-config-builder.png")) + print("nb-07-config-builder.png") + + # ── 8. Run section ──────────────────────────────────────────────────── + nb_scroll(2400) + page.screenshot(path=str(OUT_DIR / "nb-08-run-section.png")) + print("nb-08-run-section.png") + + # ── 9. Results section ──────────────────────────────────────────────── + nb_scroll(3200) + page.screenshot(path=str(OUT_DIR / "nb-09-results.png")) + print("nb-09-results.png") + + browser.close() + + +def main() -> int: + if not NOTEBOOK.exists(): + print(f"Notebook not found: {NOTEBOOK}") + print("Run: python scripts/make_ifg_notebook.py") + return 1 + + port = free_port() + print(f"Starting JupyterLab on port {port}...") + + env = { + **os.environ, + "JUPYTER_TOKEN": TOKEN, + } + import shutil + + jupyter_bin = shutil.which("jupyter") or sys.executable + " -m jupyter" + proc = subprocess.Popen( + [ + jupyter_bin, + "lab", + "--no-browser", + f"--port={port}", + f"--ServerApp.token={TOKEN}", + "--ServerApp.disable_check_xsrf=True", + f"--notebook-dir={REPO_ROOT}", + ], + cwd=str(REPO_ROOT), + env=env, + stdout=subprocess.DEVNULL, + stderr=subprocess.DEVNULL, + ) + try: + wait_for_server(f"http://127.0.0.1:{port}/lab?token={TOKEN}") + print(f"JupyterLab ready at http://127.0.0.1:{port}") + take_shots(port) + finally: + proc.terminate() + try: + proc.wait(timeout=5) + except subprocess.TimeoutExpired: + proc.kill() + + pngs = list(OUT_DIR.glob("nb-*.png")) + print(f"\nWrote {len(pngs)} PNG(s) to {OUT_DIR}/") + return 0 + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/scripts/web_screenshots.py b/scripts/web_screenshots.py new file mode 100644 index 0000000..a87a329 --- /dev/null +++ b/scripts/web_screenshots.py @@ -0,0 +1,223 @@ +"""Refresh the screenshots embedded in ``src/sweets/web/README.md``. + +Boots a temporary uvicorn server against the built frontend bundle, drives +Playwright through every tab + interaction, and writes the resulting PNGs into +``docs/web/screenshots/``. + +Prerequisites +------------- +- ``pixi install -e web`` (gets fastapi, uvicorn, playwright, opera_utils, + etc.) and the bundled chromium: ``playwright install chromium``. +- ``pixi run -e web web-install && pixi run -e web web-build`` so a + ``src/sweets/web/frontend/dist/`` exists for the backend to serve. +- Network access to ASF / CMR — the search step hits real granule services + to produce a representative results overlay. Without network the screenshot + will just show an empty search panel, which is also fine. + +Usage +----- +:: + + pixi run -e web web-screenshots + # or directly: + python scripts/web_screenshots.py + +Refresh cadence +--------------- +Re-run after any UI change that touches the layout, the map overlays, or the +config form. The script is idempotent; it overwrites the PNGs in place. CI +doesn't run it (it needs a GUI browser binary and live ASF / CMR queries). +""" + +from __future__ import annotations + +import argparse +import os +import socket +import subprocess +import sys +import time +from pathlib import Path + +REPO_ROOT = Path(__file__).resolve().parent.parent +OUT_DIR = REPO_ROOT / "docs" / "web" / "screenshots" +FRONTEND_DIST = REPO_ROOT / "src" / "sweets" / "web" / "frontend" / "dist" + +# A tight Los Angeles AOI + 2-month window that consistently returns ~30+ +# OPERA CSLC granules spanning two tracks — gives us a real missing-data +# overlay + a useful track picker to demo. +DEMO_BBOX = (-118.50, 33.95, -118.00, 34.35) +DEMO_DATES = ("2024-01-01", "2024-03-01") + + +def free_port() -> int: + """Return an OS-assigned free TCP port.""" + with socket.socket() as s: + s.bind(("127.0.0.1", 0)) + return s.getsockname()[1] + + +def wait_for_server(url: str, timeout: float = 30.0) -> None: + """Poll the backend until /api/health responds.""" + import urllib.error + import urllib.request + + deadline = time.monotonic() + timeout + while time.monotonic() < deadline: + try: + with urllib.request.urlopen(url, timeout=1) as r: + if r.status == 200: + return + except (urllib.error.URLError, ConnectionError, TimeoutError): + pass + time.sleep(0.3) + msg = f"backend at {url} did not come up within {timeout}s" + raise RuntimeError(msg) + + +def take_shots(port: int) -> None: + """Drive Playwright through every demo flow.""" + from playwright.sync_api import sync_playwright + + OUT_DIR.mkdir(parents=True, exist_ok=True) + base = f"http://127.0.0.1:{port}/" + + with sync_playwright() as p: + browser = p.chromium.launch() + ctx = browser.new_context(viewport={"width": 1400, "height": 900}) + page = ctx.new_page() + page.goto(base, wait_until="networkidle") + + # 1. Search (empty) + page.screenshot(path=str(OUT_DIR / "01-search-empty.png")) + print("01-search-empty.png") + + # 2. Search results over Los Angeles + w, s, e, n = DEMO_BBOX + page.get_by_label("West", exact=True).fill(str(w)) + page.get_by_label("South", exact=True).fill(str(s)) + page.get_by_label("East", exact=True).fill(str(e)) + page.get_by_label("North", exact=True).fill(str(n)) + page.get_by_label("Start", exact=True).fill(DEMO_DATES[0]) + page.get_by_label("End", exact=True).fill(DEMO_DATES[1]) + page.get_by_role("button", name="Search", exact=True).click() + # Wait for the track list (only appears after results land) so the + # screenshot includes the missing-data summary + track chips. + try: + page.wait_for_selector(".track-list", timeout=60_000) + except Exception as ex: + print(f" (no track-list within 60s: {ex})", file=sys.stderr) + time.sleep(1.5) # leaflet animation settle + page.screenshot(path=str(OUT_DIR / "02-search-results.png")) + print("02-search-results.png") + + # 2b. Pick the highest-count track to narrow the stack + page.locator(".track-item").first.click() + try: + page.wait_for_selector(".track-item.selected", timeout=30_000) + except Exception: + pass + time.sleep(1.5) + page.screenshot(path=str(OUT_DIR / "02b-search-track-narrowed.png")) + print("02b-search-track-narrowed.png") + + # 2c. Expand the granule list + page.locator("h2:has-text('Granules') button").click() + time.sleep(0.5) + page.screenshot(path=str(OUT_DIR / "02c-granule-list.png")) + print("02c-granule-list.png") + + # 3. Config (basic, full-page) + page.get_by_role("navigation").get_by_text("Config", exact=True).click() + page.wait_for_selector("text=Configure a new job", timeout=15_000) + time.sleep(0.5) + page.screenshot(path=str(OUT_DIR / "03-config-form.png")) + print("03-config-form.png") + + # 3b. Config + show advanced (dolphin / tropo). Take two scrolled + # captures because .content.full clips at the viewport. + page.get_by_label("Show advanced", exact=False).check() + time.sleep(0.6) + page.evaluate("document.querySelector('.content.full').scrollTop = 1050") + time.sleep(0.2) + page.screenshot(path=str(OUT_DIR / "03b-config-advanced-dolphin.png")) + print("03b-config-advanced-dolphin.png") + + page.evaluate("document.querySelector('.content.full').scrollTop = 2400") + time.sleep(0.2) + page.screenshot(path=str(OUT_DIR / "03c-config-advanced-tropo.png")) + print("03c-config-advanced-tropo.png") + + # 4. Jobs (empty) + page.get_by_role("navigation").get_by_text("Jobs", exact=True).click() + page.wait_for_selector("text=Jobs (") + time.sleep(0.5) + page.screenshot(path=str(OUT_DIR / "04-jobs-empty.png")) + print("04-jobs-empty.png") + + browser.close() + + +def main() -> int: + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument( + "--no-build", + action="store_true", + help="Skip rebuilding the frontend (use the existing dist/).", + ) + parser.add_argument( + "--port", + type=int, + default=None, + help="Bind backend to this port (default: OS-assigned).", + ) + args = parser.parse_args() + + if not args.no_build: + print("building frontend...") + subprocess.check_call( + ["npm", "run", "build"], + cwd=str(REPO_ROOT / "src" / "sweets" / "web" / "frontend"), + ) + + if not FRONTEND_DIST.exists(): + msg = ( + f"frontend bundle missing at {FRONTEND_DIST}; run " + "`pixi run -e web web-install && pixi run -e web web-build`" + ) + raise SystemExit(msg) + + port = args.port or free_port() + print(f"starting uvicorn on :{port}") + proc = subprocess.Popen( + [ + sys.executable, + "-m", + "uvicorn", + "sweets.web.app:app", + "--host", + "127.0.0.1", + "--port", + str(port), + "--log-level", + "warning", + ], + cwd=str(REPO_ROOT), + env={**os.environ}, + ) + try: + wait_for_server(f"http://127.0.0.1:{port}/api/health") + take_shots(port) + finally: + proc.terminate() + try: + proc.wait(timeout=5) + except subprocess.TimeoutExpired: + proc.kill() + + print(f"\nWrote {len(list(OUT_DIR.glob('*.png')))} PNGs to {OUT_DIR}") + return 0 + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/src/sweets/_burst_alignment.py b/src/sweets/_burst_alignment.py new file mode 100644 index 0000000..17fa3cc --- /dev/null +++ b/src/sweets/_burst_alignment.py @@ -0,0 +1,913 @@ +"""Estimate and remove inter-burst phase artifacts from per-burst rasters. + +Per-burst interferograms (or unwrapped phase) often disagree across the +seam where two bursts overlap because of calibration, azimuth-FM-rate +mis-registration, or ionospheric path differences. Mosaicking with a +"last-one-wins" rule (as `dolphin.stitching.merge_images` does) freezes +those discontinuities into the stitched product. + +This module estimates a per-burst correction polynomial from the overlap +regions and writes corrected rasters that can then be stitched cleanly. +Two model degrees are supported: + +- ``degree=0`` — a single constant offset per burst. Robust, cheap, and + almost always worth running. +- ``degree=1`` — a planar ramp: ``offset + cx*(x-x_ref) + cy*(y-y_ref)`` + per burst, in the data CRS. This captures the typical S1 azimuth + gradient (which projects onto both x and y in geocoded coordinates + because of the platform heading), as well as a range gradient. + +Both wrapped (complex) and unwrapped (real) inputs are handled. The +correction is multiplied as ``exp(-1j * polynomial)`` for wrapped data +and subtracted for unwrapped. + +Notes +----- +The fit is least-squares on differences across overlaps, which leaves +the absolute level free (gauge). The first burst per connected component +is anchored to zero, so corrections are relative. + +For ``degree=1`` the implementation iterates offset -> ramp -> offset +so that residual DC bias does not contaminate the slope estimate and vice versa. + +For wrapped inputs the LSQ residual is computed on raw values, which is +only a good approximation when individual offsets are well below pi. In +typical S1 IW burst overlaps, offsets are tens of milliradians to a few +hundred milliradians — well within range. For unwrapped data there is no +such ambiguity. + +Running this on wrapped phase, before unwrapping, is the recommended +order: it removes the seam discontinuity that would otherwise force the +unwrapper to bridge a 2*pi step at every burst boundary. + +Ported from ``dolphin.burst_alignment`` (feat/burst-alignment branch). +""" + +from __future__ import annotations + +import os.path +from collections.abc import Iterable, Mapping, Sequence +from dataclasses import dataclass +from pathlib import Path +from typing import Literal + +import numpy as np +import rasterio +from loguru import logger +from rasterio.enums import Resampling +from rasterio.vrt import WarpedVRT +from rasterio.windows import from_bounds + +from dolphin import io +from dolphin._types import Filename +from opera_utils._dates import DATE_FORMAT, _date_format_to_regex + +__all__ = [ + "BurstCorrection", + "align_bursts", + "apply_burst_offsets", + "estimate_burst_offsets", +] + + +_MIN_OVERLAP_PIXELS = 40 +_MIN_PATCH_PIXELS = 20 +_MIN_VALID_PATCHES = 3 +_MIN_INLIER_PATCHES = 6 +_MAD_OUTLIER_THRESHOLD = 2.5 + + +@dataclass(frozen=True) +class BurstCorrection: + """Correction polynomial estimated for one burst. + + The phase artifact, evaluated at world coordinates ``(x, y)`` in the + data CRS, is:: + + offset + cx * (x - x_ref) + cy * (y - y_ref) + + For ``degree=0`` only ``offset`` is non-zero. ``x_ref``/``y_ref`` + are shared across all bursts in a single estimation run; they exist + so the LSQ stays well-conditioned and so ``offset`` keeps its meaning + as the value of the polynomial at the reference point. + + Subtracting this polynomial from unwrapped phase, or multiplying the + complex data by ``exp(-1j * polynomial)`` for wrapped phase, removes + the artifact. + """ + + offset: float = 0.0 + cx: float = 0.0 + cy: float = 0.0 + x_ref: float = 0.0 + y_ref: float = 0.0 + + def evaluate(self, x: np.ndarray, y: np.ndarray) -> np.ndarray: + """Return the polynomial value at world coordinates ``(x, y)``.""" + return self.offset + self.cx * (x - self.x_ref) + self.cy * (y - self.y_ref) + + @property + def is_planar(self) -> bool: + """True if either slope is non-zero (i.e. degree-1 correction).""" + return self.cx != 0.0 or self.cy != 0.0 + + +def estimate_burst_offsets( + burst_files: Sequence[Filename], + *, + degree: int = 0, + method: Literal["median", "mean"] = "median", + anchor_index: int = 0, + n_patches: tuple[int, int] = (4, 8), + min_overlap_pixels: int = _MIN_OVERLAP_PIXELS, + mad_threshold: float = _MAD_OUTLIER_THRESHOLD, + max_fringes_per_burst: float | None = 0.5, +) -> dict[Path, BurstCorrection]: + """Estimate per-burst phase correction from overlap regions. + + Parameters + ---------- + burst_files : Sequence of paths + Per-burst rasters that share a CRS and resolution. They may be + wrapped (complex dtype) or unwrapped (real dtype); the data type + of the first file determines the mode. + degree : {0, 1}, optional + Polynomial degree: 0 = constant offset per burst; 1 = offset + + planar ramp (cx, cy) in the data CRS. + method : {"median", "mean"}, optional + Reduction over per-patch offsets within each overlap. + anchor_index : int, optional + Index of the burst whose correction is pinned to zero. + n_patches : (int, int), optional + Number of (azimuth, range) patches for the planar fit (degree=1). + min_overlap_pixels : int, optional + Skip overlap pairs with fewer jointly-valid pixels. + mad_threshold : float, optional + Per-patch MAD outlier threshold. + max_fringes_per_burst : float, optional + Tikhonov prior on the planar slope (degree=1 only). + + Returns + ------- + dict[Path, BurstCorrection] + Map from input path to the per-burst correction. + + """ + if degree not in (0, 1): + raise ValueError(f"degree must be 0 or 1, got {degree}") + + paths = [Path(f) for f in burst_files] + if len(paths) < 2: + return {p: BurstCorrection() for p in paths} + + is_complex = _is_complex_raster(paths[0]) + logger.debug( + "estimate_burst_offsets: {} bursts, degree={}, {} mode", + len(paths), + degree, + "wrapped (complex)" if is_complex else "unwrapped (real)", + ) + + burst_extents = _read_burst_extents(paths) + + cache: dict[tuple[int, int], _OverlapCache] = {} + for i in range(len(paths)): + for j in range(i + 1, len(paths)): + entry = _load_overlap(paths[i], paths[j]) + if entry is None: + continue + if int(entry.valid.sum()) < min_overlap_pixels: + continue + cache[(i, j)] = entry + + if not cache: + logger.warning("estimate_burst_offsets: no overlapping bursts found") + return {p: BurstCorrection() for p in paths} + + x_ref, y_ref = _choose_reference(cache.values()) + + corrections = _initialize_corrections(paths, x_ref=x_ref, y_ref=y_ref) + corrections = _fit_offset_step( + cache=cache, + corrections=corrections, + paths=paths, + is_complex=is_complex, + method=method, + n_patches=n_patches, + mad_threshold=mad_threshold, + anchor_index=anchor_index, + ) + + if degree == 1: + corrections = _fit_planar_step( + cache=cache, + corrections=corrections, + paths=paths, + is_complex=is_complex, + method=method, + n_patches=n_patches, + mad_threshold=mad_threshold, + anchor_index=anchor_index, + burst_extents=burst_extents, + max_fringes_per_burst=max_fringes_per_burst, + ) + corrections = _fit_offset_step( + cache=cache, + corrections=corrections, + paths=paths, + is_complex=is_complex, + method=method, + n_patches=n_patches, + mad_threshold=mad_threshold, + anchor_index=anchor_index, + ) + + return corrections + + +def apply_burst_offsets( + burst_files: Sequence[Filename], + corrections: Mapping[Path, BurstCorrection], + output_dir: Filename, + *, + suffix: str = ".aligned", +) -> list[Path]: + """Write corrected per-burst rasters with the polynomial removed. + + For complex (wrapped) inputs each pixel is multiplied by + ``exp(-1j * polynomial(x, y))``. For real (unwrapped) inputs the + polynomial is subtracted. Nodata pixels are passed through. + """ + out_dir = Path(output_dir) + out_dir.mkdir(parents=True, exist_ok=True) + + in_paths = [Path(f) for f in burst_files] + out_paths = _build_output_paths(in_paths, out_dir, suffix=suffix) + + for in_path, out_path in zip(in_paths, out_paths, strict=False): + corr = corrections[in_path] + + with rasterio.open(in_path) as src: + arr = src.read(1) + nodata = src.nodata + transform = src.transform + + corrected = _apply_correction(arr, corr, nodata=nodata, transform=transform) + out_path.parent.mkdir(parents=True, exist_ok=True) + io.write_arr(arr=corrected, output_name=out_path, like_filename=in_path) + logger.debug( + "wrote {} (offset={:+.4f} cx={:+.3e} cy={:+.3e})", + out_path, + corr.offset, + corr.cx, + corr.cy, + ) + + return out_paths + + +def align_bursts( + burst_files: Sequence[Filename], + output_dir: Filename, + *, + degree: int = 0, + method: Literal["median", "mean"] = "median", + anchor_index: int = 0, + suffix: str = ".aligned", + max_fringes_per_burst: float | None = 0.5, +) -> tuple[list[Path], dict[Path, BurstCorrection]]: + """Estimate corrections, apply them, and return the corrected paths. + + Parameters + ---------- + burst_files : Sequence of paths + Per-burst rasters (complex or real). + output_dir : path + Directory to write corrected rasters into. + degree : {0, 1} + Polynomial degree: 0 = constant offset, 1 = planar ramp. + method : {"median", "mean"} + Aggregation method for per-patch offsets. + anchor_index : int + Index of the burst pinned to zero correction. + suffix : str + Suffix appended to the stem of each corrected output file. + max_fringes_per_burst : float or None + Tikhonov prior strength for degree=1 slope estimates. + + Returns + ------- + list[Path] + Paths to the corrected output rasters. + dict[Path, BurstCorrection] + Per-burst correction polynomials. + + """ + corrections = estimate_burst_offsets( + burst_files, + degree=degree, + method=method, + anchor_index=anchor_index, + max_fringes_per_burst=max_fringes_per_burst, + ) + out_paths = apply_burst_offsets( + burst_files, corrections, output_dir=output_dir, suffix=suffix + ) + return out_paths, corrections + + +# --------------------------------------------------------------------------- +# internals +# --------------------------------------------------------------------------- + + +@dataclass +class _OverlapCache: + """Aligned overlap arrays plus per-pixel world coordinates.""" + + arr_a: np.ndarray + arr_b: np.ndarray + x_world: np.ndarray + y_world: np.ndarray + valid: np.ndarray + + +def _initialize_corrections( + paths: Sequence[Path], *, x_ref: float, y_ref: float +) -> dict[Path, BurstCorrection]: + return {p: BurstCorrection(x_ref=x_ref, y_ref=y_ref) for p in paths} + + +def _read_burst_extents(paths: Sequence[Path]) -> dict[Path, tuple[float, float]]: + """Return ``{path: (x_extent, y_extent)}`` in CRS units.""" + extents: dict[Path, tuple[float, float]] = {} + for p in paths: + with rasterio.open(p) as src: + extents[p] = ( + float(src.bounds.right - src.bounds.left), + float(src.bounds.top - src.bounds.bottom), + ) + return extents + + +def _load_overlap(path_a: Path, path_b: Path) -> _OverlapCache | None: + with rasterio.open(path_a) as ra, rasterio.open(path_b) as rb: + if ra.crs != rb.crs: + logger.warning( + "skipping overlap {} vs {}: CRS mismatch", path_a.name, path_b.name + ) + return None + if ra.res != rb.res: + logger.warning( + "skipping overlap {} vs {}: resolution mismatch", + path_a.name, + path_b.name, + ) + return None + + xmin = max(ra.bounds.left, rb.bounds.left) + xmax = min(ra.bounds.right, rb.bounds.right) + ymin = max(ra.bounds.bottom, rb.bounds.bottom) + ymax = min(ra.bounds.top, rb.bounds.top) + if xmax <= xmin or ymax <= ymin: + return None + + win = from_bounds(xmin, ymin, xmax, ymax, transform=ra.transform) + win = win.round_offsets().round_lengths() + if win.width <= 0 or win.height <= 0: + return None + + arr_a = ra.read(1, window=win) + nodata_a = ra.nodata + with WarpedVRT( + rb, + crs=ra.crs, + transform=ra.transform, + width=ra.width, + height=ra.height, + resampling=Resampling.nearest, + ) as vrt: + arr_b = vrt.read(1, window=win) + nodata_b = vrt.nodata if vrt.nodata is not None else rb.nodata + + col_off = int(win.col_off) + row_off = int(win.row_off) + cols = np.arange(win.width) + rows = np.arange(win.height) + x_world = ra.transform.a * (col_off + cols + 0.5) + ra.transform.c + y_world = ra.transform.e * (row_off + rows + 0.5) + ra.transform.f + + valid = _valid_mask(arr_a, nodata_a) & _valid_mask(arr_b, nodata_b) + return _OverlapCache(arr_a, arr_b, x_world, y_world, valid) + + +def _is_complex_raster(path: Path) -> bool: + with rasterio.open(path) as src: + return np.issubdtype(np.dtype(src.dtypes[0]), np.complexfloating) + + +def _valid_mask(arr: np.ndarray, nodata: float | None) -> np.ndarray: + if np.iscomplexobj(arr): + return np.isfinite(arr.real) & np.isfinite(arr.imag) & (arr != 0) + valid = np.isfinite(arr) + if nodata is not None and np.isfinite(nodata): + valid &= arr != nodata + return valid + + +def _choose_reference(caches: Iterable[_OverlapCache]) -> tuple[float, float]: + xs: list[float] = [] + ys: list[float] = [] + for c in caches: + if not c.valid.any(): + continue + rows, cols = np.nonzero(c.valid) + xs.append(float(c.x_world[cols].mean())) + ys.append(float(c.y_world[rows].mean())) + if not xs: + return 0.0, 0.0 + return float(np.mean(xs)), float(np.mean(ys)) + + +def _residual_diff( + arr_a: np.ndarray, + arr_b: np.ndarray, + valid: np.ndarray, + corr_a: BurstCorrection, + corr_b: BurstCorrection, + x_world: np.ndarray, + y_world: np.ndarray, + is_complex: bool, +) -> np.ndarray: + poly_a = corr_a.evaluate(x_world[None, :], y_world[:, None]) + poly_b = corr_b.evaluate(x_world[None, :], y_world[:, None]) + delta = poly_b - poly_a + + if is_complex: + diff = arr_b * np.conj(arr_a) * np.exp(-1j * delta).astype(arr_a.dtype) + out = np.full(diff.shape, np.nan + 0j, dtype=np.complex64) + out[valid] = diff[valid] + return out + + diff = (arr_b - arr_a) - delta + out = np.full(diff.shape, np.nan, dtype=np.float64) + out[valid] = diff[valid] + return out + + +def _patch_stats( + diff: np.ndarray, + x_world: np.ndarray, + y_world: np.ndarray, + *, + n_patches: tuple[int, int], + method: str, + mad_threshold: float, + is_complex: bool, +) -> list[tuple[float, float, float, float]]: + """Reduce a 2D overlap-difference array into per-patch (xc, yc, value, weight).""" + ny, nx = diff.shape + npy = max(1, min(n_patches[0], ny)) + npx = max(1, min(n_patches[1], nx)) + + y_edges = np.linspace(0, ny, npy + 1, dtype=int) + x_edges = np.linspace(0, nx, npx + 1, dtype=int) + + out: list[tuple[float, float, float, float]] = [] + for py in range(npy): + y0, y1 = y_edges[py], y_edges[py + 1] + if y1 <= y0: + continue + for px in range(npx): + x0, x1 = x_edges[px], x_edges[px + 1] + if x1 <= x0: + continue + block = diff[y0:y1, x0:x1] + if is_complex: + mask = np.isfinite(block.real) & np.isfinite(block.imag) + else: + mask = np.isfinite(block) + n = int(mask.sum()) + if n < _MIN_PATCH_PIXELS: + continue + valid = block[mask] + value = float(np.angle(valid.mean())) if is_complex else float(valid.mean()) + xs, ys = np.meshgrid(x_world[x0:x1], y_world[y0:y1]) + xc = float(xs[mask].mean()) + yc = float(ys[mask].mean()) + out.append((xc, yc, value, float(np.sqrt(n)))) + + if len(out) < _MIN_VALID_PATCHES: + return [] + + values = np.array([p[2] for p in out]) + if method == "median": + center = float(np.median(values)) + resid = _wrap(values - center) if is_complex else (values - center) + mad = float(np.median(np.abs(resid))) + if mad > 0: + inliers = np.abs(resid) <= mad_threshold * mad + if int(inliers.sum()) >= _MIN_INLIER_PATCHES: + out = [p for p, keep in zip(out, inliers, strict=False) if keep] + return out + + +def _fit_offset_step( + *, + cache: dict[tuple[int, int], _OverlapCache], + corrections: dict[Path, BurstCorrection], + paths: Sequence[Path], + is_complex: bool, + method: str, + n_patches: tuple[int, int], + mad_threshold: float, + anchor_index: int, +) -> dict[Path, BurstCorrection]: + pair_eqs: list[tuple[int, int, float, float]] = [] + for (i, j), entry in cache.items(): + diff = _residual_diff( + entry.arr_a, + entry.arr_b, + entry.valid, + corrections[paths[i]], + corrections[paths[j]], + entry.x_world, + entry.y_world, + is_complex=is_complex, + ) + patches = _patch_stats( + diff, + entry.x_world, + entry.y_world, + n_patches=n_patches, + method=method, + mad_threshold=mad_threshold, + is_complex=is_complex, + ) + if not patches: + continue + vals = np.array([p[2] for p in patches]) + ws = np.array([p[3] for p in patches]) + offset = _aggregate_pair(vals, ws, method=method, is_complex=is_complex) + pair_eqs.append((i, j, offset, float(np.sqrt((ws**2).sum())))) + + deltas = _solve_offset_lsq( + pair_eqs, + n_bursts=len(paths), + anchor_index=anchor_index, + is_complex=is_complex, + ) + return _add_offsets(corrections, paths, deltas, is_complex=is_complex) + + +def _fit_planar_step( + *, + cache: dict[tuple[int, int], _OverlapCache], + corrections: dict[Path, BurstCorrection], + paths: Sequence[Path], + is_complex: bool, + method: str, + n_patches: tuple[int, int], + mad_threshold: float, + anchor_index: int, + burst_extents: dict[Path, tuple[float, float]], + max_fringes_per_burst: float | None, +) -> dict[Path, BurstCorrection]: + pair_patches: dict[tuple[int, int], list[tuple[float, float, float, float]]] = {} + for (i, j), entry in cache.items(): + diff = _residual_diff( + entry.arr_a, + entry.arr_b, + entry.valid, + corrections[paths[i]], + corrections[paths[j]], + entry.x_world, + entry.y_world, + is_complex=is_complex, + ) + patches = _patch_stats( + diff, + entry.x_world, + entry.y_world, + n_patches=n_patches, + method=method, + mad_threshold=mad_threshold, + is_complex=is_complex, + ) + if patches: + pair_patches[(i, j)] = patches + + sample_corr = next(iter(corrections.values())) + cx_arr, cy_arr = _solve_planar_lsq( + pair_patches, + n_bursts=len(paths), + anchor_index=anchor_index, + is_complex=is_complex, + x_ref=sample_corr.x_ref, + y_ref=sample_corr.y_ref, + burst_extents=[burst_extents[p] for p in paths], + max_fringes_per_burst=max_fringes_per_burst, + ) + + new_corr: dict[Path, BurstCorrection] = {} + for k, p in enumerate(paths): + c = corrections[p] + new_corr[p] = BurstCorrection( + offset=c.offset, + cx=c.cx + float(cx_arr[k]), + cy=c.cy + float(cy_arr[k]), + x_ref=c.x_ref, + y_ref=c.y_ref, + ) + return new_corr + + +def _add_offsets( + corrections: dict[Path, BurstCorrection], + paths: Sequence[Path], + deltas: np.ndarray, + *, + is_complex: bool, +) -> dict[Path, BurstCorrection]: + new_corr: dict[Path, BurstCorrection] = {} + for k, p in enumerate(paths): + c = corrections[p] + new_offset = c.offset + float(deltas[k]) + if is_complex: + new_offset = _wrap_scalar(new_offset) + new_corr[p] = BurstCorrection( + offset=new_offset, + cx=c.cx, + cy=c.cy, + x_ref=c.x_ref, + y_ref=c.y_ref, + ) + return new_corr + + +def _solve_offset_lsq( + pair_eqs: list[tuple[int, int, float, float]], + *, + n_bursts: int, + anchor_index: int, + is_complex: bool, +) -> np.ndarray: + if not pair_eqs: + return np.zeros(n_bursts, dtype=np.float64) + + from scipy import sparse + from scipy.sparse.csgraph import connected_components + from scipy.sparse.linalg import lsqr + + adj = sparse.lil_matrix((n_bursts, n_bursts)) + for i, j, _, _ in pair_eqs: + adj[i, j] = 1 + adj[j, i] = 1 + n_comp, labels = connected_components(adj.tocsr(), directed=False) + + out = np.zeros(n_bursts, dtype=np.float64) + for comp in range(n_comp): + comp_idx = [int(i) for i in np.where(labels == comp)[0]] + if len(comp_idx) == 1: + continue + local = {gi: k for k, gi in enumerate(comp_idx)} + comp_eqs = [ + (local[i], local[j], o, w) + for i, j, o, w in pair_eqs + if i in local and j in local + ] + if not comp_eqs: + continue + + n_local = len(comp_idx) + n_eq = len(comp_eqs) + 1 + A = sparse.lil_matrix((n_eq, n_local)) + b = np.zeros(n_eq) + wt = np.zeros(n_eq) + for k, (li, lj, o, w) in enumerate(comp_eqs): + A[k, li] = -1.0 + A[k, lj] = +1.0 + b[k] = _wrap_scalar(o) if is_complex else o + wt[k] = w + + anchor_local = local.get(anchor_index, 0) + A[-1, anchor_local] = 1.0 + b[-1] = 0.0 + sum_w = wt[:-1].sum() + wt[-1] = sum_w * 100 if sum_w > 0 else 1e6 + + sqW = np.sqrt(wt) + sol, *_ = lsqr(sparse.diags(sqW) @ A.tocsr(), sqW * b) + sol = sol - sol[anchor_local] + for k, gi in enumerate(comp_idx): + out[gi] = _wrap_scalar(float(sol[k])) if is_complex else float(sol[k]) + return out + + +def _solve_planar_lsq( + pair_patches: dict[tuple[int, int], list[tuple[float, float, float, float]]], + *, + n_bursts: int, + anchor_index: int, + is_complex: bool, + x_ref: float, + y_ref: float, + burst_extents: Sequence[tuple[float, float]], + max_fringes_per_burst: float | None, +) -> tuple[np.ndarray, np.ndarray]: + if not pair_patches: + return np.zeros(n_bursts), np.zeros(n_bursts) + + from scipy import sparse + from scipy.sparse.csgraph import connected_components + from scipy.sparse.linalg import lsqr + + adj = sparse.lil_matrix((n_bursts, n_bursts)) + for (i, j), patches in pair_patches.items(): + if patches: + adj[i, j] = 1 + adj[j, i] = 1 + n_comp, labels = connected_components(adj.tocsr(), directed=False) + + all_xc = [] + all_yc = [] + for patches in pair_patches.values(): + for xc, yc, _, _ in patches: + all_xc.append(xc - x_ref) + all_yc.append(yc - y_ref) + x_scale = max(float(np.std(all_xc)), 1.0) + y_scale = max(float(np.std(all_yc)), 1.0) + + cx_out = np.zeros(n_bursts) + cy_out = np.zeros(n_bursts) + + for comp in range(n_comp): + comp_idx = [int(i) for i in np.where(labels == comp)[0]] + if len(comp_idx) == 1: + continue + local = {gi: k for k, gi in enumerate(comp_idx)} + comp_pairs = [ + (local[i], local[j], patches) + for (i, j), patches in pair_patches.items() + if i in local and j in local + ] + if not comp_pairs: + continue + + n_local = len(comp_idx) + rows: list[int] = [] + cols: list[int] = [] + data: list[float] = [] + b_list: list[float] = [] + wt_list: list[float] = [] + eq = 0 + for li, lj, patches in comp_pairs: + for xc, yc, val, w in patches: + dx = (xc - x_ref) / x_scale + dy = (yc - y_ref) / y_scale + rows.extend([eq, eq, eq, eq]) + cols.extend([2 * li, 2 * li + 1, 2 * lj, 2 * lj + 1]) + data.extend([-dx, -dy, +dx, +dy]) + b_list.append(_wrap_scalar(val) if is_complex else val) + wt_list.append(w) + eq += 1 + + if eq < 2 * n_local: + continue + + if max_fringes_per_burst is not None and max_fringes_per_burst > 0: + for li_local, gi in enumerate(comp_idx): + ext_x, ext_y = burst_extents[gi] + sigma_cx_scaled = ( + 2 * np.pi * max_fringes_per_burst * x_scale / max(ext_x, 1.0) + ) + sigma_cy_scaled = ( + 2 * np.pi * max_fringes_per_burst * y_scale / max(ext_y, 1.0) + ) + for kc, sigma in ( + (2 * li_local, sigma_cx_scaled), + (2 * li_local + 1, sigma_cy_scaled), + ): + rows.append(eq) + cols.append(kc) + data.append(1.0) + b_list.append(0.0) + wt_list.append(1.0 / (sigma * sigma)) + eq += 1 + + anchor_local = local.get(anchor_index, 0) + for kc in (2 * anchor_local, 2 * anchor_local + 1): + rows.append(eq) + cols.append(kc) + data.append(1.0) + b_list.append(0.0) + wt_list.append(max(sum(wt_list) * 100, 1e6)) + eq += 1 + + A = sparse.coo_matrix((data, (rows, cols)), shape=(eq, 2 * n_local)).tocsr() + b_arr = np.array(b_list) + w_arr = np.array(wt_list) + sqW = np.sqrt(w_arr) + sol, *_ = lsqr(sparse.diags(sqW) @ A, sqW * b_arr) + + sol = sol.copy() + sol[0::2] -= sol[2 * anchor_local] + sol[1::2] -= sol[2 * anchor_local + 1] + + for k, gi in enumerate(comp_idx): + cx_out[gi] = sol[2 * k] / x_scale + cy_out[gi] = sol[2 * k + 1] / y_scale + + return cx_out, cy_out + + +def _wrap_scalar(x: float) -> float: + return float((x + np.pi) % (2 * np.pi) - np.pi) + + +def _wrap(x: np.ndarray) -> np.ndarray: + return (x + np.pi) % (2 * np.pi) - np.pi + + +def _weighted_median(values: np.ndarray, weights: np.ndarray) -> float: + """Continuous weighted median via cumulative-weight interpolation.""" + order = np.argsort(values) + sv = values[order] + sw = weights[order] + cw = np.cumsum(sw) / sw.sum() + return float(np.interp(0.5, cw, sv)) + + +def _aggregate_pair( + values: np.ndarray, weights: np.ndarray, *, method: str, is_complex: bool +) -> float: + if method == "median": + if is_complex: + center = float(np.angle((np.exp(1j * values) * weights).sum())) + resid = _wrap(values - center) + return _wrap_scalar(center + _weighted_median(resid, weights)) + return _weighted_median(values, weights) + if method == "mean": + if is_complex: + return _wrap_scalar(float(np.angle((np.exp(1j * values) * weights).sum()))) + return float(np.average(values, weights=weights)) + raise ValueError(f"unknown method {method!r}") + + +def _apply_correction( + arr: np.ndarray, + corr: BurstCorrection, + *, + nodata: float | None, + transform, +) -> np.ndarray: + valid = _valid_mask(arr, nodata) + out = arr.copy() + if not corr.is_planar: + if np.iscomplexobj(arr): + out[valid] = arr[valid] * np.exp(-1j * corr.offset).astype(arr.dtype) + else: + out[valid] = arr[valid] - corr.offset + return out + + h, w = arr.shape + cols = np.arange(w) + rows = np.arange(h) + x_world = transform.a * (cols + 0.5) + transform.c + y_world = transform.e * (rows + 0.5) + transform.f + polynomial = corr.evaluate(x_world[None, :], y_world[:, None]) + if np.iscomplexobj(arr): + out[valid] = arr[valid] * np.exp(-1j * polynomial[valid]).astype(arr.dtype) + else: + out[valid] = arr[valid] - polynomial[valid] + return out + + +def _build_output_paths( + in_paths: Sequence[Path], + out_dir: Path, + *, + suffix: str, + file_date_fmt: str = DATE_FORMAT, +) -> list[Path]: + stems = [p.stem for p in in_paths] + if len(set(stems)) == len(stems): + out: list[Path] = [] + for p in in_paths: + ext = ".tif" if p.suffix.lower() == ".vrt" else p.suffix + out.append(out_dir / f"{p.stem}{suffix}{ext}") + return out + + date_pat = _date_format_to_regex(file_date_fmt) + abs_parents = [str(p.resolve().parent) for p in in_paths] + common = os.path.commonpath(abs_parents) if len(abs_parents) > 1 else "" + out_paths: list[Path] = [] + for p, parent in zip(in_paths, abs_parents, strict=False): + rel = os.path.relpath(parent, common) if common else parent + prefix = rel.replace(os.sep, "_").strip("_") or "burst" + # Strip date tokens so dates don't appear twice in the output stem + # when the directory structure already contains the pair dates. + prefix = date_pat.sub("", prefix).strip("_") or "burst" + ext = ".tif" if p.suffix.lower() == ".vrt" else p.suffix + out_paths.append(out_dir / f"{prefix}__{p.stem}{suffix}{ext}") + return out_paths diff --git a/src/sweets/_crossmul.py b/src/sweets/_crossmul.py new file mode 100644 index 0000000..8f7fef8 --- /dev/null +++ b/src/sweets/_crossmul.py @@ -0,0 +1,389 @@ +"""Blockwise multilooked interferogram and coherence computation. + +Reads geocoded SLCs (COMPASS HDF5 with ``/data/VV`` subdataset) in +azimuth blocks, cross-multiplies, multilooks with boxcar or Gaussian +filtering, and writes complex interferogram and coherence GeoTIFFs. + +Saving the complex interferogram (not wrapped phase) is deliberate: when +burst outputs are later stitched, GDAL interpolates real and imaginary +parts independently, which is correct. Wrapped phase is derived *after* +stitching so that interpolation never crosses a +/-pi discontinuity. + +The implementation uses NumPy / SciPy with a JAX-accelerated path for +Gaussian multilooking when JAX is available. No ISCE3 signal dependency. +""" + +from __future__ import annotations + +import functools +from pathlib import Path +from typing import Literal + +import numpy as np +from loguru import logger +from pydantic import BaseModel, Field +from scipy.ndimage import gaussian_filter + +try: + import jax # noqa: F401 + + _JAX_AVAILABLE = True +except ImportError: + _JAX_AVAILABLE = False + +from dolphin.io import ( + format_nc_filename, + get_raster_crs, + get_raster_gt, + get_raster_xysize, + load_gdal, + write_arr, + write_block, +) + +from dolphin._types import Filename + +__all__ = ["CrossmulOptions", "run_crossmul"] + +FilterType = Literal["boxcar", "gaussian"] + +_DEFAULT_LINES_PER_BLOCK = 512 +_GTIFF_OPTIONS = ["COMPRESS=DEFLATE", "TILED=YES", "ZLEVEL=6", "BIGTIFF=IF_SAFER"] + + +class CrossmulOptions(BaseModel, frozen=True): + """Options for interferogram formation via multilook crossmul. + + Parameters + ---------- + looks : tuple[int, int] + Multilook factors ``(azimuth_looks, range_looks)``. Controls the + filter window size and output pixel spacing relative to the input SLCs. + filter_type : {"boxcar", "gaussian"} + ``"boxcar"`` for uniform averaging; ``"gaussian"`` for Gaussian- + weighted averaging (sigma = looks/2, GMTSAR convention). + lines_per_block : int + Number of *output* azimuth rows written per processing block. + Controls peak memory: each block requires + ``lines_per_block * az_looks * ncols * 8`` bytes of input. + """ + + looks: tuple[int, int] = Field( + default=(10, 40), + description=( + "Multilook factors (azimuth, range). With COMPASS geocoding at" + " 10 m x 2.5 m, the default (10, 40) gives ~100 m x 100 m output." + ), + ) + filter_type: FilterType = Field( + default="boxcar", + description=( + "'boxcar' for uniform spatial averaging (fast reshape+mean)," + " 'gaussian' for Gaussian-weighted averaging" + " (sigma = looks / 2, GMTSAR style)." + ), + ) + lines_per_block: int = Field( + default=_DEFAULT_LINES_PER_BLOCK, + description="Output azimuth rows per processing block.", + ge=1, + ) + + +def _boxcar_multilook(arr: np.ndarray, looks: tuple[int, int]) -> np.ndarray: + """Boxcar multilook via reshape+mean. + + Parameters + ---------- + arr + 2-D array (real or complex). + looks + ``(az_looks, rg_looks)`` window size. + + Returns + ------- + np.ndarray + Multilooked array, shape ``(nrows // az_looks, ncols // rg_looks)``. + + """ + az_looks, rg_looks = looks + nrows, ncols = arr.shape + nrows_out = nrows // az_looks + ncols_out = ncols // rg_looks + arr = arr[: nrows_out * az_looks, : ncols_out * rg_looks] + return arr.reshape(nrows_out, az_looks, ncols_out, rg_looks).mean(axis=(1, 3)) + + +def _gaussian_kernel_1d(sigma: float, truncate: float = 4.0) -> np.ndarray: + """Build a normalized 1-D Gaussian kernel matching scipy's gaussian_filter.""" + radius = int(truncate * sigma + 0.5) + x = np.arange(-radius, radius + 1, dtype=np.float64) + k = np.exp(-0.5 * (x / sigma) ** 2) + return (k / k.sum()).astype(np.float32) + + +@functools.lru_cache(maxsize=16) +def _build_gaussian_conv_fn( + sigma_az: float, sigma_rg: float, az_looks: int, rg_looks: int +): + """Return a JIT-compiled separable strided Gaussian conv function. + + Applies the Gaussian kernel only at output sample positions (strided + conv) rather than filtering the full-resolution array and then + decimating. For (10, 40) looks this is ~50x fewer FLOPs than the + scipy filter-then-decimate approach. + + The output shape is exactly ``(H // az_looks, W // rg_looks)``; input + is clipped to a multiple of the stride before convolving. + """ + import jax + import jax.numpy as jnp + from jax import lax as jax_lax + + k_az = jnp.array(_gaussian_kernel_1d(sigma_az)) + k_rg = jnp.array(_gaussian_kernel_1d(sigma_rg)) + pad_az = len(k_az) // 2 + pad_rg = len(k_rg) // 2 + + @jax.jit + def _conv(arr: jax.Array) -> jax.Array: + # arr: (H, W) real float32 + # Clip to multiples of stride so output is exactly H//az x W//rg. + H, W = arr.shape + x = arr[: (H // az_looks) * az_looks, : (W // rg_looks) * rg_looks] + x = x[None, None, :, :] # (1, 1, H_c, W_c) + + # Range pass: horizontal strided conv -> (1, 1, H_c, W_c//rg_looks) + x = jax_lax.conv_general_dilated( + x, + k_rg[None, None, None, :], + window_strides=(1, rg_looks), + padding=((0, 0), (pad_rg, pad_rg)), + dimension_numbers=("NCHW", "OIHW", "NCHW"), + ) + # Azimuth pass: vertical strided conv -> (1, 1, H_c//az_looks, W_c//rg_looks) + x = jax_lax.conv_general_dilated( + x, + k_az[None, None, :, None], + window_strides=(az_looks, 1), + padding=((pad_az, pad_az), (0, 0)), + dimension_numbers=("NCHW", "OIHW", "NCHW"), + ) + return x[0, 0, :, :] + + return _conv + + +def _gaussian_multilook(arr: np.ndarray, looks: tuple[int, int]) -> np.ndarray: + """Gaussian multilook: separable strided conv (JAX) or filter+decimate (scipy). + + Parameters + ---------- + arr + 2-D array (real or complex). + looks + ``(az_looks, rg_looks)`` — controls the Gaussian sigma + (sigma = looks / 2) and decimation stride. + + Returns + ------- + np.ndarray + Decimated array, shape ``(nrows // az_looks, ncols // rg_looks)``. + + """ + az_looks, rg_looks = looks + sigma_az = az_looks / 2.0 + sigma_rg = rg_looks / 2.0 + + if _JAX_AVAILABLE: + import jax.numpy as jnp + + conv_fn = _build_gaussian_conv_fn(sigma_az, sigma_rg, az_looks, rg_looks) + if np.iscomplexobj(arr): + r = np.array(conv_fn(jnp.array(arr.real.astype(np.float32)))) + i = np.array(conv_fn(jnp.array(arr.imag.astype(np.float32)))) + return (r + 1j * i).astype(arr.dtype) + return np.array(conv_fn(jnp.array(arr.astype(np.float32)))).astype(arr.dtype) + + # scipy fallback when JAX is unavailable. + # Clip to multiples of stride first so output shape == (H//az, W//rg), + # matching the JAX path and the write_block row allocation. + H, W = arr.shape + arr = arr[: (H // az_looks) * az_looks, : (W // rg_looks) * rg_looks] + sigma = (sigma_az, sigma_rg) + if np.iscomplexobj(arr): + filtered_r = gaussian_filter(arr.real.astype(np.float64), sigma) + filtered_i = gaussian_filter(arr.imag.astype(np.float64), sigma) + return ((filtered_r + 1j * filtered_i).astype(arr.dtype))[ + ::az_looks, ::rg_looks + ] + return gaussian_filter(arr.astype(np.float64), sigma).astype(arr.dtype)[ + ::az_looks, ::rg_looks + ] + + +def _multilook( + arr: np.ndarray, looks: tuple[int, int], filter_type: FilterType +) -> np.ndarray: + if filter_type == "gaussian": + return _gaussian_multilook(arr, looks) + return _boxcar_multilook(arr, looks) + + +def _compute_coherence( + ifg_ml: np.ndarray, + ref_power_ml: np.ndarray, + sec_power_ml: np.ndarray, +) -> np.ndarray: + """Compute sample coherence magnitude.""" + denom = np.sqrt(ref_power_ml * sec_power_ml) + # safe_divide: avoid 0/0 in NaN-free regions; NaN propagates correctly + with np.errstate(invalid="ignore", divide="ignore"): + coh = np.where(denom > 0, np.abs(ifg_ml) / denom, 0.0).astype(np.float32) + return np.clip(coh, 0.0, 1.0) + + +def _output_geotransform( + input_gt: list[float], az_looks: int, rg_looks: int +) -> tuple[float, ...]: + """Compute output geotransform after multilooking. + + GDAL geotransform origins are upper-left pixel *corners*, so the output + corner stays at ``(x0, y0)``; only the pixel spacing scales. + """ + x0, dx, _, y0, _, dy = input_gt + return (x0, dx * rg_looks, 0.0, y0, 0.0, dy * az_looks) + + +def run_crossmul( + ref_file: Filename, + sec_file: Filename, + pair_dir: Path, + *, + date1: str, + date2: str, + options: CrossmulOptions | None = None, + subdataset: str = "/data/VV", + overwrite: bool = False, +) -> tuple[Path, Path]: + """Form a multilooked wrapped interferogram and coherence from two GSLCs. + + Parameters + ---------- + ref_file + Path to the reference (earlier) geocoded SLC (COMPASS HDF5). + sec_file + Path to the secondary (later) geocoded SLC. + pair_dir + Output directory for this pair (created if absent). + date1 + Reference date string ``YYYYMMDD``. + date2 + Secondary date string ``YYYYMMDD``. + options + Multilook and filter settings. Defaults to ``CrossmulOptions()``. + subdataset + HDF5 dataset path within the SLC file. + + Returns + ------- + ifg_path, coherence_path : tuple[Path, Path] + Complex interferogram (complex64) and coherence (float32) GeoTIFFs. + Wrapped phase is *not* saved here; derive it with ``np.angle()`` + after any stitching step so interpolation never crosses a +/-pi + discontinuity. + + """ + if options is None: + options = CrossmulOptions() + pair_dir.mkdir(parents=True, exist_ok=True) + + ifg_path = pair_dir / f"{date1}_{date2}_ifg.tif" + coh_path = pair_dir / f"{date1}_{date2}_coherence.tif" + + if ifg_path.exists() and coh_path.exists() and not overwrite: + logger.info(f"Pair {date1}_{date2} already exists; skipping crossmul.") + return ifg_path, coh_path + + ref_fmt = format_nc_filename(str(ref_file), subdataset) + sec_fmt = format_nc_filename(str(sec_file), subdataset) + + ncols, nrows = get_raster_xysize(ref_fmt) + gt = get_raster_gt(ref_fmt) + crs = get_raster_crs(ref_fmt) + + az_looks, rg_looks = options.looks + out_nrows = nrows // az_looks + out_ncols = ncols // rg_looks + out_gt = _output_geotransform(gt, az_looks, rg_looks) + + # Create output files (empty). Complex nodata = 0+0j; invalid pixels are + # identified by coherence == 0 rather than a NaN sentinel. + write_arr( + arr=None, + output_name=ifg_path, + shape=(out_nrows, out_ncols), + dtype=np.complex64, + driver="GTiff", + options=_GTIFF_OPTIONS, + geotransform=list(out_gt), + projection=crs, + nodata=0, + ) + write_arr( + arr=None, + output_name=coh_path, + shape=(out_nrows, out_ncols), + dtype=np.float32, + driver="GTiff", + options=_GTIFF_OPTIONS, + geotransform=list(out_gt), + projection=crs, + nodata=float("nan"), + ) + + block_in_rows = options.lines_per_block * az_looks + out_row = 0 + + for r0 in range(0, nrows - az_looks + 1, block_in_rows): + r1 = min(r0 + block_in_rows, (nrows // az_looks) * az_looks) + actual_in_rows = r1 - r0 + + ref_block = load_gdal(ref_fmt, rows=slice(r0, r1)).astype(np.complex64) + sec_block = load_gdal(sec_fmt, rows=slice(r0, r1)).astype(np.complex64) + + # Zero-fill NaN for crossmul; track valid mask + ref_nan = ~np.isfinite(ref_block.real) + sec_nan = ~np.isfinite(sec_block.real) + ref_block[ref_nan] = 0.0 + sec_block[sec_nan] = 0.0 + + ifg = ref_block * np.conj(sec_block) + ref_power = (ref_block.real**2 + ref_block.imag**2).astype(np.float32) + sec_power = (sec_block.real**2 + sec_block.imag**2).astype(np.float32) + + ifg_ml = _multilook(ifg, options.looks, options.filter_type) + ref_ml = _multilook(ref_power, options.looks, options.filter_type) + sec_ml = _multilook(sec_power, options.looks, options.filter_type) + + coh_block = _compute_coherence(ifg_ml, ref_ml, sec_ml) + ifg_block = ifg_ml.astype(np.complex64) + + # Zero out pixels where both SLCs had no data + both_nan = _multilook( + (ref_nan | sec_nan).astype(np.float32), options.looks, options.filter_type + ) + nodata_mask = both_nan > 0.5 + ifg_block[nodata_mask] = 0 + 0j + coh_block[nodata_mask] = np.nan + + n_out = actual_in_rows // az_looks + write_block(ifg_block[:n_out], ifg_path, row_start=out_row, col_start=0) + write_block(coh_block[:n_out], coh_path, row_start=out_row, col_start=0) + out_row += n_out + + logger.info( + f"Crossmul {date1}/{date2}: {out_nrows}x{out_ncols} pixels" + f" ({az_looks}x{rg_looks} looks, {options.filter_type})" + ) + return ifg_path, coh_path diff --git a/src/sweets/cli.py b/src/sweets/cli.py index 7a2ad24..6ed3461 100644 --- a/src/sweets/cli.py +++ b/src/sweets/cli.py @@ -384,14 +384,79 @@ def execute(self) -> None: workflow.run(starting_step=self.starting_step) +@dataclass +class IfgRunCmd: + """Run an interferogram workflow from a sweets_ifg_config.yaml.""" + + config_file: Annotated[Path, tyro.conf.Positional] + """Path to a sweets_ifg_config.yaml.""" + + starting_step: int = 1 + """Skip earlier stages (1=download, 2=geocode, 3=crossmul).""" + + def execute(self) -> None: + """Load the IfgWorkflow and run it.""" + if not self.config_file.exists(): + msg = f"config file {self.config_file} does not exist" + raise SystemExit(msg) + from sweets.ifg import IfgWorkflow + + workflow = IfgWorkflow.from_yaml(self.config_file) + workflow.run(starting_step=self.starting_step) + + +@dataclass +class ServerCmd: + """Launch the sweets web UI (FastAPI backend + bundled React frontend). + + Install the optional web extras first:: + + pip install -e ".[web]" # or: pixi install -e + + Then run ``sweets server`` to start uvicorn on http://localhost:8000. + During frontend development, run ``npm run dev`` inside + ``src/sweets/web/frontend/`` for hot-reloaded React on :5173 (Vite + proxies ``/api`` to :8000). + """ + + host: str = "127.0.0.1" + """Bind address. Use 0.0.0.0 to expose on the network.""" + + port: int = 8000 + """TCP port.""" + + reload: bool = False + """Enable uvicorn auto-reload (development only).""" + + def execute(self) -> None: + try: + import uvicorn + except ImportError as e: + msg = ( + "sweets server requires the `web` extras. Install via:\n" + ' pip install -e ".[web]"\n' + f"(original error: {e})" + ) + raise SystemExit(msg) from e + + uvicorn.run( + "sweets.web.app:app", + host=self.host, + port=self.port, + reload=self.reload, + ) + + def main() -> None: """Top-level CLI entry point.""" cmd = tyro.extras.subcommand_cli_from_dict( { "config": ConfigCli, "run": RunCmd, + "ifg-run": IfgRunCmd, "schema": SchemaCmd, "report": ReportCmd, + "server": ServerCmd, }, prog="sweets", description="Sentinel-1 InSAR workflow runner.", diff --git a/src/sweets/ifg.py b/src/sweets/ifg.py new file mode 100644 index 0000000..25d0124 --- /dev/null +++ b/src/sweets/ifg.py @@ -0,0 +1,1177 @@ +"""Interferogram workflow: crossmul + optional unwrap from geocoded SLCs. + +An alternative to the full dolphin displacement workflow that produces +multilooked wrapped (and optionally unwrapped) interferograms directly +from a stack of geocoded SLCs. + +The search/download/geocode stages are identical to the main +:class:`~sweets.core.Workflow`. Differences start at step 3: instead of +running dolphin's phase-linking pipeline, this workflow + +1. Selects pairs via a nearest-N or single-reference network. +2. Computes a multilooked interferogram + coherence per pair (blockwise, + pure NumPy / SciPy crossmul — no GPU required). +3. Optionally unwraps with dolphin's SNAPHU / SPURT / WHIRLWIND backends. + +Configuration serialises to / loads from ``sweets_ifg_config.yaml``. +""" + +from __future__ import annotations + +import re +import shutil +from concurrent.futures import ProcessPoolExecutor, ThreadPoolExecutor, wait +from functools import partial +from pathlib import Path +from typing import TYPE_CHECKING, Annotated, Any, Literal, Optional, Union + +from dolphin.utils import set_num_threads +from dolphin.workflows.config import YamlModel +from opera_utils import group_by_burst +from pydantic import ConfigDict, Field, computed_field, field_validator, model_validator +from shapely import wkt as shp_wkt + +from loguru import logger + +from ._burst_db import get_burst_db +from ._crossmul import CrossmulOptions, run_crossmul +from ._geocode_slcs import create_config_files, run_geocode, run_static_layers +from ._geometry import stitch_geometry +from ._log import log_runtime +from ._netrc import setup_nasa_netrc +from ._orbit import download_orbits +from ._types import Filename +from .dem import create_dem, create_water_mask +from .download import BurstSearch, LocalSafeSearch, NisarGslcSearch, OperaCslcSearch + +if TYPE_CHECKING: + pass + +Source = Annotated[ + Union[BurstSearch, LocalSafeSearch, OperaCslcSearch, NisarGslcSearch], + Field(discriminator="kind"), +] + +UnwrapMethod = Literal["snaphu", "spurt", "whirlwind"] + + +class NetworkOptions(YamlModel): + """Interferogram network selection options. + + Parameters + ---------- + max_bandwidth : int | None + Maximum number of nearest neighbors (by acquisition index) to include + in the interferogram network. ``None`` means only nearest-1. + reference_date : str | None + Date (``YYYY-MM-DD``) of a common reference SLC. When set, every + other SLC is paired against this one in addition to the nearest-N + network. Use alone (``max_bandwidth=0``) for a purely single- + reference (small-baseline-like) network. + max_temporal_baseline : float | None + Exclude pairs whose temporal separation exceeds this threshold + (days). Applied after the bandwidth and reference-date selection. + """ + + max_bandwidth: int = Field( + default=1, + ge=0, + description=( + "Nearest-neighbor depth. 1 = sequential pairs only;" + " 3 = add pairs up to 3 acquisitions apart." + ), + ) + reference_date: Optional[str] = Field( + default=None, + description=( + "Date of the common reference SLC (YYYY-MM-DD). When set, every" + " other date is also paired to this one regardless of bandwidth." + ), + ) + max_temporal_baseline: Optional[float] = Field( + default=None, + description=( + "Drop pairs whose temporal baseline exceeds this value (days)." + " None (default) applies no temporal-baseline cap." + ), + ) + + +class IfgUnwrapOptions(YamlModel): + """Unwrapping options. + + Parameters + ---------- + run_unwrap : bool + If False, only wrapped phase and coherence are produced. + unwrap_method : UnwrapMethod + Algorithm: ``"snaphu"`` (default), ``"spurt"``, or ``"whirlwind"``. + n_parallel_jobs : int + Interferograms to unwrap concurrently. + nlooks : float + Effective number of looks (used by SNAPHU for coherence-based + cost estimation). Set to ``az_looks * rg_looks`` when unset. + snaphu_ntiles : tuple[int, int] | "auto" + Tile grid for SNAPHU. ``"auto"`` selects 2x2 for small areas. + snaphu_tile_overlap : tuple[int, int] + Row and column overlap between SNAPHU tiles. + """ + + run_unwrap: bool = Field( + default=True, + description=( + "Run the unwrapping step. Set False to produce only wrapped" + " phase and coherence." + ), + ) + unwrap_method: UnwrapMethod = Field( + default="snaphu", + description="Unwrapping algorithm.", + ) + n_parallel_jobs: int = Field( + default=2, + ge=1, + description="Interferograms to unwrap concurrently.", + ) + nlooks: Optional[float] = Field( + default=None, + description=( + "Effective number of looks for cost estimation. Defaults to" + " ``az_looks * rg_looks`` from the crossmul options." + ), + ) + snaphu_ntiles: Union[tuple[int, int], Literal["auto"]] = Field( + default="auto", + description="SNAPHU tile grid (rows, cols). 'auto' picks a 2x2 grid.", + ) + snaphu_tile_overlap: tuple[int, int] = Field( + default=(128, 128), + description="SNAPHU tile overlap (rows, cols).", + ) + snaphu_cost: Literal["defo", "smooth"] = Field( + default="smooth", + description="SNAPHU statistical cost mode.", + ) + + +class StitchOptions(YamlModel): + """Options for stitching per-burst interferograms into a single output. + + Parameters + ---------- + run_stitch : bool + Merge all per-burst wrapped-phase and coherence files for each + date pair into a single stitched GeoTIFF. + crop_to_bbox : bool + Crop the stitched output to the workflow ``bbox``. Has no effect + when ``run_stitch`` is False. + run_burst_align : bool + Estimate and remove inter-burst phase offsets before stitching via + a least-squares constant (or planar) correction in each overlap + region. Requires ``dolphin.burst_alignment`` (available on the + ``feat/burst-alignment`` branch of dolphin; not yet on main). + burst_align_degree : {0, 1} + Polynomial degree for burst-alignment corrections: 0 = constant + DC offset per burst, 1 = planar ramp (offset + x-slope + y-slope). + """ + + run_stitch: bool = Field( + default=True, + description=( + "Merge per-burst interferograms into one stitched GeoTIFF per" + " date pair. Outputs land in /stitched/." + ), + ) + crop_to_bbox: bool = Field( + default=True, + description="Crop stitched output to the workflow bbox.", + ) + run_burst_align: bool = Field( + default=True, + description=( + "Estimate and remove inter-burst phase offsets before stitching." + " Requires dolphin.burst_alignment (feat/burst-alignment branch)." + ), + ) + burst_align_degree: Literal[0, 1] = Field( + default=0, + description="Burst-alignment polynomial degree: 0=constant, 1=planar ramp.", + ) + + +class IfgWorkflow(YamlModel): + """Interferogram-only workflow: geocode + crossmul + stitch (+ optional unwrap). + + Configuration is a strict subset of :class:`~sweets.core.Workflow` with + the ``dolphin`` displacement block replaced by a lightweight crossmul + + unwrap section. The search / download / geocode stages are identical. + """ + + work_dir: Path = Field( + default_factory=Path.cwd, + description="Root of working directory for processing.", + validate_default=True, + ) + bbox: Optional[tuple[float, float, float, float]] = Field( + default=None, + description=( + "AOI as (left, bottom, right, top) in decimal degrees." + " Either `bbox` or `wkt` must be set." + ), + ) + wkt: Optional[str] = Field( + default=None, + description="AOI as a WKT polygon (or path to a `.wkt` file). Overrides bbox.", + ) + search: Source = Field( + ..., + description=( + "Source of input SLCs — same options as the main Workflow:" + " BurstSearch, LocalSafeSearch, OperaCslcSearch, NisarGslcSearch." + ), + ) + dem_filename: Path = Field( + default_factory=lambda data: data["work_dir"] / "dem.tif", + description="DEM in EPSG:4326. Downloaded via sardem if absent.", + ) + dem_bbox: Optional[tuple[float, float, float, float]] = Field( + default=None, + description=( + "Optional DEM download extent override (left, bottom, right, top)." + ), + ) + water_mask_filename: Path = Field( + default_factory=lambda data: data["work_dir"] / "watermask.tif", + description="Water mask (uint8 GTiff, 1=land, 0=water).", + ) + orbit_dir: Path = Field( + default=Path("orbits"), + description="Directory for Sentinel-1 precise orbit files.", + validate_default=True, + ) + slc_posting: tuple[float, float] = Field( + default=(10, 5), + description="Geocoded SLC posting (y, x) in meters.", + ) + pol_type: Literal["co-pol", "cross-pol"] = Field( + default="co-pol", + description="Polarization type (COMPASS knob).", + ) + gpu_enabled: bool = Field( + default=True, + description="Run COMPASS geocoding on GPU when an isce3-cuda build is available.", + ) + + crossmul: CrossmulOptions = Field( + default_factory=CrossmulOptions, + description=( + "Multilooked interferogram options: look factors, filter type," + " and block size for streaming I/O." + ), + ) + network: NetworkOptions = Field( + default_factory=NetworkOptions, + description="Interferogram network selection (nearest-N and/or single-reference).", + ) + unwrap: IfgUnwrapOptions = Field( + default_factory=IfgUnwrapOptions, + description="Optional unwrapping step. Set `unwrap.run_unwrap = false` to skip.", + ) + stitch: StitchOptions = Field( + default_factory=StitchOptions, + description="Stitch per-burst interferograms and optionally crop to bbox.", + ) + + n_workers: int = Field( + default=4, + ge=1, + description="Process pool size for COMPASS geocoding.", + ) + threads_per_worker: int = Field( + default=8, + ge=1, + description="OMP_NUM_THREADS for each geocoding worker.", + ) + overwrite: bool = Field( + default=False, + description="Overwrite existing intermediate / output files.", + ) + + model_config = ConfigDict(extra="allow", populate_by_name=True) + + # ------------------------------------------------------------------ + # Validators (mirrored from core.Workflow) + # ------------------------------------------------------------------ + + @field_validator("wkt", mode="before") + @classmethod + def _check_file_and_parse_wkt(cls, v: Any) -> Any: + if v is None: + return v + if Path(v).exists(): + v = Path(v).read_text().strip() + try: + shp_wkt.loads(v) + except Exception as e: + msg = f"Invalid WKT string: {e}" + raise ValueError(msg) from e + return v + + @field_validator("work_dir", "orbit_dir") + @classmethod + def _expand_dirs(cls, v: Any) -> Path: + return Path(v).expanduser().resolve() + + @model_validator(mode="before") + @classmethod + def _sync_aoi(cls, values: Any) -> Any: + """Push top-level bbox/wkt into the search source (same as Workflow).""" + if not isinstance(values, dict): + return values + if "search" not in values: + values["search"] = {} + elif isinstance( + values["search"], + (BurstSearch, LocalSafeSearch, OperaCslcSearch, NisarGslcSearch), + ): + values["search"] = values["search"].model_dump( + exclude_unset=True, by_alias=True + ) + if isinstance(values["search"], dict) and "kind" not in values["search"]: + values["search"]["kind"] = "safe" + outer_bbox = values.get("bbox") + outer_wkt = values.get("wkt") + inner = values["search"] + inner_bbox = inner.get("bbox") + inner_wkt = inner.get("wkt") + bbox = outer_bbox or inner_bbox + wkt_value = outer_wkt or inner_wkt + if not bbox and not wkt_value: + msg = "Must specify `bbox` or `wkt` (on IfgWorkflow or `search`)" + raise ValueError(msg) + if bbox is not None: + values["bbox"] = bbox + if not inner_bbox: + inner["bbox"] = bbox + if outer_wkt is not None: + values["wkt"] = outer_wkt + if not inner_wkt: + inner["wkt"] = outer_wkt + return values + + @model_validator(mode="after") + def _set_bbox_and_wkt(self) -> "IfgWorkflow": + if self.bbox is None and self.wkt is not None: + self.bbox = shp_wkt.loads(self.wkt).bounds + assert self.bbox is not None + if self.bbox[1] > self.bbox[3]: + msg = f"Latitude min must be lower than max, got {self.bbox}" + raise ValueError(msg) + if self.bbox[0] > self.bbox[2]: + msg = f"Longitude min must be lower than max, got {self.bbox}" + raise ValueError(msg) + return self + + # ------------------------------------------------------------------ + # Computed paths + # ------------------------------------------------------------------ + + @computed_field # type: ignore[prop-decorator] + @property + def log_dir(self) -> Path: + return self.work_dir / "logs" + + @computed_field # type: ignore[prop-decorator] + @property + def gslc_dir(self) -> Path: + return self.work_dir / "gslcs" + + @computed_field # type: ignore[prop-decorator] + @property + def geom_dir(self) -> Path: + return self.work_dir / "geometry" + + @computed_field # type: ignore[prop-decorator] + @property + def ifg_dir(self) -> Path: + return self.work_dir / "interferograms" + + # DEM buffer constants (same as Workflow) + _DEM_BUFFER_DEG_COMPASS = 1.0 + _DEM_BUFFER_DEG_DEFAULT = 0.25 + + def _pad_bbox( + self, bbox: tuple[float, float, float, float], buf_deg: float + ) -> tuple[float, float, float, float]: + return ( + bbox[0] - buf_deg, + bbox[1] - buf_deg, + bbox[2] + buf_deg, + bbox[3] + buf_deg, + ) + + @property + def _dem_bbox(self) -> tuple[float, float, float, float]: + if self.dem_bbox is not None: + return self.dem_bbox + assert self.bbox is not None + buf = ( + self._DEM_BUFFER_DEG_COMPASS + if isinstance(self.search, (BurstSearch, LocalSafeSearch)) + else self._DEM_BUFFER_DEG_DEFAULT + ) + return self._pad_bbox(self.bbox, buf) + + @property + def _water_mask_bbox(self) -> tuple[float, float, float, float]: + assert self.bbox is not None + return self._pad_bbox(self.bbox, self._DEM_BUFFER_DEG_DEFAULT) + + # ------------------------------------------------------------------ + # Persistence helpers + # ------------------------------------------------------------------ + + def save(self, config_file: Filename = "sweets_ifg_config.yaml") -> None: + """Save this configuration to a YAML file.""" + logger.info(f"Saving IFG config to {config_file}") + self.to_yaml(config_file) + + @classmethod + def load(cls, config_file: Filename = "sweets_ifg_config.yaml") -> "IfgWorkflow": + """Load a configuration from a YAML file.""" + logger.info(f"Loading IFG config from {config_file}") + return cls.from_yaml(config_file) + + # ------------------------------------------------------------------ + # Step helpers (duplicated from core.Workflow) + # ------------------------------------------------------------------ + + _MIN_VALID_GSLC_BYTES = 1 * 1024 * 1024 + + def _existing_safes(self) -> list[Path]: + assert isinstance(self.search, (BurstSearch, LocalSafeSearch)) + return self.search.existing_safes() + + def _existing_gslcs(self) -> list[Path]: + if isinstance(self.search, OperaCslcSearch): + return [ + p + for p in self.search.existing_cslcs() + if p.stat().st_size >= self._MIN_VALID_GSLC_BYTES + ] + if isinstance(self.search, NisarGslcSearch): + import rasterio + + valid: list[Path] = [] + for p in self.search.existing_files(): + try: + with rasterio.open(p) as src: + assert not (src.transform.a == 1.0 and src.transform.e == 1.0) + assert src.crs is not None + except Exception as e: + logger.warning(f"Dropping {p.name}: not a valid raster ({e}).") + continue + valid.append(p) + return valid + return [ + p + for p in sorted(self.gslc_dir.glob("t*/*/t*.h5")) + if not p.name.startswith("static_") + and p.stat().st_size >= self._MIN_VALID_GSLC_BYTES + ] + + def _existing_static_layers(self) -> list[Path]: + if isinstance(self.search, OperaCslcSearch): + return self.search.existing_static_layers() + if isinstance(self.search, NisarGslcSearch): + return [] + return sorted(self.gslc_dir.glob("t*/*/static_*.h5")) + + def _gslc_root(self) -> Path: + if isinstance(self.search, (OperaCslcSearch, NisarGslcSearch)): + return self.search.out_dir + return self.gslc_dir + + def _apply_missing_data_filter(self, gslc_files: list[Path]) -> list[Path]: + if isinstance(self.search, NisarGslcSearch): + return gslc_files + if len(gslc_files) < 2: + return gslc_files + from opera_utils.missing_data import ( + get_missing_data_options, + print_with_rich, + ) + + try: + options = get_missing_data_options( + slc_files=[str(p) for p in gslc_files], + ) + except Exception as e: + logger.warning( + f"get_missing_data_options failed ({e}); skipping missing-data filter." + ) + return gslc_files + if not options: + logger.warning("No missing-data options returned; skipping filter.") + return gslc_files + + top = options[0] + if top.num_candidate_bursts == top.total_num_bursts: + logger.info( + f"Missing-data filter: all {top.total_num_bursts} CSLCs are complete;" + " nothing to exclude." + ) + return gslc_files + + logger.info(f"Missing-data filter: {len(options)} consistent subset option(s).") + print_with_rich(options, use_stderr=False) + logger.info( + f"Keeping option #1: {top.num_burst_ids} burst(s) x" + f" {top.num_dates} date(s) = {top.total_num_bursts} CSLCs." + ) + + kept_set = {Path(p) for p in top.inputs} + to_exclude = [p for p in gslc_files if p not in kept_set] + root = self._gslc_root().resolve() + excluded_dir = (self.work_dir / "excluded_cslcs").resolve() + for f in to_exclude: + src = f.resolve() + try: + rel = src.relative_to(root) + except ValueError: + rel = Path(src.name) + dst = excluded_dir / rel + dst.parent.mkdir(parents=True, exist_ok=True) + logger.warning(f"Excluding {rel} -> excluded_cslcs/{rel}") + shutil.move(str(src), str(dst)) + + return sorted(kept_set) + + @log_runtime + def _download(self) -> list[Path]: + if isinstance(self.search, OperaCslcSearch): + existing = self.search.existing_cslcs() + if existing and not self.overwrite: + logger.info( + f"Found {len(existing)} existing OPERA CSLCs; skipping download." + ) + else: + self.search.download() + existing_static = self.search.existing_static_layers() + n_bursts = len(self.search.burst_ids or []) + if n_bursts > 0: + # Explicit burst IDs: can compare counts exactly. + static_complete = len(existing_static) >= n_bursts + else: + # AOI mode: burst count is unknown without a network query. + # Require a full set (at least one per subdirectory file) — re-run + # with overwrite=True to force a fresh static-layer download. + static_complete = bool(existing_static) + if not static_complete or self.overwrite: + self.search.download_static_layers() + return self.search.existing_cslcs() + + if isinstance(self.search, NisarGslcSearch): + existing = self.search.existing_files() + if existing and not self.overwrite: + logger.info( + f"Found {len(existing)} existing NISAR GSLCs; skipping download." + ) + return existing + return self.search.download() + + if isinstance(self.search, LocalSafeSearch): + existing = self.search.existing_safes() + if not existing: + msg = ( + f"LocalSafeSearch.out_dir={self.search.out_dir} has no" + " S1 SAFE dirs or zip archives." + ) + raise RuntimeError(msg) + logger.info( + f"LocalSafeSearch: using {len(existing)} inputs from {self.search.out_dir}." + ) + return existing + + assert isinstance(self.search, BurstSearch) + existing = self.search.existing_safes() + if existing and not self.overwrite: + logger.info( + f"Found {len(existing)} existing SAFE dirs; skipping burst2safe." + ) + return existing + return self.search.download() + + @log_runtime + def _geocode_slcs( + self, safes: list[Path], dem_file: Path, burst_db_file: Path + ) -> tuple[list[Path], list[Path]]: + self.log_dir.mkdir(parents=True, exist_ok=True) + using_zipped = safes[0].suffix == ".zip" + compass_cfg_files = create_config_files( + slc_dir=safes[0].parent, + burst_db_file=burst_db_file, + dem_file=dem_file, + orbit_dir=self.orbit_dir, + bbox=self.bbox, + y_posting=self.slc_posting[0], + x_posting=self.slc_posting[1], + pol_type=self.pol_type, + out_dir=self.gslc_dir, + overwrite=self.overwrite, + using_zipped=using_zipped, + gpu_enabled=self.gpu_enabled, + ) + + existing = {p.name: p for p in self._existing_gslcs()} + logger.info(f"Found {len(existing)} existing GSLCs") + gslc_files: list[Path] = [] + todo: list[Path] = [] + for cfg in compass_cfg_files: + name = _cfg_to_filename(cfg) + if name in existing: + gslc_files.append(existing[name]) + else: + todo.append(cfg) + if todo: + run = partial(run_geocode, log_dir=self.log_dir) + with ProcessPoolExecutor(max_workers=self.n_workers) as pool: + gslc_files.extend(pool.map(run, todo)) + + static_existing = {p.name: p for p in self._existing_static_layers()} + first_per_burst = [ + cfgs[0] for cfgs in group_by_burst(compass_cfg_files).values() + ] + static_files: list[Path] = [] + static_todo: list[Path] = [] + for cfg in first_per_burst: + name = _cfg_to_static_filename(cfg) + if name in static_existing: + static_files.append(static_existing[name]) + else: + static_todo.append(cfg) + if static_todo: + run_sl = partial(run_static_layers, log_dir=self.log_dir) + with ProcessPoolExecutor(max_workers=self.n_workers) as pool: + static_files.extend(pool.map(run_sl, static_todo)) + + return sorted(gslc_files), sorted(static_files) + + @log_runtime + def _stitch_geometry(self, static_files: list[Path]) -> list[Path]: + from dolphin._types import Bbox + + bbox = Bbox(*self.bbox) if self.bbox is not None else None + return stitch_geometry( + geom_path_list=[Path(p) for p in static_files], + geom_dir=self.geom_dir, + dem_filename=self.dem_filename, + looks=self.crossmul.looks, + bbox=bbox, + overwrite=self.overwrite, + ) + + def _subdataset(self) -> str: + if isinstance(self.search, NisarGslcSearch): + return "/unused-for-raster-inputs" + return "/data/VV" + + # ------------------------------------------------------------------ + # IFG network + crossmul + # ------------------------------------------------------------------ + + @log_runtime + def _run_ifg_network(self, gslc_files: list[Path]) -> list[tuple[Path, Path]]: + """Form all interferograms in the network, grouped by burst ID. + + Geocoded SLCs from different bursts have different spatial extents and + cannot be directly crossmul'd together. We group by burst ID (the + directory two levels up from each HDF5, e.g. ``t146_312777_iw1``) and + run an independent interferogram network per burst. Outputs go into + ``//_/``. + + Returns + ------- + list of (phase_path, coherence_path) tuples for every produced pair. + + """ + from dolphin.interferogram import Network + + self.ifg_dir.mkdir(parents=True, exist_ok=True) + + subdataset = self._subdataset() + + # Group by burst ID (parent directory name, e.g. t146_312777_iw1). + # For OPERA / NISAR sources that are not burst-organized, all SLCs fall + # into the same "single burst" group. + burst_groups: dict[str, list[Path]] = {} + for slc in gslc_files: + burst_id = _burst_id_from_gslc(slc) + burst_groups.setdefault(burst_id, []).append(slc) + + products: list[tuple[Path, Path]] = [] + for burst_id, burst_slcs in sorted(burst_groups.items()): + burst_slcs_sorted = sorted(burst_slcs) + logger.info(f"Burst {burst_id}: {len(burst_slcs_sorted)} SLC(s)") + if len(burst_slcs_sorted) < 2: + logger.warning(f"Burst {burst_id}: only 1 SLC, skipping.") + continue + + burst_ifg_dir = self.ifg_dir / burst_id + burst_ifg_dir.mkdir(parents=True, exist_ok=True) + + # Build pair list via dolphin's Network + net = Network( + slc_list=burst_slcs_sorted, + outdir=burst_ifg_dir, + max_bandwidth=( + self.network.max_bandwidth + if self.network.max_bandwidth > 0 + else None + ), + max_temporal_baseline=self.network.max_temporal_baseline, + subdataset=subdataset, + write=False, + ) + pairs: list = list(net.slc_file_pairs) + + # Add single-reference pairs if requested + if self.network.reference_date is not None: + ref_date_str = self.network.reference_date.replace("-", "") + ref_slc: Path | None = None + for slc in burst_slcs_sorted: + if ref_date_str in slc.name: + ref_slc = slc + break + if ref_slc is None: + logger.warning( + f"Burst {burst_id}: reference_date" + f" {self.network.reference_date!r} not found; skipping" + " single-reference pairs." + ) + else: + existing_keys = {(str(a), str(b)) for a, b in pairs} + for sec_slc in burst_slcs_sorted: + if sec_slc == ref_slc: + continue + key = (str(ref_slc), str(sec_slc)) + if key not in existing_keys: + pairs.append((ref_slc, sec_slc)) + existing_keys.add(key) + + if not pairs: + logger.warning(f"Burst {burst_id}: no pairs formed; skipping.") + continue + + logger.info(f"Burst {burst_id}: forming {len(pairs)} interferogram(s)...") + for slc1, slc2 in pairs: + date1 = _date_from_gslc(Path(slc1)) + date2 = _date_from_gslc(Path(slc2)) + pair_dir = burst_ifg_dir / f"{date1}_{date2}" + phase_p, coh_p = run_crossmul( + ref_file=Path(slc1), + sec_file=Path(slc2), + pair_dir=pair_dir, + date1=date1, + date2=date2, + options=self.crossmul, + subdataset=subdataset, + overwrite=self.overwrite, + ) + products.append((phase_p, coh_p)) + + return products + + # ------------------------------------------------------------------ + # Optional unwrapping + # ------------------------------------------------------------------ + + @log_runtime + def _run_unwrap( + self, + ifg_products: list[tuple[Path, Path]], + ) -> list[Path]: + """Unwrap all wrapped-phase files. + + Returns + ------- + list[Path] + Paths to unwrapped-phase GeoTIFFs. + + """ + from dolphin.unwrap import run as dolphin_unwrap + from dolphin.workflows import UnwrapOptions + + # Derive wrapped-phase files from complex IFGs if needed (the stitched + # path already produces _wrapped_phase.tif; the per-burst path does not). + phase_files = [ + _ensure_wrapped_phase(p, overwrite=self.overwrite) for p, _ in ifg_products + ] + coh_files = [c for _, c in ifg_products] + + unw_dir = self.work_dir / "unwrapped" + unw_dir.mkdir(parents=True, exist_ok=True) + + opts = self.unwrap + az_looks, rg_looks = self.crossmul.looks + effective_nlooks = ( + opts.nlooks if opts.nlooks is not None else float(az_looks * rg_looks) + ) + + ntiles = (2, 2) if opts.snaphu_ntiles == "auto" else opts.snaphu_ntiles # type: ignore[assignment] + + unwrap_options = UnwrapOptions.model_validate( + { + "unwrap_method": opts.unwrap_method, + "n_parallel_jobs": opts.n_parallel_jobs, + "snaphu_options": { + "ntiles": list(ntiles), + "tile_overlap": list(opts.snaphu_tile_overlap), + "cost": opts.snaphu_cost, + }, + } + ) + + mask = self.water_mask_filename if self.water_mask_filename.exists() else None + + unw_files, _ = dolphin_unwrap( + ifg_filenames=phase_files, + cor_filenames=coh_files, + output_path=unw_dir, + unwrap_options=unwrap_options, + nlooks=effective_nlooks, + mask_filename=mask, + overwrite=self.overwrite, + ) + logger.info(f"Unwrapped {len(unw_files)} interferogram(s) in {unw_dir}") + return unw_files + + def _stitch_ifgs( + self, + ifg_products: list[tuple[Path, Path]], + ) -> list[tuple[Path, Path]]: + """Stitch per-burst interferograms into one file per date pair. + + Parameters + ---------- + ifg_products + Per-burst ``(wrapped_phase, coherence)`` path pairs produced by + :meth:`_run_ifg_network`. + + Returns + ------- + list[tuple[Path, Path]] + Stitched ``(wrapped_phase, coherence)`` path pairs in + ``/stitched/``. + + """ + from dolphin.stitching import merge_by_date + + stitch_dir = self.ifg_dir / "stitched" + stitch_dir.mkdir(parents=True, exist_ok=True) + + ifg_files = [p for p, _ in ifg_products] + coh_files = [c for _, c in ifg_products] + + from dolphin._types import Bbox + + out_bounds: Bbox | None = ( + Bbox(*self.bbox) if self.stitch.crop_to_bbox and self.bbox else None + ) + + if self.stitch.run_burst_align: + from opera_utils import group_by_date + + from sweets._burst_alignment import align_bursts + + align_dir = stitch_dir / "burst_aligned" + align_dir.mkdir(parents=True, exist_ok=True) + logger.info("Running burst alignment on complex IFG files...") + # Process each date pair's bursts independently — passing all pairs + # together would let the overlap detector compare same-geography + # bursts from different pairs and produce garbage offsets. + aligned: list[Path] = [] + for _dates, group in group_by_date(ifg_files).items(): + out, _ = align_bursts( + group, + align_dir, + degree=self.stitch.burst_align_degree, + ) + aligned.extend(out) + ifg_files = aligned + + logger.info( + f"Stitching {len(ifg_files)} per-burst interferogram pairs" + + (f" cropped to bbox {self.bbox}" if out_bounds else "") + ) + # Stitch complex IFGs first — GDAL interpolates real+imag independently, + # which is correct. Wrapped phase is derived after so interpolation + # never crosses a ±π discontinuity. + ifg_map = merge_by_date( + ifg_files, + output_dir=stitch_dir, + output_suffix="_ifg.tif", + out_bounds=out_bounds, + out_bounds_epsg=4326 if out_bounds else None, + overwrite=self.overwrite, + ) + coh_map = merge_by_date( + coh_files, + output_dir=stitch_dir, + output_suffix="_coherence.tif", + out_bounds=out_bounds, + out_bounds_epsg=4326 if out_bounds else None, + overwrite=self.overwrite, + ) + + # Derive wrapped-phase GeoTIFFs from the stitched complex IFGs. + stitched: list[tuple[Path, Path]] = [] + for date_key, ifg_path in sorted(ifg_map.items()): + coh_path = coh_map.get(date_key) + if coh_path is None: + continue + phase_path = _derive_wrapped_phase(ifg_path, overwrite=self.overwrite) + stitched.append((phase_path, coh_path)) + logger.info(f"Stitched {len(stitched)} interferogram pair(s) to {stitch_dir}") + return stitched + + # ------------------------------------------------------------------ + # Top-level run + # ------------------------------------------------------------------ + + @log_runtime + def run(self, starting_step: int = 1) -> list[tuple[Path, Path]]: + """Run the interferogram workflow. + + Parameters + ---------- + starting_step : int + Skip earlier stages: 1 = download, 2 = geocode, 3 = crossmul. + + Returns + ------- + list[tuple[Path, Path]] + ``(wrapped_phase_path, coherence_path)`` pairs for each interferogram. + + """ + setup_nasa_netrc() + set_num_threads(self.threads_per_worker) + self.work_dir.mkdir(parents=True, exist_ok=True) + self.log_dir.mkdir(parents=True, exist_ok=True) + + is_safe = isinstance(self.search, (BurstSearch, LocalSafeSearch)) + is_nisar = isinstance(self.search, NisarGslcSearch) + needs_compass = is_safe + + if starting_step <= 1: + with ThreadPoolExecutor(max_workers=4) as pool: + dem_fut = pool.submit(create_dem, self.dem_filename, self._dem_bbox) + mask_fut = pool.submit( + create_water_mask, + self.water_mask_filename, + self._water_mask_bbox, + ) + burst_db_fut = pool.submit(get_burst_db) if needs_compass else None + futures: list = [dem_fut, mask_fut] + if burst_db_fut is not None: + futures.append(burst_db_fut) + wait(futures) + dem_fut.result() + mask_fut.result() + burst_db_file = burst_db_fut.result() if burst_db_fut else None + self._download() + else: + burst_db_file = get_burst_db() if needs_compass else None + + if starting_step <= 2: + if isinstance(self.search, NisarGslcSearch): + logger.info("NISAR source: skipping COMPASS and geometry stitching.") + elif isinstance(self.search, OperaCslcSearch): + static_files = self._existing_static_layers() + if not static_files: + msg = ( + f"No CSLC-STATIC layers found in" + f" {self.search.static_layers_dir!s}." + ) + raise RuntimeError(msg) + self._stitch_geometry(static_files) + else: + safes = self._existing_safes() + if not safes: + msg = f"No SAFE dirs found in {self.search.out_dir}." + raise RuntimeError(msg) + download_orbits(self.search.out_dir, self.orbit_dir) + assert burst_db_file is not None + _, static_files = self._geocode_slcs( + safes, self.dem_filename, burst_db_file + ) + self._stitch_geometry(static_files) + + # Collect GSLCs + gslc_files = self._existing_gslcs() + logger.info(f"Found {len(gslc_files)} GSLC files for interferogram formation") + if not gslc_files: + where = ( + self.search.out_dir + if (is_nisar or isinstance(self.search, OperaCslcSearch)) + else self.gslc_dir + ) + msg = f"No GSLCs found in {where}." + raise RuntimeError(msg) + + gslc_files = self._apply_missing_data_filter(gslc_files) + if len(gslc_files) < 2: + msg = ( + f"Only 1 usable GSLC found ({gslc_files[0].name});" + " need at least 2 to form an interferogram." + ) + raise RuntimeError(msg) + + # Crossmul + if starting_step <= 3: + ifg_products = self._run_ifg_network(gslc_files) + else: + ifg_products = _collect_existing_ifg_products(self.ifg_dir) + + # Stitch per-burst interferograms + optional bbox crop + if self.stitch.run_stitch: + if starting_step <= 4: + stitched = self._stitch_ifgs(ifg_products) + else: + stitched = _collect_existing_ifg_products(self.ifg_dir / "stitched") + # Unwrap the stitched products (single file per pair, smaller) + if self.unwrap.run_unwrap: + self._run_unwrap(stitched) + return stitched + + # Unwrap per-burst products (no stitching requested) + if self.unwrap.run_unwrap: + self._run_unwrap(ifg_products) + + return ifg_products + + +# --------------------------------------------------------------------------- +# Private helpers +# --------------------------------------------------------------------------- + + +# Matches OPERA burst token like _T048-101101-IW3_ inside a filename stem. +# \b word-boundary doesn't work here because underscore is a word char. +_OPERA_BURST_RE = re.compile(r"(?:^|_)(T\d+-\d+-IW\d)(?:_|$)", re.IGNORECASE) + + +def _burst_id_from_gslc(path: Path) -> str: + """Extract burst ID from a GSLC path. + + Tries three strategies in order: + + 1. Grandparent directory name for COMPASS burst-organized output + (``//.h5``, e.g. ``t146_312777_iw1``). + 2. OPERA CSLC filename pattern ``T048-101101-IW3`` → ``t048_101101_iw3``. + 3. Falls back to ``"single"`` so non-burst sources still work. + """ + parts = path.parts + if len(parts) >= 3: + grandparent = parts[-3] + if ( + "_iw" in grandparent + or grandparent.startswith("t0") + or grandparent.startswith("t1") + ): + return grandparent + + m = _OPERA_BURST_RE.search(path.stem) + if m: + return m.group(1).replace("-", "_").lower() + + return "single" + + +def _date_from_gslc(path: Path) -> str: + """Extract YYYYMMDD date from a GSLC filename. + + For COMPASS files (``t078_165578_iw3_20221029.h5``) the date is the + last ``_``-delimited 8-digit token. For OPERA CSLCs the acquisition + date is embedded as ``20240101T232835Z``; ``opera_utils.get_dates`` + handles both formats and we take the first (earliest) date found. + """ + from opera_utils import get_dates + + dates = get_dates(path) + if dates: + return dates[0].strftime("%Y%m%d") + msg = f"Cannot extract YYYYMMDD date from GSLC filename: {path.name}" + raise ValueError(msg) + + +def _derive_wrapped_phase(ifg_path: Path, overwrite: bool = False) -> Path: + """Write ``_wrapped_phase.tif`` alongside a complex ``_ifg.tif``. + + Idempotent: returns the existing file if already present and not overwriting. + """ + import numpy as np + from dolphin.io import load_gdal, write_arr + from osgeo import gdal + + phase_path = Path(str(ifg_path).replace("_ifg.tif", "_wrapped_phase.tif")) + if phase_path.exists() and not overwrite: + return phase_path + + ds = gdal.Open(str(ifg_path)) + gt = ds.GetGeoTransform() + crs = ds.GetProjection() + ds = None + + ifg = load_gdal(ifg_path) + phase = np.angle(ifg).astype(np.float32) + phase[ifg == 0] = np.nan # propagate nodata + + write_arr( + arr=phase, + output_name=phase_path, + like_filename=ifg_path, + dtype=np.float32, + driver="GTiff", + geotransform=list(gt), + projection=crs, + nodata=float("nan"), + ) + return phase_path + + +def _ensure_wrapped_phase(ifg_path: Path, overwrite: bool = False) -> Path: + """Return the wrapped-phase path for an IFG, deriving it if needed.""" + if "_ifg.tif" in ifg_path.name: + return _derive_wrapped_phase(ifg_path, overwrite=overwrite) + return ifg_path + + +def _collect_existing_ifg_products(ifg_dir: Path) -> list[tuple[Path, Path]]: + """Collect already-produced (ifg, coherence) pairs from ``ifg_dir``. + + Handles both flat ``/`` and burst-grouped + ``//`` layouts. + """ + _SKIP_DIRS = {"stitched", "burst_aligned"} + products: list[tuple[Path, Path]] = [] + for ifg_f in sorted(ifg_dir.rglob("*_ifg.tif")): + if _SKIP_DIRS & set(ifg_f.relative_to(ifg_dir).parts): + continue + coh_f = ifg_f.parent / ifg_f.name.replace("_ifg.tif", "_coherence.tif") + if coh_f.exists(): + products.append((ifg_f, coh_f)) + return products + + +def _cfg_to_filename(cfg_path: Path) -> str: + """COMPASS runconfig path -> expected GSLC HDF5 filename.""" + date = cfg_path.name.split("_")[2] + burst = "_".join(cfg_path.stem.split("_")[3:]) + return f"{burst}_{date}.h5" + + +def _cfg_to_static_filename(cfg_path: Path) -> str: + """COMPASS runconfig path -> expected static-layers HDF5 filename.""" + burst = "_".join(cfg_path.stem.split("_")[3:]) + return f"static_layers_{burst}.h5" diff --git a/src/sweets/plotting.py b/src/sweets/plotting.py index b0ba353..873c5c8 100644 --- a/src/sweets/plotting.py +++ b/src/sweets/plotting.py @@ -466,3 +466,168 @@ def plot_area_of_interest( # Plot the area of interest area_gdf.plot(ax=ax, edgecolor="red", facecolor="None", lw=2) return fig, ax + + +def plot_ifg_pairs( + ifg_dir: Union[Path, str], + *, + max_pairs: int = 9, + figsize: Optional[tuple[float, float]] = None, + subsample: int = 2, + output_path: Optional[Union[Path, str]] = None, +) -> plt.Figure: + """Plot wrapped-phase and coherence thumbnails for IFG-workflow output. + + Scans ```` (and one level of subdirectories, for burst-grouped + layouts) for ``*_wrapped_phase.tif`` / ``*_coherence.tif`` pairs and + produces a grid of thumbnails. + + Parameters + ---------- + ifg_dir + Top-level interferogram output directory (``IfgWorkflow.ifg_dir``). + max_pairs + Maximum number of pairs to show. + figsize + Figure size. Auto-sized if None. + subsample + Spatial subsample factor (applied via ``dolphin.io.load_gdal``). + output_path + If given, save the figure to this path. + + Returns + ------- + matplotlib.figure.Figure + + """ + from dolphin import io as dolph_io + + ifg_dir = Path(ifg_dir) + phase_files = sorted(ifg_dir.rglob("*_wrapped_phase.tif"))[:max_pairs] + # Fall back to complex IFGs (per-burst outputs before stitching). + if not phase_files: + phase_files = sorted(ifg_dir.rglob("*_ifg.tif"))[:max_pairs] + if not phase_files: + raise FileNotFoundError(f"No interferogram files found under {ifg_dir}") + + n = len(phase_files) + ncols = min(n, 3) + nrows = (n + ncols - 1) // ncols + if figsize is None: + figsize = (ncols * 5, nrows * 4) + + fig, axes = plt.subplots(nrows, ncols * 2, figsize=figsize, squeeze=False) + fig.suptitle("IFG QA: Wrapped Phase (left) and Coherence (right)", fontsize=12) + + stats: list[dict] = [] + for i, phase_f in enumerate(phase_files): + is_complex = phase_f.name.endswith("_ifg.tif") + coh_suffix = "_coherence.tif" + coh_f = phase_f.parent / phase_f.name.replace( + "_ifg.tif" if is_complex else "_wrapped_phase.tif", coh_suffix + ) + row = i // ncols + col = (i % ncols) * 2 + + pair_tag = phase_f.stem.replace("_wrapped_phase", "").replace("_ifg", "") + + raw = dolph_io.load_gdal(phase_f, subsample_factor=subsample) + phase_data = np.angle(raw).astype(np.float32) if is_complex else raw + ax_p = axes[row][col] + im_p = ax_p.imshow( + phase_data, + cmap="oil_slick", + vmin=-np.pi, + vmax=np.pi, + interpolation="nearest", + ) + ax_p.set_title(pair_tag, fontsize=8) + ax_p.axis("off") + fig.colorbar(im_p, ax=ax_p, fraction=0.046, pad=0.04, label="rad") + + if coh_f.exists(): + coh_data = dolph_io.load_gdal(coh_f, subsample_factor=subsample) + valid = np.isfinite(coh_data) + mean_coh = float(np.nanmean(coh_data)) if valid.any() else float("nan") + ax_c = axes[row][col + 1] + im_c = ax_c.imshow( + coh_data, + cmap="viridis", + vmin=0, + vmax=1, + interpolation="nearest", + ) + ax_c.set_title(f"coh mean={mean_coh:.3f}", fontsize=8) + ax_c.axis("off") + fig.colorbar(im_c, ax=ax_c, fraction=0.046, pad=0.04) + stats.append({"pair": pair_tag, "mean_coherence": mean_coh}) + + # Hide unused axes + for i in range(n, nrows * ncols): + row = i // ncols + col = (i % ncols) * 2 + axes[row][col].axis("off") + axes[row][col + 1].axis("off") + + plt.tight_layout() + + if output_path is not None: + fig.savefig(output_path, dpi=150, bbox_inches="tight") + print(f"Saved QA figure to {output_path}") + + return fig + + +def save_ifg_qa_metrics( + ifg_dir: Union[Path, str], + output_path: Optional[Union[Path, str]] = None, +) -> list[dict]: + """Compute and save QA metrics for all IFG pairs. + + Computes mean/median coherence and valid-pixel fraction for each pair, + writes a JSON sidecar ``ifg_qa.json`` in ``ifg_dir``, and returns the + list of metric dicts. + + Parameters + ---------- + ifg_dir + Top-level interferogram output directory. + output_path + Path for the JSON output. Defaults to ``/ifg_qa.json``. + + Returns + ------- + list[dict] + One dict per pair: ``pair``, ``mean_coh``, ``median_coh``, + ``valid_frac``. + + """ + import json + + from dolphin import io as dolph_io + + ifg_dir = Path(ifg_dir) + coh_files = sorted(ifg_dir.rglob("*_coherence.tif")) + + metrics: list[dict] = [] + for coh_f in coh_files: + coh = dolph_io.load_gdal(coh_f) + valid = np.isfinite(coh) + if not valid.any(): + continue + metrics.append( + { + "pair": coh_f.stem.replace("_coherence", ""), + "burst": coh_f.parent.name, + "mean_coh": float(np.nanmean(coh)), + "median_coh": float(np.nanmedian(coh)), + "valid_frac": float(valid.mean()), + "file": str(coh_f), + } + ) + + if output_path is None: + output_path = ifg_dir / "ifg_qa.json" + Path(output_path).write_text(json.dumps(metrics, indent=2)) + print(f"Wrote QA metrics ({len(metrics)} pairs) to {output_path}") + return metrics diff --git a/src/sweets/web/README.md b/src/sweets/web/README.md new file mode 100644 index 0000000..b897292 --- /dev/null +++ b/src/sweets/web/README.md @@ -0,0 +1,205 @@ +# sweets web UI + +FastAPI backend + React/TypeScript frontend for the sweets InSAR workflow. + +## What it does + +1. **Search** — query CMR / ASF for OPERA CSLC bursts, Sentinel-1 SLC bursts, + or NISAR GSLC frames covering a map-drawn AOI + date range, and overlay + the granule outlines on the map. Runs the same missing-data filter sweets + uses on the actual download so the user sees, *before* kicking anything + off, which bursts will be kept (green) vs dropped as partial coverage + (red). +2. **Config** — render a form from `Workflow.model_json_schema()` via + `@rjsf/core`, so every Workflow / Dolphin / Tropo field is exposed + without hand-written form code. +3. **Monitor** — start a job, stream its logs over a WebSocket, watch the + step bar tick through download → geocode → ifg → stitch → unwrap. +4. **View** — once a job finishes, hand off to + [`bowser`](https://github.com/scottstanie/bowser) via + `bowser setup-dolphin /dolphin` (button in the job detail). + +## Screenshots + +**Search (empty)** — pick a source, type or draw an AOI, set a date range. + +![Empty search tab](../../../docs/web/screenshots/01-search-empty.png) + +**Search (results)** — real OPERA CSLC query over Los Angeles, Jan–Mar 2024 +(`bbox=[-118.5, 33.95, -118.0, 34.35]`). 39 granules from two tracks: T144 DESC +(26) and T71 ASC (13). The missing-data filter picked the 7-burst × 4-date +subset that forms a coherent stack — **28 green features kept, 11 red features +excluded**. The dashed orange box is the requested AOI. + +![39 LA bursts with green/red coverage](../../../docs/web/screenshots/02-search-results.png) + +**Narrow to one track** — sweets only processes a single track per job; clicking +a track chip in the sidebar re-runs the search filtered to that track. Here +we picked T144 DESC, so the ascending stack drops out: + +![Search narrowed to track 144 DESC](../../../docs/web/screenshots/02b-search-track-narrowed.png) + +**Granule list + export** — expand the list of returned granules, or grab the +whole set as a CSV or a newline-separated URL list suitable for `wget -i`: + +![Granule list with CSV/URL export buttons](../../../docs/web/screenshots/02c-granule-list.png) + +**Config (full-page)** — form auto-generated from `Workflow.model_json_schema()`. +The basic view shows the knobs most users actually touch; "Show advanced" +exposes the full nested dolphin / tropo configs. AOI + source come from the +Search tab, not the form. + +![Auto-generated config form](../../../docs/web/screenshots/03-config-form.png) + +With "Show advanced" on, the nested `DolphinOptions` and `TropoOptions` +pydantic models are folded in — phase-linking window, strides, unwrap +method, snaphu / spurt knobs, tropo step toggles, etc.: + +![Advanced config — dolphin section](../../../docs/web/screenshots/03b-config-advanced-dolphin.png) +![Advanced config — tropo section](../../../docs/web/screenshots/03c-config-advanced-tropo.png) + +**Jobs (empty)** — list, step-bar progress, WebSocket log tail, results +manifest, and a "View in bowser" button that shells +`bowser setup-dolphin /dolphin`. + +![Empty jobs tab](../../../docs/web/screenshots/04-jobs-empty.png) + +**Jobs (running)** — live OPERA CSLC job: 2 burst IDs +(`T071_151228_IW2/IW3`), 3-month window (Jan–Mar 2024), `n_workers=3`. +The step bar shows step 1 (download) pulsing; the WebSocket log tail is +streaming `sardem` / OPERA download messages; the manifest is already +populating with the GeoTIFFs that have landed on disk. + +![Jobs tab with a real OPERA job downloading](../../../docs/web/screenshots/04b-jobs-running.png) + +**Jobs (completed)** — same job after the pipeline finished +(end-to-end in ~3m 30s on this machine). All five step segments lit +blue, status flipped to green "COMPLETED", 86 entries in the results +manifest covering dem / watermask / OPERA CSLCs / geometry rasters / +21 unwrapped interferograms / 7 timeseries pairs / velocity.tif. +Click "Setup & open" to hand off the `dolphin/` outputs to +[bowser](https://github.com/scottstanie/bowser). + +![Jobs tab after the pipeline completed](../../../docs/web/screenshots/04c-jobs-completed.png) + +## Layout + +``` +src/sweets/web/ +├── app.py FastAPI factory (routers + static mount) +├── api/ +│ ├── jobs.py Job CRUD + start/cancel +│ ├── websocket.py /api/ws/jobs/{id}/logs +│ ├── schema.py /api/schema -> Workflow JSON schema +│ ├── search.py /api/search -> granule GeoJSON +│ └── results.py /api/jobs/{id}/manifest + /view (bowser) +├── models/ SQLModel job persistence (SQLite) +├── services/ +│ ├── executor.py Background `sweets run` subprocess +│ └── log_manager.py Per-job line buffer + WebSocket pub/sub +└── frontend/ React 18 + TS + Vite + Leaflet + ├── package.json + ├── tsconfig.json + ├── vite.config.ts Proxies /api -> localhost:8000 + └── src/ + ├── main.tsx + ├── App.tsx Sidebar tabs + map shell + ├── api.ts Typed fetch wrappers + ├── state.tsx React context (tab, bbox, source, ...) + ├── style.css Bowser-inspired dark theme + └── components/ + ├── MapView.tsx Leaflet + leaflet-draw rectangle + overlay + ├── SearchPanel.tsx Source / dates / track / frame search + ├── ConfigPanel.tsx RJSF schema-driven form + └── JobsPanel.tsx List + step bar + logs + manifest + bowser +``` + +## API + +| Method | Path | Purpose | +| ------ | --------------------------------- | -------------------------------- | +| GET | `/api/health` | Liveness | +| GET | `/api/schema` | `Workflow.model_json_schema()` | +| POST | `/api/search` | Granule GeoJSON for an AOI | +| GET | `/api/jobs/` | List jobs | +| POST | `/api/jobs/` | Create job | +| POST | `/api/jobs/{id}/start` | Spawn `sweets run` subprocess | +| POST | `/api/jobs/{id}/cancel` | SIGTERM the subprocess | +| GET | `/api/jobs/{id}/manifest` | List interesting output files | +| POST | `/api/jobs/{id}/view` | `bowser setup-dolphin` handoff | +| WS | `/api/ws/jobs/{id}/logs` | Live log stream | + +## Dev loop + +```bash +# Backend (needs the optional web extras) +pip install -e ".[web]" +sweets server --reload # uvicorn on :8000 + +# Frontend (separate terminal) +cd src/sweets/web/frontend +npm install +npm run dev # Vite on :5173, proxies /api +``` + +Open http://localhost:5173. Vite proxies `/api` and `/api/ws/*` through to +the backend, so the React app behaves identically to a production build. + +With pixi, the same loop is one-liner per terminal: + +```bash +pixi run -e web sweets-server # backend +pixi run -e web web-install # one-time: npm install +pixi run -e web web-dev # frontend +``` + +## Production + +```bash +cd src/sweets/web/frontend +npm install && npm run build # writes ./dist +cd - +sweets server --host 0.0.0.0 --port 8000 # serves dist/ as static +``` + +## Refreshing the screenshots + +The README images are regenerated by `scripts/web_screenshots.py`, which: +1. Rebuilds the frontend bundle (`npm run build`). +2. Boots a temporary uvicorn server on a free port. +3. Drives Playwright through every demo flow — search, track-narrow, + granule list expand, advanced config dolphin / tropo sections, jobs. +4. Writes PNGs into `docs/web/screenshots/`. +5. Kills the server. + +```bash +# One-time setup (inside the web pixi env): +playwright install chromium + +# Then, whenever the UI changes: +pixi run -e web web-screenshots +``` + +The search step hits live ASF / CMR APIs to give a realistic results +overlay; no credentials are required for the public granule queries. +CI does not run this — it needs a GUI browser binary and live network. +Refresh manually after any layout change or before publishing a new +demo to the team. + +## Storage + +Jobs are persisted in `~/.sweets/sweets.db` (SQLite). The `config` column +holds the full Workflow YAML as JSON; `work_dir` is denormalized onto the +row when the job starts so the manifest / bowser endpoints can find it +without re-parsing the config. + +## What's intentionally minimal + +- **Auth**: none. This is a local-first dev tool; bind to `127.0.0.1` and + don't expose it publicly. +- **CSS**: hand-rolled bowser-style dark theme. No Tailwind / MUI / etc. +- **Form UX**: RJSF default widgets. Replace per-field with custom widgets + if/when the auto-generated layout gets unwieldy. +- **Results viewer**: handed off to `bowser` rather than reimplemented. + The `/api/jobs/{id}/view` endpoint runs `bowser setup-dolphin` so the + user lands directly in the mature viewer. diff --git a/src/sweets/web/__init__.py b/src/sweets/web/__init__.py new file mode 100644 index 0000000..f7e8d19 --- /dev/null +++ b/src/sweets/web/__init__.py @@ -0,0 +1,12 @@ +"""Web UI for sweets — FastAPI backend with a React frontend.""" + +from __future__ import annotations + +__all__ = ["create_app"] + + +def create_app(): + """Create and configure the FastAPI application.""" + from sweets.web.app import app + + return app diff --git a/src/sweets/web/api/__init__.py b/src/sweets/web/api/__init__.py new file mode 100644 index 0000000..405deca --- /dev/null +++ b/src/sweets/web/api/__init__.py @@ -0,0 +1,3 @@ +"""API routes for sweets web UI.""" + +from __future__ import annotations diff --git a/src/sweets/web/api/jobs.py b/src/sweets/web/api/jobs.py new file mode 100644 index 0000000..78632a4 --- /dev/null +++ b/src/sweets/web/api/jobs.py @@ -0,0 +1,180 @@ +"""Job CRUD API endpoints.""" + +from __future__ import annotations + +import os +import signal +from datetime import datetime, timezone +from typing import Annotated + +from fastapi import APIRouter, Depends, HTTPException +from sqlmodel import Session, select + +from sweets.web.models import Job, JobCreate, JobRead, JobStatus, JobUpdate +from sweets.web.models.database import get_session +from sweets.web.services.executor import start_job_background +from sweets.web.services.log_manager import log_manager + +router = APIRouter() + +SessionDep = Annotated[Session, Depends(get_session)] + + +def _to_read(job: Job) -> JobRead: + """Convert a DB ``Job`` to a ``JobRead`` with the live step folded in. + + The executor only persists ``current_step`` to the DB at job completion + (final value committed in its ``finally`` block). While a job is running, + the log-line step-pattern parser inside ``LogManager`` already tracks + the higher value in memory, so we surface it here to keep the UI's + step-bar + "step N/5" label accurate without an extra DB write per line. + + Returning a fresh ``JobRead`` (instead of mutating the SQLModel + instance) avoids the footgun where a stray ``session.commit()`` + later in the request lifecycle would persist the in-memory bump + over the real value. + """ + data = JobRead.model_validate(job) + if job.id is not None: + live = log_manager.get_current_step(job.id) + if live > data.current_step: + data.current_step = live + return data + + +@router.get("/") +def list_jobs( + session: SessionDep, + skip: int = 0, + limit: int = 100, + status: JobStatus | None = None, +) -> list[JobRead]: + """List all jobs, optionally filtered by status.""" + query = ( + select(Job) + .offset(skip) + .limit(limit) + .order_by(Job.created_at.desc()) # type: ignore[attr-defined] + ) + if status: + query = query.where(Job.status == status) + return [_to_read(j) for j in session.exec(query).all()] + + +@router.post("/", response_model=JobRead) +def create_job(job: JobCreate, session: SessionDep): + """Create a new job (does not start it).""" + db_job = Job.model_validate(job) + session.add(db_job) + session.commit() + session.refresh(db_job) + return db_job + + +@router.get("/{job_id}") +def get_job(job_id: int, session: SessionDep) -> JobRead: + """Get a job by ID.""" + job = session.get(Job, job_id) + if not job: + raise HTTPException(status_code=404, detail="Job not found") + return _to_read(job) + + +@router.patch("/{job_id}", response_model=JobRead) +def update_job(job_id: int, job_update: JobUpdate, session: SessionDep): + """Update a job.""" + job = session.get(Job, job_id) + if not job: + raise HTTPException(status_code=404, detail="Job not found") + + update_data = job_update.model_dump(exclude_unset=True) + for key, value in update_data.items(): + setattr(job, key, value) + + session.add(job) + session.commit() + session.refresh(job) + return job + + +@router.delete("/{job_id}") +def delete_job(job_id: int, session: SessionDep): + """Delete a job.""" + job = session.get(Job, job_id) + if not job: + raise HTTPException(status_code=404, detail="Job not found") + + # Don't allow deleting running jobs + if job.status == JobStatus.RUNNING: + raise HTTPException(status_code=400, detail="Cannot delete a running job") + + # Clear log buffer + log_manager.clear_buffer(job_id) + + session.delete(job) + session.commit() + return {"ok": True} + + +@router.post("/{job_id}/start", response_model=JobRead) +def start_job(job_id: int, session: SessionDep): + """Start a pending job.""" + job = session.get(Job, job_id) + if not job: + raise HTTPException(status_code=404, detail="Job not found") + + if job.status != JobStatus.PENDING: + raise HTTPException( + status_code=400, + detail=f"Job is {job.status.value}, can only start pending jobs", + ) + + # Start in background thread with log streaming + start_job_background(job_id, job.config) + + # Refresh to get updated status + session.refresh(job) + return job + + +@router.post("/{job_id}/cancel", response_model=JobRead) +def cancel_job(job_id: int, session: SessionDep): + """Cancel a running job.""" + job = session.get(Job, job_id) + if not job: + raise HTTPException(status_code=404, detail="Job not found") + + if job.status != JobStatus.RUNNING: + raise HTTPException(status_code=400, detail="Job is not running") + + if job.pid: + try: + os.kill(job.pid, signal.SIGTERM) + except ProcessLookupError: + pass # Already dead + + job.status = JobStatus.CANCELLED + job.completed_at = datetime.now(timezone.utc) + job.pid = None + + log_manager.append_log(job_id, "Job cancelled by user") + + session.add(job) + session.commit() + session.refresh(job) + return job + + +@router.get("/{job_id}/logs") +def get_job_logs(job_id: int, session: SessionDep): + """Get buffered logs for a job (for non-WebSocket clients).""" + job = session.get(Job, job_id) + if not job: + raise HTTPException(status_code=404, detail="Job not found") + + buffer = log_manager.get_buffer(job_id) + return { + "job_id": job_id, + "lines": buffer.get_history(), + "current_step": buffer.current_step, + } diff --git a/src/sweets/web/api/results.py b/src/sweets/web/api/results.py new file mode 100644 index 0000000..d67bb49 --- /dev/null +++ b/src/sweets/web/api/results.py @@ -0,0 +1,197 @@ +"""Job results: on-disk manifest + bowser handoff. + +The manifest endpoint walks the job's working directory and reports the +"interesting" output files (GSLCs, dolphin outputs, DEM, water mask, etc.) +so the UI can show a results panel without re-deriving paths from the +config schema. + +The bowser endpoint shells out to ``bowser setup-dolphin `` +to convert dolphin outputs into bowser-readable form and (optionally) starts +a `bowser` dev/server process so the user can click straight into the viewer. +""" + +from __future__ import annotations + +import shutil +import subprocess +from pathlib import Path +from typing import Annotated + +from fastapi import APIRouter, Depends, HTTPException +from sqlmodel import Session + +from sweets.web.models import Job +from sweets.web.models.database import get_session + +router = APIRouter() + +SessionDep = Annotated[Session, Depends(get_session)] + + +# Globs of "interesting" files relative to the work_dir. Keep this list short +# and focused — the frontend renders them inline, so dumping every file in +# the work_dir would be noisy. +MANIFEST_GLOBS: list[tuple[str, str]] = [ + ("dem", "dem.tif"), + ("watermask", "watermask.tif"), + ("config", "sweets_config.yaml"), + ("config", "sweets_ifg_config.yaml"), + ("report", "sweets_report.html"), + ("gslc", "gslcs/**/t*.h5"), + ("opera-cslc", "data/OPERA_L2_CSLC-S1_*.h5"), + ("nisar-gslc", "data/NISAR_L2_GSLC_*.h5"), + ("geometry", "geometry/*.tif"), + ("dolphin-unwrapped", "dolphin/unwrapped/*.tif"), + ("dolphin-timeseries", "dolphin/timeseries/*.tif"), + ("dolphin-velocity", "dolphin/timeseries/velocity.tif"), + # IFG workflow outputs + ("ifg-complex", "interferograms/**/*_ifg.tif"), + ("ifg-phase", "interferograms/**/*_wrapped_phase.tif"), + ("ifg-coherence", "interferograms/**/*_coherence.tif"), + ("ifg-unwrapped", "interferograms/**/unwrapped/*.tif"), + ("ifg-unwrapped", "unwrapped/*.tif"), + ("ifg-qa", "interferograms/ifg_qa.json"), + ("ifg-qa-plot", "ifg_qa.png"), +] + + +def _resolve_work_dir(job: Job) -> Path | None: + if job.work_dir: + return Path(job.work_dir) + cfg = job.config or {} + wd = cfg.get("work_dir") + if wd: + return Path(wd) + return None + + +@router.get("/{job_id}/manifest") +def get_manifest(job_id: int, session: SessionDep) -> dict: + """List interesting output files under the job's work_dir.""" + job = session.get(Job, job_id) + if not job: + raise HTTPException(404, "Job not found") + + work_dir = _resolve_work_dir(job) + if work_dir is None or not work_dir.exists(): + return { + "job_id": job_id, + "work_dir": str(work_dir) if work_dir else None, + "exists": False, + "entries": [], + } + + seen: set[Path] = set() + entries: list[dict] = [] + for kind, pattern in MANIFEST_GLOBS: + for p in sorted(work_dir.glob(pattern)): + if p in seen or not p.is_file(): + continue + seen.add(p) + entries.append( + { + "path": str(p.relative_to(work_dir)), + "size": p.stat().st_size, + "kind": kind, + } + ) + + return { + "job_id": job_id, + "work_dir": str(work_dir), + "exists": True, + "entries": entries, + } + + +@router.post("/{job_id}/view") +def bowser_view( + job_id: int, + session: SessionDep, + autostart: bool = False, + port: int = 4280, +) -> dict: + """Run ``bowser setup-dolphin `` and (optionally) start bowser. + + Always returns the command we would have run plus the resolved + ``dolphin_dir``, so the UI can show the exact CLI invocation to the user + even when ``bowser`` isn't on PATH. When ``autostart`` is true and + ``bowser`` is available, kicks off a detached ``bowser serve`` and returns + the local URL. + """ + job = session.get(Job, job_id) + if not job: + raise HTTPException(404, "Job not found") + + work_dir = _resolve_work_dir(job) + if work_dir is None: + raise HTTPException(400, "Job has no resolved work_dir") + + # IFG jobs produce interferograms/, not dolphin/ — bowser doesn't apply. + cfg = job.config or {} + if "crossmul" in cfg: + ifg_dir = work_dir / "interferograms" + return { + "job_id": job_id, + "dolphin_dir": str(ifg_dir), + "command": f"open {ifg_dir}", + "url": None, + "ran": False, + "stdout": "", + "stderr": ( + f"Bowser is for dolphin displacement outputs. " + f"IFG results are in: {ifg_dir}" + ), + } + + dolphin_dir = work_dir / "dolphin" + cmd = f"bowser setup-dolphin {dolphin_dir}" + + bowser_bin = shutil.which("bowser") + if bowser_bin is None or not dolphin_dir.exists(): + return { + "job_id": job_id, + "dolphin_dir": str(dolphin_dir), + "command": cmd, + "url": None, + "ran": False, + "stdout": "", + "stderr": ( + "bowser CLI not found on PATH" + if bowser_bin is None + else f"{dolphin_dir} does not exist yet" + ), + } + + proc = subprocess.run( + [bowser_bin, "setup-dolphin", str(dolphin_dir)], + capture_output=True, + text=True, + check=False, + ) + + url = None + if autostart and proc.returncode == 0: + # Best-effort: kick off `bowser serve` detached and surface the URL. + # Failures here aren't fatal — the manual command still works. + try: + subprocess.Popen( # noqa: S603 - controlled args + [bowser_bin, "serve", "--port", str(port)], + cwd=str(dolphin_dir), + stdout=subprocess.DEVNULL, + stderr=subprocess.DEVNULL, + start_new_session=True, + ) + url = f"http://localhost:{port}/" + except FileNotFoundError: + pass + + return { + "job_id": job_id, + "dolphin_dir": str(dolphin_dir), + "command": cmd, + "url": url, + "ran": proc.returncode == 0, + "stdout": proc.stdout, + "stderr": proc.stderr, + } diff --git a/src/sweets/web/api/schema.py b/src/sweets/web/api/schema.py new file mode 100644 index 0000000..02d48fc --- /dev/null +++ b/src/sweets/web/api/schema.py @@ -0,0 +1,27 @@ +"""JSON Schema endpoints for sweets workflow configurations. + +Exposes schema for both the full displacement workflow and the lighter +interferogram-only workflow so the frontend can auto-generate config forms. +""" + +from __future__ import annotations + +from fastapi import APIRouter + +router = APIRouter() + + +@router.get("") +def workflow_schema() -> dict: + """Return the JSON Schema for ``sweets.core.Workflow`` (displacement).""" + from sweets.core import Workflow + + return Workflow.model_json_schema() + + +@router.get("/ifg") +def ifg_workflow_schema() -> dict: + """Return the JSON Schema for ``sweets.ifg.IfgWorkflow`` (interferogram).""" + from sweets.ifg import IfgWorkflow + + return IfgWorkflow.model_json_schema() diff --git a/src/sweets/web/api/search.py b/src/sweets/web/api/search.py new file mode 100644 index 0000000..0826711 --- /dev/null +++ b/src/sweets/web/api/search.py @@ -0,0 +1,352 @@ +"""Granule search endpoint. + +Returns a GeoJSON ``FeatureCollection`` of granule outlines for the requested +source, AOI, and date range. The frontend overlays these on the Leaflet map +so the user can see exactly which bursts / frames their search will pull in +before kicking off a download. + +Three sources are supported, each backed by a small wrapper around an upstream +search call (no new CMR code in sweets): + +- ``safe`` : Sentinel-1 SLC bursts via ``asf_search.search``. +- ``opera-cslc`` : OPERA L2_CSLC-S1 bursts via ``opera_utils.download.search_cslcs``. +- ``nisar-gslc`` : NISAR L2_GSLC frames via ``opera_utils.nisar.search``. +""" + +from __future__ import annotations + +from datetime import datetime +from typing import Any, Literal, Optional + +from fastapi import APIRouter, HTTPException +from pydantic import BaseModel, Field + +router = APIRouter() + + +SourceKind = Literal["safe", "opera-cslc", "nisar-gslc"] + + +class SearchRequest(BaseModel): + """User-side search parameters from the map / search panel.""" + + source: SourceKind + bbox: tuple[float, float, float, float] = Field( + ..., description="(left, bottom, right, top) in decimal degrees." + ) + start: str = Field(..., description="ISO date or datetime.") + end: str = Field(..., description="ISO date or datetime.") + track: Optional[int] = None + frame: Optional[int] = None + + +def _feature( + name: str, + geometry: dict, + *, + date: str = "", + track: Optional[int] = None, + burst_id: Optional[str] = None, + frame: Optional[int] = None, + url: Optional[str] = None, + flight_direction: Optional[str] = None, +) -> dict: + return { + "type": "Feature", + "properties": { + "name": name, + "date": date, + "track": track, + "burst_id": burst_id, + "frame": frame, + "url": url, + "flight_direction": _norm_direction(flight_direction), + # Filled in later by _annotate_coverage; default to True so + # sources without burst-level coverage (NISAR) still render. + "in_coverage": True, + }, + "geometry": geometry, + } + + +def _norm_direction(v: Any) -> Optional[str]: + """Normalize various CMR/ASF flight-direction encodings to ASC/DESC. + + Returns ``None`` for anything we can't confidently map. NISAR CMR + granules expose orbit direction as ``AscendingFlag = "T" | "F"``; the + raw "T"/"F" would otherwise leak into the UI's track chips. + """ + if v is None: + return None + s = str(v).strip().upper() + if s in {"ASCENDING", "ASC", "ASCEND"}: + return "ASCENDING" + if s in {"DESCENDING", "DESC", "DESCEND"}: + return "DESCENDING" + if s in {"T", "TRUE", "1"}: + return "ASCENDING" + if s in {"F", "FALSE", "0"}: + return "DESCENDING" + return None + + +def _annotate_coverage(features: list[dict]) -> dict[str, Any]: + """Run the same missing-data analysis sweets uses on actual downloads. + + Mirrors :meth:`sweets.core.Workflow._apply_missing_data_filter` so the + map preview shows the user, *before* the download, which bursts will + end up in the chosen consistent subset and which will be dropped. The + optimization is "maximize total bursts s.t. every chosen burst has + every chosen date" — see :func:`opera_utils.missing_data.get_missing_data_options`. + + Returns a small summary dict describing the chosen option, or an + empty dict when coverage analysis isn't applicable (e.g. NISAR, or + every feature already covers every date). + """ + from datetime import datetime as _dt + + tuples: list[tuple[str, _dt]] = [] + for f in features: + p = f["properties"] + bid = p.get("burst_id") + date = (p.get("date") or "")[:10] + if not bid or not date: + continue + try: + tuples.append((bid, _dt.fromisoformat(date))) + except ValueError: + continue + + if len(tuples) < 2: + return {} + + try: + from opera_utils.missing_data import get_missing_data_options + except ImportError: + return {} + + options = get_missing_data_options(burst_id_date_tuples=tuples) + if not options: + return {} + + top = options[0] + chosen_bursts = set(top.burst_ids) + chosen_dates = {d.date().isoformat() for d in top.dates} + + in_coverage = 0 + for f in features: + p = f["properties"] + bid = p.get("burst_id") + date = (p.get("date") or "")[:10] + if bid in chosen_bursts and date in chosen_dates: + p["in_coverage"] = True + in_coverage += 1 + else: + p["in_coverage"] = False + + return { + "num_bursts": len(chosen_bursts), + "num_dates": len(chosen_dates), + "num_features_in_coverage": in_coverage, + "num_features_excluded": len(features) - in_coverage, + "num_options": len(options), + } + + +def _safe_search(req: SearchRequest) -> list[dict]: + import asf_search as asf + + opts = asf.ASFSearchOptions( + platform=asf.PLATFORM.SENTINEL1, + processingLevel=asf.PRODUCT_TYPE.BURST, + start=req.start, + end=req.end, + intersectsWith=_bbox_to_wkt(req.bbox), + ) + if req.track is not None: + opts.relativeOrbit = req.track + results = asf.search(opts=opts) + out: list[dict] = [] + for r in results: + geom = r.geometry + props = r.properties + out.append( + _feature( + name=props.get("sceneName") or props.get("fileID", "?"), + geometry=geom, + date=props.get("startTime", ""), + track=props.get("pathNumber"), + burst_id=str(props.get("burst", {}).get("fullBurstID", "") or "") + or None, + url=props.get("url"), + flight_direction=props.get("flightDirection"), + ) + ) + return out + + +def _opera_cslc_search(req: SearchRequest) -> list[dict]: + from opera_utils.download import search_cslcs + + results = search_cslcs( + start=_to_dt(req.start), + end=_to_dt(req.end), + bounds=req.bbox, + track=req.track, + ) + out: list[dict] = [] + for r in results: + props = getattr(r, "properties", {}) or {} + geom = getattr(r, "geometry", None) + if geom is None: + continue + burst_id = props.get("operaBurstID") or props.get("burstID") + out.append( + _feature( + name=props.get("sceneName") or props.get("fileID", burst_id or "?"), + geometry=geom, + date=props.get("startTime", ""), + track=props.get("pathNumber"), + burst_id=burst_id, + url=props.get("url"), + flight_direction=props.get("flightDirection"), + ) + ) + return out + + +def _nisar_search(req: SearchRequest) -> list[dict]: + from opera_utils.nisar import search + + results = search( + bbox=req.bbox, + relative_orbit_number=req.track, + track_frame_number=req.frame, + start_datetime=_to_dt(req.start), + end_datetime=_to_dt(req.end), + ) + out: list[dict] = [] + for r in results: + # opera_utils.nisar.search may return either CMR JSON-like dicts or + # asf_search ASFProduct objects depending on opera_utils version. + # Pull a polygon out of whichever shape we get. + geom, props = _extract_geom_and_props(r) + if geom is None: + continue + name = props.get("granule_ur") or props.get("sceneName") or "?" + out.append( + _feature( + name=name, + geometry=geom, + date=props.get("startTime", "") or props.get("time_start", ""), + track=props.get("track") or props.get("pathNumber"), + frame=props.get("frame"), + url=props.get("url"), + flight_direction=props.get("flightDirection") + or props.get("ascendingFlag"), + ) + ) + return out + + +def _extract_geom_and_props(r: Any) -> tuple[Optional[dict], dict]: + """Adapt asf_search.ASFProduct, dict, or umm-json hit to (geometry, properties).""" + if hasattr(r, "geometry") and hasattr(r, "properties"): + return r.geometry, dict(getattr(r, "properties") or {}) + if isinstance(r, dict): + # umm-json hit shape: {"umm": {"SpatialExtent": ...}} + umm = r.get("umm", {}) + spatial = ( + umm.get("SpatialExtent", {}) + .get("HorizontalSpatialDomain", {}) + .get("Geometry", {}) + ) + polys = spatial.get("GPolygons", []) + if polys: + pts = polys[0].get("Boundary", {}).get("Points", []) + coords = [[p["Longitude"], p["Latitude"]] for p in pts] + if coords and coords[0] != coords[-1]: + coords.append(coords[0]) + return {"type": "Polygon", "coordinates": [coords]}, _flatten_umm(umm) + return None, _flatten_umm(umm) + return None, {} + + +def _flatten_umm(umm: dict) -> dict: + out: dict[str, Any] = {} + out["granule_ur"] = umm.get("GranuleUR") + t = umm.get("TemporalExtent", {}).get("RangeDateTime", {}) + out["startTime"] = t.get("BeginningDateTime") + for attr in umm.get("AdditionalAttributes", []) or []: + name = attr.get("Name") + vals = attr.get("Values") or [] + if name and vals: + out[name] = vals[0] + return out + + +def _bbox_to_wkt(bbox: tuple[float, float, float, float]) -> str: + left, bottom, right, top = bbox + return ( + f"POLYGON(({left} {bottom}, {right} {bottom}, " + f"{right} {top}, {left} {top}, {left} {bottom}))" + ) + + +def _to_dt(s: str) -> datetime: + from dateutil.parser import parse as parse_date + + return parse_date(s) + + +@router.post("") +def search_granules(req: SearchRequest) -> dict: + """Return a GeoJSON FeatureCollection of matching granule outlines. + + Each feature is annotated with ``properties.in_coverage`` so the map + can show the user which bursts will actually be processed (i.e. the + largest consistent (burst, date) subset) vs which would be filtered + out as partial-coverage during the missing-data step. NISAR is granule- + per-frame and skips this analysis. + """ + if req.source == "safe": + features = _safe_search(req) + elif req.source == "opera-cslc": + features = _opera_cslc_search(req) + elif req.source == "nisar-gslc": + features = _nisar_search(req) + else: # pragma: no cover - exhaustive by type + raise HTTPException(400, f"Unknown source: {req.source}") + + coverage = _annotate_coverage(features) if req.source != "nisar-gslc" else {} + + return { + "type": "FeatureCollection", + "features": features, + "count": len(features), + "source": req.source, + "coverage": coverage, + "tracks": _summarize_tracks(features), + } + + +def _summarize_tracks(features: list[dict]) -> list[dict]: + """Group features by (track, flight_direction) with a granule count. + + The frontend uses this to render a track picker — sweets only downloads + one track at a time, and the user typically wants to see which tracks + actually have data over the AOI before narrowing. + """ + by_key: dict[tuple[Optional[int], Optional[str]], int] = {} + for f in features: + p = f["properties"] + key = (p.get("track"), p.get("flight_direction")) + by_key[key] = by_key.get(key, 0) + 1 + return [ + {"track": t, "flight_direction": d, "count": n} + for (t, d), n in sorted( + by_key.items(), + key=lambda kv: (-kv[1], kv[0][0] if kv[0][0] is not None else -1), + ) + if t is not None + ] diff --git a/src/sweets/web/api/websocket.py b/src/sweets/web/api/websocket.py new file mode 100644 index 0000000..d3f2868 --- /dev/null +++ b/src/sweets/web/api/websocket.py @@ -0,0 +1,97 @@ +"""WebSocket endpoints for live log streaming.""" + +from __future__ import annotations + +import asyncio + +from fastapi import APIRouter, WebSocket, WebSocketDisconnect +from sqlmodel import Session + +from sweets.web.models import Job, JobStatus +from sweets.web.models.database import engine +from sweets.web.services.log_manager import log_manager + +router = APIRouter() + + +@router.websocket("/jobs/{job_id}/logs") +async def job_logs_websocket(websocket: WebSocket, job_id: int): + """WebSocket endpoint for streaming job logs. + + Sends: + - {"type": "history", "lines": [...], "step": N} on connect + - {"type": "log", "line": "...", "step": N} for each new line + - {"type": "status", "status": "completed|failed|cancelled"} when job ends + """ + await websocket.accept() + + # Verify job exists + with Session(engine) as session: + job = session.get(Job, job_id) + if not job: + await websocket.send_json({"type": "error", "message": "Job not found"}) + await websocket.close() + return + + initial_status = job.status + + # Get log buffer and subscribe + buffer = log_manager.get_buffer(job_id) + queue = buffer.subscribe() + + try: + # Send history first + history = buffer.get_history() + await websocket.send_json( + { + "type": "history", + "lines": history, + "step": buffer.current_step, + } + ) + + # If job already finished, send final status and close + if initial_status in ( + JobStatus.COMPLETED, + JobStatus.FAILED, + JobStatus.CANCELLED, + ): + await websocket.send_json( + { + "type": "status", + "status": initial_status.value, + } + ) + return + + # Stream new logs + terminal = { + JobStatus.COMPLETED, + JobStatus.FAILED, + JobStatus.CANCELLED, + } + while True: + try: + # Wait for new log with timeout to check job status + msg = await asyncio.wait_for(queue.get(), timeout=2.0) + await websocket.send_json(msg) + except asyncio.TimeoutError: + # Check if the job has finished — or been deleted while we + # were watching. The deleted case needs an explicit break; + # otherwise the loop spins forever subscribed to an + # orphaned buffer, holding the WebSocket open. + with Session(engine) as session: + job = session.get(Job, job_id) + if job is None: + await websocket.send_json({"type": "status", "status": "deleted"}) + break + if job.status in terminal: + await websocket.send_json( + {"type": "status", "status": job.status.value} + ) + break + + except WebSocketDisconnect: + pass + finally: + buffer.unsubscribe(queue) diff --git a/src/sweets/web/app.py b/src/sweets/web/app.py new file mode 100644 index 0000000..fe329cd --- /dev/null +++ b/src/sweets/web/app.py @@ -0,0 +1,97 @@ +"""FastAPI application for sweets web UI.""" + +from __future__ import annotations + +import logging +import os +import signal +from contextlib import asynccontextmanager +from pathlib import Path + +from fastapi import FastAPI +from fastapi.middleware.cors import CORSMiddleware +from fastapi.staticfiles import StaticFiles +from sqlmodel import Session, select + +from sweets.web.api import jobs, results, schema, search, websocket +from sweets.web.models import Job, JobStatus +from sweets.web.models.database import create_db_and_tables, engine + +logger = logging.getLogger(__name__) + + +def _sweep_stale_jobs() -> None: + """Mark RUNNING jobs as FAILED on startup. + + If the server crashed or was restarted mid-job the row stays "running" + forever — the subprocess is orphaned and we've lost its stdout pipe, + so we can't reattach or stream logs anyway. Best-effort SIGTERM the + pid if it's still alive (so we don't leak the orphan), then flip the + status to FAILED with a note so the user knows to re-create. + """ + with Session(engine) as session: + stale = session.exec(select(Job).where(Job.status == JobStatus.RUNNING)).all() + for job in stale: + if job.pid: + try: + os.kill(job.pid, signal.SIGTERM) + except (ProcessLookupError, PermissionError): + pass + job.status = JobStatus.FAILED + job.pid = None + note = "[server restart: orphaned subprocess, status unknown]" + job.error_message = ( + f"{job.error_message}\n{note}" if job.error_message else note + ) + session.add(job) + session.commit() + if stale: + logger.warning( + "Marked %d stale RUNNING job(s) as FAILED on startup", len(stale) + ) + + +@asynccontextmanager +async def lifespan(app: FastAPI): + """Initialize database and reconcile orphaned jobs on startup.""" + create_db_and_tables() + _sweep_stale_jobs() + yield + + +app = FastAPI( + title="Sweets", + description="Web UI for InSAR processing workflows", + version="0.1.0", + lifespan=lifespan, +) + +# CORS for local development (Vite dev server on different port) +app.add_middleware( + CORSMiddleware, + allow_origins=["http://localhost:5173", "http://127.0.0.1:5173"], + allow_credentials=True, + allow_methods=["*"], + allow_headers=["*"], +) + + +@app.get("/api/health") +async def health_check(): + """Health check endpoint.""" + return {"status": "ok"} + + +# API routes +app.include_router(jobs.router, prefix="/api/jobs", tags=["jobs"]) +app.include_router(results.router, prefix="/api/jobs", tags=["results"]) +app.include_router(schema.router, prefix="/api/schema", tags=["schema"]) +app.include_router(search.router, prefix="/api/search", tags=["search"]) +app.include_router(websocket.router, prefix="/api/ws", tags=["websocket"]) + + +# Serve static frontend (production) — keep this LAST so the catch-all +# `/` mount doesn't shadow `/api/*` routes registered above. +STATIC_DIR = Path(__file__).parent / "frontend" / "dist" +if STATIC_DIR.exists(): + app.mount("/", StaticFiles(directory=STATIC_DIR, html=True), name="static") diff --git a/src/sweets/web/frontend/.gitignore b/src/sweets/web/frontend/.gitignore new file mode 100644 index 0000000..06e6038 --- /dev/null +++ b/src/sweets/web/frontend/.gitignore @@ -0,0 +1,3 @@ +node_modules +dist +*.tsbuildinfo diff --git a/src/sweets/web/frontend/index.html b/src/sweets/web/frontend/index.html new file mode 100644 index 0000000..5f27b30 --- /dev/null +++ b/src/sweets/web/frontend/index.html @@ -0,0 +1,12 @@ + + + + + + sweets + + +
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"@rjsf/core": "^5.18.0", + "@rjsf/utils": "^5.18.0", + "@rjsf/validator-ajv8": "^5.18.0", + "leaflet": "^1.9.4", + "leaflet-draw": "^1.0.4", + "react": "^18.3.1", + "react-dom": "^18.3.1" + }, + "devDependencies": { + "@types/leaflet": "^1.9.12", + "@types/leaflet-draw": "^1.0.11", + "@types/react": "^18.3.3", + "@types/react-dom": "^18.3.0", + "@vitejs/plugin-react": "^4.3.1", + "typescript": "^5.5.3", + "vite": "^5.4.0" + } +} diff --git a/src/sweets/web/frontend/src/App.tsx b/src/sweets/web/frontend/src/App.tsx new file mode 100644 index 0000000..77e917b --- /dev/null +++ b/src/sweets/web/frontend/src/App.tsx @@ -0,0 +1,73 @@ +import { StateProvider, useAppState } from "./state"; +import type { Tab } from "./state"; +import { MapView } from "./components/MapView"; +import { SearchPanel } from "./components/SearchPanel"; +import { ConfigPanel } from "./components/ConfigPanel"; +import { JobsPanel } from "./components/JobsPanel"; + +const TABS: { id: Tab; label: string }[] = [ + { id: "search", label: "Search" }, + { id: "config", label: "Config" }, + { id: "jobs", label: "Jobs" }, +]; + +function TopNav() { + const { tab, setTab } = useAppState(); + return ( +
    +
    sweets
    + +
    + ); +} + +function Body() { + const { tab } = useAppState(); + if (tab === "config") { + return ( +
    + +
    + ); + } + return ( +
    + +
    + +
    +
    + ); +} + +function Shell() { + return ( +
    + + +
    + ); +} + +export default function App() { + return ( + + + + ); +} diff --git a/src/sweets/web/frontend/src/api.ts b/src/sweets/web/frontend/src/api.ts new file mode 100644 index 0000000..23d50c0 --- /dev/null +++ b/src/sweets/web/frontend/src/api.ts @@ -0,0 +1,53 @@ +import type { + BowserHandoff, + Job, + Manifest, + SearchRequest, + SearchResponse, +} from "./types"; + +async function http(path: string, init?: RequestInit): Promise { + const r = await fetch(path, { + headers: { "Content-Type": "application/json" }, + ...init, + }); + if (!r.ok) { + const body = await r.text(); + throw new Error(`${r.status} ${r.statusText}: ${body}`); + } + if (r.status === 204) return undefined as T; + return r.json(); +} + +export const api = { + schema: () => http("/api/schema"), + ifgSchema: () => http("/api/schema/ifg"), + search: (req: SearchRequest) => + http("/api/search", { + method: "POST", + body: JSON.stringify(req), + }), + listJobs: () => http("/api/jobs/"), + createJob: (name: string, config: Record) => + http("/api/jobs/", { + method: "POST", + body: JSON.stringify({ name, config }), + }), + startJob: (id: number) => + http(`/api/jobs/${id}/start`, { method: "POST" }), + cancelJob: (id: number) => + http(`/api/jobs/${id}/cancel`, { method: "POST" }), + deleteJob: (id: number) => + http(`/api/jobs/${id}`, { method: "DELETE" }), + manifest: (id: number) => http(`/api/jobs/${id}/manifest`), + bowser: (id: number, autostart: boolean) => + http(`/api/jobs/${id}/view?autostart=${autostart}`, { + method: "POST", + }), +}; + +export function jobLogsWs(id: number): WebSocket { + const proto = window.location.protocol === "https:" ? "wss:" : "ws:"; + const host = window.location.host; + return new WebSocket(`${proto}//${host}/api/ws/jobs/${id}/logs`); +} diff --git a/src/sweets/web/frontend/src/components/ConfigPanel.tsx b/src/sweets/web/frontend/src/components/ConfigPanel.tsx new file mode 100644 index 0000000..e89fa8c --- /dev/null +++ b/src/sweets/web/frontend/src/components/ConfigPanel.tsx @@ -0,0 +1,443 @@ +import { useEffect, useMemo, useState } from "react"; +import Form from "@rjsf/core"; +import type { RJSFSchema, UiSchema } from "@rjsf/utils"; +import { getDefaultFormState } from "@rjsf/utils"; +import validator from "@rjsf/validator-ajv8"; +import { api } from "../api"; +import { useAppState } from "../state"; +import type { SearchParams } from "../state"; +import type { SourceKind } from "../types"; + +type WorkflowType = "displacement" | "interferogram"; + +// Fields shown in the default "basic" view for the displacement workflow. +const DISPLACEMENT_BASIC_FIELDS = [ + "work_dir", + "slc_posting", + "pol_type", + "gpu_enabled", + "n_workers", + "threads_per_worker", + "overwrite", +]; +const DISPLACEMENT_ADVANCED_FIELDS = [ + ...DISPLACEMENT_BASIC_FIELDS, + "dolphin", + "tropo", +]; + +// Fields for the interferogram workflow. +const IFG_BASIC_FIELDS = [ + "work_dir", + "slc_posting", + "pol_type", + "overwrite", + "network", + "crossmul", + "stitch", + "unwrap", +]; +const IFG_ADVANCED_FIELDS = [ + ...IFG_BASIC_FIELDS, + "gpu_enabled", + "n_workers", + "threads_per_worker", +]; + +// Within the IFG unwrap sub-schema, hide the advanced SNAPHU tile knobs +// (snaphu_ntiles, snaphu_tile_overlap) from the basic view — they render +// poorly because Union[tuple,Literal] can't be represented as a simple widget. +const IFG_UI_SCHEMA_UNWRAP_ADVANCED: UiSchema = { + snaphu_ntiles: { "ui:widget": "hidden" }, + snaphu_tile_overlap: { "ui:widget": "hidden" }, +}; + +const DISPLACEMENT_UI_SCHEMA: UiSchema = { + work_dir: { "ui:help": "Root output directory. Created if missing." }, + slc_posting: { + "ui:help": + "Geocoded posting (y, x) in meters. Ignored for OPERA/NISAR sources.", + }, + pol_type: { "ui:help": "Only honored for the SAFE / BurstSearch path." }, + n_workers: { "ui:help": "COMPASS geocoding process pool size." }, + threads_per_worker: { "ui:help": "OMP threads per geocoding worker." }, + overwrite: { "ui:help": "Re-run steps even if outputs already exist." }, + dolphin: { "ui:options": { label: false } }, + tropo: { "ui:options": { label: false } }, +}; + +const IFG_UI_SCHEMA: UiSchema = { + work_dir: { "ui:help": "Root output directory. Created if missing." }, + slc_posting: { + "ui:help": + "Geocoded posting (y, x) in meters. Ignored for OPERA/NISAR sources.", + }, + pol_type: { "ui:help": "Only honored for the SAFE / BurstSearch path." }, + overwrite: { "ui:help": "Re-run steps even if outputs already exist." }, + // No label:false here — RJSF renders the legend title above the fieldset + // by default, which is correct. ui:help would appear below the block. + unwrap: IFG_UI_SCHEMA_UNWRAP_ADVANCED, +}; + +function pickFields(schema: RJSFSchema, fields: string[]): RJSFSchema { + const src = schema as RJSFSchema & { + properties?: Record; + required?: string[]; + }; + const props: Record = {}; + for (const k of fields) { + if (src.properties && k in src.properties) { + props[k] = src.properties[k]; + } + } + const required = (src.required ?? []).filter((r: string) => + fields.includes(r), + ); + return { ...schema, properties: props, required }; +} + +// Rewrite Pydantic JSON Schema 2020-12 constructs that RJSF v5 can't render: +// +// 1. prefixItems (fixed-length tuples) → items (RJSF only knows draft-7 style) +// 2. anyOf: [T, {type:"null"}] → T (Optional[X] renders as a +// schema-picker dropdown instead of a plain X widget without this) +function rewriteSchemaInPlace(node: unknown): void { + if (node == null || typeof node !== "object") return; + if (Array.isArray(node)) { + for (const child of node) rewriteSchemaInPlace(child); + return; + } + const obj = node as Record; + + // 1. tuple rewrite + if (Array.isArray(obj.prefixItems) && obj.items == null) { + obj.items = obj.prefixItems; + delete obj.prefixItems; + } + + // 2. $ref + siblings → allOf:[{$ref}] + siblings + // In draft-07, siblings of $ref are ignored; RJSF sees an object with no + // properties and renders the "add new key" button. Wrapping in allOf fixes it. + if (typeof obj.$ref === "string" && Object.keys(obj).length > 1) { + const ref = obj.$ref; + delete obj.$ref; + obj.allOf = [{ $ref: ref }]; + } + + // 3. nullable union collapse: anyOf: [T, null] → T + if (Array.isArray(obj.anyOf)) { + const variants = obj.anyOf as unknown[]; + const nonNull = variants.filter( + (s) => + !( + typeof s === "object" && + s !== null && + (s as Record).type === "null" + ), + ); + if (nonNull.length < variants.length && nonNull.length === 1) { + const inner = nonNull[0] as Record; + for (const [k, v] of Object.entries(inner)) { + if (!(k in obj)) obj[k] = v; + } + delete obj.anyOf; + } + } + + for (const key of Object.keys(obj)) { + rewriteSchemaInPlace(obj[key]); + } +} + +// Build the discriminated-union `Workflow.search` dict from the shared +// Search-tab state. +function buildSearch( + source: SourceKind, + bbox: [number, number, number, number], + sp: SearchParams, + burstIds: string[] | null, +): { search: Record } | { error: string } { + const search: Record = { kind: source, bbox }; + if (!sp.start || !sp.end) { + return { error: "Set Start and End dates on the Search tab." }; + } + search.start = sp.start; + search.end = sp.end; + if (source === "safe") { + if (!sp.track) { + return { error: "Track is required for the S1 burst SAFE source." }; + } + search.track = Number(sp.track); + } else if (source === "opera-cslc") { + if (sp.track) search.track = Number(sp.track); + if (burstIds?.length) search.burst_ids = burstIds; + } else if (source === "nisar-gslc") { + if (sp.track) search.track = Number(sp.track); + if (sp.frame) search.frame = Number(sp.frame); + } + return { search }; +} + +const DEFAULT_JOB_NAME = "sweets-job"; + +function timestamp(): string { + const d = new Date(); + const pad = (n: number) => String(n).padStart(2, "0"); + return ( + `${d.getFullYear()}${pad(d.getMonth() + 1)}${pad(d.getDate())}` + + `-${pad(d.getHours())}${pad(d.getMinutes())}` + ); +} + +function autoWorkDir(jobName: string): string { + return `~/sweets-jobs/${jobName}-${timestamp()}`; +} + +export function ConfigPanel() { + const [workflowType, setWorkflowType] = useState("displacement"); + const [schemas, setSchemas] = useState< + Partial> + >({}); + const [formData, setFormData] = useState>({}); + const [name, setName] = useState(DEFAULT_JOB_NAME); + const [showAdvanced, setShowAdvanced] = useState(false); + const [error, setError] = useState(null); + const [busy, setBusy] = useState(false); + const { bbox, source, searchParams, selectedBurstIds, setTab, setSelectedJobId } = + useAppState(); + + // Compute defaults only for the fields in `fields`, using the full schema + // as rootSchema so $refs resolve correctly. This avoids extra keys + // (bbox, search, orbit_dir…) bleeding into formData and triggering RJSF's + // additionalProperties widget for fields not in the visible schema. + function applyDefaults( + fullSchema: RJSFSchema, + fields: string[], + jobName: string = name, + ): Record { + const visible = pickFields(fullSchema, fields); + const defaults = + (getDefaultFormState( + validator, + visible, + {}, + fullSchema, + ) as Record) ?? {}; + defaults.work_dir = autoWorkDir(jobName); + return defaults; + } + + // Fetch both schemas once on mount. + useEffect(() => { + api + .schema() + .then((s) => { + rewriteSchemaInPlace(s); + const schema = s as RJSFSchema; + setSchemas((prev) => ({ ...prev, displacement: schema })); + if (workflowType === "displacement") + setFormData(applyDefaults(schema, DISPLACEMENT_BASIC_FIELDS)); + }) + .catch((e) => setError(String(e))); + + api + .ifgSchema() + .then((s) => { + rewriteSchemaInPlace(s); + const schema = s as RJSFSchema; + setSchemas((prev) => ({ ...prev, interferogram: schema })); + if (workflowType === "interferogram") + setFormData(applyDefaults(schema, IFG_BASIC_FIELDS)); + }) + .catch((e) => setError(String(e))); + }, []); // eslint-disable-line react-hooks/exhaustive-deps + + // Reset form data (with defaults) when workflow type changes. + function switchWorkflowType(t: WorkflowType) { + setWorkflowType(t); + const s = schemas[t]; + const fields = + t === "interferogram" ? IFG_BASIC_FIELDS : DISPLACEMENT_BASIC_FIELDS; + setFormData(s ? applyDefaults(s, fields) : {}); + setShowAdvanced(false); + } + + const fullSchema = schemas[workflowType] ?? null; + + const basicFields = + workflowType === "interferogram" ? IFG_BASIC_FIELDS : DISPLACEMENT_BASIC_FIELDS; + const advancedFields = + workflowType === "interferogram" + ? IFG_ADVANCED_FIELDS + : DISPLACEMENT_ADVANCED_FIELDS; + const uiSchema = + workflowType === "interferogram" ? IFG_UI_SCHEMA : DISPLACEMENT_UI_SCHEMA; + const advancedLabel = + workflowType === "interferogram" + ? "Show advanced (workers)" + : "Show advanced (dolphin / tropo)"; + + const visibleSchema = useMemo(() => { + if (!fullSchema) return null; + return pickFields(fullSchema, showAdvanced ? advancedFields : basicFields); + }, [fullSchema, showAdvanced, basicFields, advancedFields]); + + async function submit(opts: { start: boolean }) { + if (!bbox) { + setError("No AOI set. Draw one on the Search tab first."); + return; + } + const built = buildSearch(source, bbox, searchParams, selectedBurstIds); + if ("error" in built) { + setError(built.error); + return; + } + setError(null); + setBusy(true); + try { + const config: Record = { + ...formData, + bbox, + ...built, + }; + const job = await api.createJob(name, config); + if (opts.start) { + await api.startJob(job.id); + } + setSelectedJobId(job.id); + setTab("jobs"); + } catch (e) { + setError(String(e)); + } finally { + setBusy(false); + } + } + + if (error && !fullSchema) return
    {error}
    ; + if (!visibleSchema) return

    Loading schema...

    ; + + const sp = searchParams; + const trackLabel = sp.track + ? `T${sp.track}` + : source === "safe" + ? "missing!" + : "any"; + + return ( +
    +
    +

    Configure a new job

    +

    + From the Search tab: source {source}, AOI{" "} + {bbox ? bboxText(bbox) : "not set"}, dates{" "} + + {sp.start || "?"} → {sp.end || "?"} + + , track {trackLabel} + {source === "nisar-gslc" && ( + <> + , frame {sp.frame || "any"} + + )} + . +

    +
    + +
    + + +
    + Workflow +
    + + +
    +
    + + +
    + +
    setFormData(e.formData as Record)} + onSubmit={() => submit({ start: false })} + liveValidate={false} + showErrorList={false} + > +
    + + + +
    + + + {error &&
    {error}
    } +
    + ); +} + +function bboxText(b: [number, number, number, number]): string { + return b.map((n) => n.toFixed(3)).join(", "); +} diff --git a/src/sweets/web/frontend/src/components/JobsPanel.tsx b/src/sweets/web/frontend/src/components/JobsPanel.tsx new file mode 100644 index 0000000..2b66bb5 --- /dev/null +++ b/src/sweets/web/frontend/src/components/JobsPanel.tsx @@ -0,0 +1,315 @@ +import { useEffect, useRef, useState } from "react"; +import { useAppState } from "../state"; +import type { Job, Manifest, BowserHandoff } from "../types"; +import { api, jobLogsWs } from "../api"; + +const STEPS = [ + "download", + "geocode", + "ifg", + "stitch", + "unwrap", +]; + +function fmtBytes(n: number): string { + if (n < 1024) return `${n} B`; + if (n < 1024 ** 2) return `${(n / 1024).toFixed(1)} KB`; + if (n < 1024 ** 3) return `${(n / 1024 ** 2).toFixed(1)} MB`; + return `${(n / 1024 ** 3).toFixed(2)} GB`; +} + +export function JobsPanel() { + const { selectedJobId, setSelectedJobId } = useAppState(); + const [jobs, setJobs] = useState([]); + const [refreshKey, setRefreshKey] = useState(0); + + useEffect(() => { + let alive = true; + const tick = () => + api.listJobs().then((j) => { + if (alive) setJobs(j); + }); + tick(); + const id = setInterval(tick, 3000); + return () => { + alive = false; + clearInterval(id); + }; + }, [refreshKey]); + + const selected = jobs.find((j) => j.id === selectedJobId) ?? null; + + return ( +
    +

    Jobs ({jobs.length})

    +
      + {jobs.map((j) => ( +
    • setSelectedJobId(j.id)} + > +
      {j.name}
      +
      + {j.status}{" "} + #{j.id} · step {j.current_step}/5 +
      +
      • + ))} + {jobs.length === 0 &&
    • No jobs yet.
      • } +
    + + {selected && ( + setRefreshKey((k) => k + 1)} + /> + )} +
    + ); +} + +function JobDetail({ job, onChange }: { job: Job; onChange: () => void }) { + // `job.current_step` from the DB only updates at completion (the executor + // commits the final step in its `finally` block). The WebSocket already + // streams the live step alongside each log line, so we lift that into + // local state and take the max with the DB value — the bar animates in + // real time while a job is running and stays correct after refresh. + const [liveStep, setLiveStep] = useState(0); + useEffect(() => { + setLiveStep(0); + }, [job.id]); + const step = Math.max(job.current_step, liveStep); + return ( + <> +

    Detail · #{job.id}

    +
    + work_dir: {job.work_dir ?? "—"} +
    + +
    + {STEPS.map((label, i) => { + const idx = i + 1; + let cls = ""; + if (step > idx) cls = " done"; + else if (step === idx) + cls = job.status === "running" ? " active" : " done"; + return
    ; + })} +
    + + + setLiveStep((prev) => (s > prev ? s : prev))} + /> + + + + ); +} + +function JobActions({ job, onChange }: { job: Job; onChange: () => void }) { + const [busy, setBusy] = useState(false); + + async function start() { + setBusy(true); + try { + await api.startJob(job.id); + } finally { + setBusy(false); + onChange(); + } + } + async function cancel() { + setBusy(true); + try { + await api.cancelJob(job.id); + } finally { + setBusy(false); + onChange(); + } + } + async function del() { + if (!confirm(`Delete job ${job.name}?`)) return; + setBusy(true); + try { + await api.deleteJob(job.id); + } finally { + setBusy(false); + onChange(); + } + } + + return ( +
    + {job.status === "pending" && ( + + )} + {job.status === "running" && ( + + )} + {job.status !== "running" && ( + + )} +
    + ); +} + +function JobLogs({ + jobId, + onStep, +}: { + jobId: number; + onStep?: (step: number) => void; +}) { + const [lines, setLines] = useState([]); + // The parent re-renders every poll tick (3s) and passes a fresh `onStep` + // closure each time. Stash it in a ref so the WebSocket effect only + // depends on `jobId` — without this the log pane tore down and + // reconnected on every parent re-render. The server sends a terminal + // "status" frame and closes the socket itself when the job finishes, + // so there's no need to react to status changes here. + const onStepRef = useRef(onStep); + onStepRef.current = onStep; + + useEffect(() => { + setLines([]); + const ws = jobLogsWs(jobId); + ws.onmessage = (ev) => { + try { + const m = JSON.parse(ev.data); + if (m.type === "history") { + setLines(m.lines); + if (typeof m.step === "number") onStepRef.current?.(m.step); + } else if (m.type === "log") { + setLines((prev) => [...prev, m.line]); + if (typeof m.step === "number") onStepRef.current?.(m.step); + } + } catch { + // ignore malformed frames + } + }; + return () => ws.close(); + }, [jobId]); + + return ( + <> +

    Logs

    +
    + {lines.length === 0 ? ( + (no output yet) + ) : ( + lines.join("\n") + )} +
    + + ); +} + +function JobManifest({ jobId }: { jobId: number }) { + const [m, setM] = useState(null); + + useEffect(() => { + let alive = true; + const tick = () => + api.manifest(jobId).then((mm) => { + if (alive) setM(mm); + }); + tick(); + const id = setInterval(tick, 5000); + return () => { + alive = false; + clearInterval(id); + }; + }, [jobId]); + + return ( + <> +

    Results

    + {m == null ? ( +

    Loading...

    + ) : !m.exists ? ( +

    work_dir does not exist yet.

    + ) : m.entries.length === 0 ? ( +

    No outputs yet.

    + ) : ( +
    + {m.entries.map((e) => ( +
    + + {e.path} + + {fmtBytes(e.size)} +
    + ))} +
    + )} + + ); +} + +function BowserButton({ jobId, isIfg }: { jobId: number; isIfg: boolean }) { + const [busy, setBusy] = useState(false); + const [result, setResult] = useState(null); + + async function go(autostart: boolean) { + setBusy(true); + try { + const r = await api.bowser(jobId, autostart); + setResult(r); + if (r.url) window.open(r.url, "_blank"); + } finally { + setBusy(false); + } + } + + if (isIfg) { + return ( + <> +

    Results directory

    + {result ? ( + {result.dolphin_dir} + ) : ( + + )} + + ); + } + + return ( + <> +

    View in bowser

    +
    + + +
    + {result && ( +
    + {result.command} + {!result.ran && ( +
    {result.stderr || "not run"}
    + )} +
    + )} + + ); +} diff --git a/src/sweets/web/frontend/src/components/MapView.tsx b/src/sweets/web/frontend/src/components/MapView.tsx new file mode 100644 index 0000000..d843ac7 --- /dev/null +++ b/src/sweets/web/frontend/src/components/MapView.tsx @@ -0,0 +1,197 @@ +import { useEffect, useRef } from "react"; +import L from "leaflet"; +import "leaflet-draw"; +import { useAppState } from "../state"; + +// Fix Leaflet's default marker icons under bundlers — irrelevant here since +// we don't use point markers, but RJSF/Leaflet plugins sometimes choke +// without this. Keeping a single CSS-only basemap from CARTO's free tier. +const BASEMAP = + "https://{s}.basemaps.cartocdn.com/dark_all/{z}/{x}/{y}{r}.png"; +const ATTRIBUTION = + '© OpenStreetMap, © CARTO'; + +const COVERED_STYLE: L.PathOptions = { + color: "#5cd97a", + weight: 1, + fillOpacity: 0.12, + fillColor: "#5cd97a", +}; + +const EXCLUDED_STYLE: L.PathOptions = { + color: "#ff6b6b", + weight: 1, + fillOpacity: 0.08, + fillColor: "#ff6b6b", + dashArray: "3 3", +}; + +const AOI_STYLE: L.PathOptions = { + color: "#ffb454", + weight: 2, + fill: false, + dashArray: "6 4", +}; + +export function MapView() { + const containerRef = useRef(null); + const mapRef = useRef(null); + const aoiLayerRef = useRef(null); + const searchLayerRef = useRef(null); + const drawerRef = useRef(null); + + const { bbox, setBbox, searchResults } = useAppState(); + + // Initialize the map once. + useEffect(() => { + if (!containerRef.current || mapRef.current) return; + const map = L.map(containerRef.current, { + center: [34.05, -118.25], + zoom: 5, + zoomControl: true, + }); + L.tileLayer(BASEMAP, { attribution: ATTRIBUTION, maxZoom: 18 }).addTo(map); + + const searchLayer = L.geoJSON(undefined, { + style: (feat) => { + const p = (feat?.properties ?? {}) as { in_coverage?: boolean }; + return p.in_coverage === false ? EXCLUDED_STYLE : COVERED_STYLE; + }, + onEachFeature: (feat, layer) => { + const p = (feat.properties ?? {}) as Record; + const lines = [ + `${p.name ?? "?"}`, + p.date ? `date: ${String(p.date).slice(0, 10)}` : null, + p.track != null ? `track: ${p.track}` : null, + p.frame != null ? `frame: ${p.frame}` : null, + p.burst_id ? `burst: ${p.burst_id}` : null, + p.in_coverage === false + ? "excluded by missing-data filter" + : null, + ].filter(Boolean); + layer.bindPopup(lines.join("
    ")); + }, + }).addTo(map); + + // Leaflet.draw via dynamic any-cast — the typing is patchy under v1+v4 + // mixes and we only use rectangle.enable() / disable(). + // eslint-disable-next-line @typescript-eslint/no-explicit-any + const Ldraw = (L as any).Draw; + if (Ldraw?.Rectangle) { + drawerRef.current = new Ldraw.Rectangle(map, { + shapeOptions: AOI_STYLE, + showArea: false, + }); + map.on((L as unknown as { Draw: { Event: { CREATED: string } } }).Draw.Event.CREATED, (e: unknown) => { + const ev = e as { layer: L.Rectangle }; + if (aoiLayerRef.current) { + map.removeLayer(aoiLayerRef.current); + } + aoiLayerRef.current = ev.layer; + ev.layer.setStyle(AOI_STYLE); + ev.layer.addTo(map); + const b = ev.layer.getBounds(); + setBbox([ + b.getWest(), + b.getSouth(), + b.getEast(), + b.getNorth(), + ] as [number, number, number, number]); + }); + } + + mapRef.current = map; + searchLayerRef.current = searchLayer; + // Initialize the Leaflet map exactly once. `setBbox` would otherwise + // pull this effect into the context-rebuild churn loop — every search + // result or tab switch would rebuild the context's memoized value, + // give us a new setBbox reference, and re-fire this effect (the guard + // above short-circuits but it's wasted work). + // eslint-disable-next-line react-hooks/exhaustive-deps + }, []); + + // Sync AOI rectangle from state (e.g. typed-in bbox). The AOI layer is + // always kept on top of the search-result overlay so a drawn box doesn't + // get buried under returned granule polygons. + useEffect(() => { + const map = mapRef.current; + if (!map) return; + if (!bbox) { + if (aoiLayerRef.current) { + map.removeLayer(aoiLayerRef.current); + aoiLayerRef.current = null; + } + return; + } + const [w, s, e, n] = bbox; + if (aoiLayerRef.current) { + aoiLayerRef.current.setBounds([ + [s, w], + [n, e], + ]); + } else { + aoiLayerRef.current = L.rectangle( + [ + [s, w], + [n, e], + ], + AOI_STYLE, + ).addTo(map); + } + aoiLayerRef.current.bringToFront(); + }, [bbox]); + + // Replace the search-results overlay whenever results change. fitBounds is + // expanded to include the AOI if it's set, so the user always sees their + // requested area along with the returned granules. + useEffect(() => { + const layer = searchLayerRef.current; + const map = mapRef.current; + if (!layer || !map) return; + layer.clearLayers(); + if (searchResults && searchResults.features.length > 0) { + layer.addData(searchResults as unknown as GeoJSON.FeatureCollection); + try { + let bounds = layer.getBounds(); + if (aoiLayerRef.current) { + bounds = bounds.extend(aoiLayerRef.current.getBounds()); + } + map.fitBounds(bounds, { padding: [40, 40] }); + } catch { + // empty bounds — ignore + } + } + // Keep AOI visible on top of any newly-added burst polygons. + if (aoiLayerRef.current) aoiLayerRef.current.bringToFront(); + }, [searchResults]); + + function startDraw() { + // eslint-disable-next-line @typescript-eslint/no-explicit-any + (drawerRef.current as any)?.enable?.(); + } + + return ( + <> +
    +
    + + +
    + + ); +} diff --git a/src/sweets/web/frontend/src/components/SearchPanel.tsx b/src/sweets/web/frontend/src/components/SearchPanel.tsx new file mode 100644 index 0000000..ef75fec --- /dev/null +++ b/src/sweets/web/frontend/src/components/SearchPanel.tsx @@ -0,0 +1,465 @@ +import { useMemo, useState } from "react"; +import { useAppState } from "../state"; +import type { + SearchFeature, + SearchRequest, + SearchResponse, + SourceKind, + TrackSummary, +} from "../types"; +import { api } from "../api"; + +const SOURCES: { id: SourceKind; label: string }[] = [ + { id: "opera-cslc", label: "OPERA CSLC (S1)" }, + { id: "safe", label: "S1 burst SAFE" }, + { id: "nisar-gslc", label: "NISAR GSLC" }, +]; + +function dirLabel(d: TrackSummary["flight_direction"]): string { + if (d === "ASCENDING") return "ASC"; + if (d === "DESCENDING") return "DESC"; + return "—"; +} + +export function SearchPanel() { + const { + source, + setSource, + bbox, + setBbox, + searchParams, + setSearchParams, + setSearchResults, + searchResults, + setSelectedBurstIds, + } = useAppState(); + const { start, end, track, frame } = searchParams; + const setField = (k: keyof typeof searchParams, v: string) => + setSearchParams((p) => ({ ...p, [k]: v })); + + const [busy, setBusy] = useState(false); + const [error, setError] = useState(null); + const [showGranules, setShowGranules] = useState(false); + + function setBboxField(idx: 0 | 1 | 2 | 3, raw: string) { + const next = (bbox ?? [-118.5, 34.0, -118.0, 34.3]).slice() as [ + number, + number, + number, + number, + ]; + const n = parseFloat(raw); + if (Number.isFinite(n)) next[idx] = n; + setBbox(next); + } + + async function runSearch(overrideTrack?: number | null) { + if (!bbox) { + setError("Draw an AOI on the map (or type a bbox)."); + return; + } + setError(null); + setBusy(true); + const trackVal = + overrideTrack !== undefined + ? overrideTrack + : track + ? Number(track) + : null; + const req: SearchRequest = { + source, + bbox, + start, + end, + track: trackVal, + frame: frame ? Number(frame) : null, + }; + try { + const r = await api.search(req); + setSearchResults(r); + setSelectedBurstIds(null); // reset burst filter on every new search + // Persist the override so the Config tab picks it up too. + if (overrideTrack !== undefined) { + setField("track", overrideTrack == null ? "" : String(overrideTrack)); + } + } catch (e) { + setError(String(e)); + } finally { + setBusy(false); + } + } + + return ( +
    +

    Source

    + + +

    AOI

    +

    Draw on map, or type a bbox below.

    +
    + + +
    +
    + + +
    + +

    Dates

    +
    + + +
    + +

    Filters

    +
    + + {source === "nisar-gslc" && ( + + )} +
    + +
    + + +
    + + {error &&
    {error}
    } + {searchResults && ( + runSearch(t)} + showGranules={showGranules} + setShowGranules={setShowGranules} + /> + )} +
    + ); +} + +function ResultsPanel({ + results, + activeTrack, + onPickTrack, + showGranules, + setShowGranules, +}: { + results: SearchResponse; + activeTrack: number | null; + onPickTrack: (t: number | null) => void; + showGranules: boolean; + setShowGranules: (b: boolean) => void; +}) { + const { selectedBurstIds, setSelectedBurstIds } = useAppState(); + const cov = results.coverage; + + // Unique burst IDs present in the current results, with per-burst count. + const burstCounts = useMemo(() => { + const map = new Map(); + for (const f of results.features) { + const b = f.properties.burst_id; + if (b) map.set(b, (map.get(b) ?? 0) + 1); + } + return [...map.entries()].sort((a, b) => a[0].localeCompare(b[0])); + }, [results.features]); + + const allBurstIds = burstCounts.map(([id]) => id); + // null means all selected; otherwise check membership in the explicit list. + const isChecked = (id: string) => + selectedBurstIds === null || selectedBurstIds.includes(id); + + function toggleBurst(id: string) { + const newChecked = allBurstIds.filter((b) => + b === id ? !isChecked(b) : isChecked(b), + ); + // If all are selected again, go back to null (no filter). + setSelectedBurstIds( + newChecked.length === allBurstIds.length ? null : newChecked, + ); + } + return ( +
    +
    + {results.count} granule{results.count === 1 ? "" : "s"} returned. +
    + {cov?.num_bursts != null && ( +
    + Missing-data filter: {cov.num_bursts} burst + {cov.num_bursts === 1 ? "" : "s"} × {cov.num_dates} date + {cov.num_dates === 1 ? "" : "s"} ( + + {cov.num_features_in_coverage} kept + + {cov.num_features_excluded ? ( + <> + ,{" "} + + {cov.num_features_excluded} excluded + + + ) : null} + ). +
    + )} + + {results.tracks.length > 0 && ( + <> +

    Tracks

    +

    + Sweets processes one track per job. Pick one to narrow the search. +

    +
      + {results.tracks.map((t) => { + const isActive = t.track === activeTrack; + return ( +
    • onPickTrack(isActive ? null : t.track)} + title={ + isActive ? "Click to clear filter" : "Filter to this track" + } + > + T{t.track} + + {dirLabel(t.flight_direction)} + + {t.count} +
      • + ); + })} +
    + + )} + + {burstCounts.length > 1 && ( + <> +

    Bursts

    +

    + Select which bursts to include in the job. + {selectedBurstIds !== null && ( + <> + {" "} + + + )} +

    +
      + {burstCounts.map(([id, count]) => ( +
    • toggleBurst(id)} + title={isChecked(id) ? "Click to exclude" : "Click to include"} + > + toggleBurst(id)} + onClick={(e) => e.stopPropagation()} + /> + {id} + {count} +
      • + ))} +
    + + )} + +

    + Granules{" "} + +

    + +
    + + +
    + + {showGranules && ( +
    + {results.features.map((f) => ( +
    + {f.properties.name} + + {(f.properties.date || "").slice(0, 10)} · T + {f.properties.track ?? "?"}{" "} + {f.properties.flight_direction === "ASCENDING" + ? "ASC" + : f.properties.flight_direction === "DESCENDING" + ? "DESC" + : ""} + +
    + ))} +
    + )} +
    + ); +} + +function featuresToCsv(features: SearchFeature[]): string { + const header = [ + "name", + "date", + "track", + "flight_direction", + "burst_id", + "frame", + "in_coverage", + "url", + ]; + const rows = features.map((f) => { + const p = f.properties; + return [ + p.name, + (p.date || "").slice(0, 10), + p.track ?? "", + p.flight_direction ?? "", + p.burst_id ?? "", + p.frame ?? "", + p.in_coverage, + p.url ?? "", + ] + .map(csvCell) + .join(","); + }); + return [header.join(","), ...rows].join("\n") + "\n"; +} + +function csvCell(v: unknown): string { + const s = String(v ?? ""); + if (/[",\n]/.test(s)) return `"${s.replace(/"/g, '""')}"`; + return s; +} + +function featuresToUrlList(features: SearchFeature[]): string { + return ( + features + .map((f) => f.properties.url) + .filter((u): u is string => !!u) + .join("\n") + "\n" + ); +} + +function downloadFile(name: string, content: string) { + const blob = new Blob([content], { type: "text/plain;charset=utf-8" }); + const url = URL.createObjectURL(blob); + const a = document.createElement("a"); + a.href = url; + a.download = name; + a.click(); + URL.revokeObjectURL(url); +} diff --git a/src/sweets/web/frontend/src/main.tsx b/src/sweets/web/frontend/src/main.tsx new file mode 100644 index 0000000..819d564 --- /dev/null +++ b/src/sweets/web/frontend/src/main.tsx @@ -0,0 +1,12 @@ +import React from "react"; +import ReactDOM from "react-dom/client"; +import App from "./App"; +import "leaflet/dist/leaflet.css"; +import "leaflet-draw/dist/leaflet.draw.css"; +import "./style.css"; + +ReactDOM.createRoot(document.getElementById("root")!).render( + + + , +); diff --git a/src/sweets/web/frontend/src/state.tsx b/src/sweets/web/frontend/src/state.tsx new file mode 100644 index 0000000..c69aed8 --- /dev/null +++ b/src/sweets/web/frontend/src/state.tsx @@ -0,0 +1,91 @@ +import { createContext, useContext, useMemo, useState } from "react"; +import type { ReactNode } from "react"; +import type { SearchResponse, SourceKind } from "./types"; + +export type Tab = "search" | "config" | "jobs"; + +type Bbox = [number, number, number, number]; + +// Shared search params. These live above SearchPanel so the Config tab can +// fold them into the discriminated-union `Workflow.search` payload — +// otherwise a job created from the UI would be missing start/end/track and +// fail at Workflow validation in the executor subprocess. +export interface SearchParams { + start: string; + end: string; + track: string; + frame: string; +} + +// null means "all bursts" (don't restrict); a string[] is an explicit allow-list +// passed to search.burst_ids in the job config. +export type SelectedBurstIds = string[] | null; + +const DEFAULT_SEARCH: SearchParams = { + start: "2024-01-01", + end: "2024-12-31", + track: "", + frame: "", +}; + +interface AppState { + tab: Tab; + setTab: (t: Tab) => void; + bbox: Bbox | null; + setBbox: (b: Bbox | null) => void; + source: SourceKind; + setSource: (s: SourceKind) => void; + searchParams: SearchParams; + setSearchParams: ( + updater: SearchParams | ((prev: SearchParams) => SearchParams), + ) => void; + searchResults: SearchResponse | null; + setSearchResults: (r: SearchResponse | null) => void; + selectedBurstIds: SelectedBurstIds; + setSelectedBurstIds: (ids: SelectedBurstIds) => void; + selectedJobId: number | null; + setSelectedJobId: (n: number | null) => void; +} + +const Ctx = createContext(null); + +export function StateProvider({ children }: { children: ReactNode }) { + const [tab, setTab] = useState("search"); + const [bbox, setBbox] = useState(null); + const [source, setSource] = useState("opera-cslc"); + const [searchParams, setSearchParams] = useState(DEFAULT_SEARCH); + const [searchResults, setSearchResults] = useState( + null, + ); + const [selectedBurstIds, setSelectedBurstIds] = + useState(null); + const [selectedJobId, setSelectedJobId] = useState(null); + + const value = useMemo( + () => ({ + tab, + setTab, + bbox, + setBbox, + source, + setSource, + searchParams, + setSearchParams, + searchResults, + setSearchResults, + selectedBurstIds, + setSelectedBurstIds, + selectedJobId, + setSelectedJobId, + }), + [tab, bbox, source, searchParams, searchResults, selectedBurstIds, selectedJobId], + ); + + return {children}; +} + +export function useAppState(): AppState { + const v = useContext(Ctx); + if (!v) throw new Error("useAppState outside StateProvider"); + return v; +} diff --git a/src/sweets/web/frontend/src/style.css b/src/sweets/web/frontend/src/style.css new file mode 100644 index 0000000..ffe9f7c --- /dev/null +++ b/src/sweets/web/frontend/src/style.css @@ -0,0 +1,616 @@ +/* Minimal bowser-inspired layout: dark sidebar, full-bleed map. */ +:root { + --bg: #1a1a1a; + --panel: #242424; + --panel-2: #2e2e2e; + --border: #3a3a3a; + --text: #e8e8e8; + --muted: #9a9a9a; + --accent: #4ea1ff; + --accent-2: #2d7dd2; + --ok: #5cd97a; + --warn: #ffb454; + --err: #ff6b6b; + --mono: ui-monospace, SFMono-Regular, "SF Mono", Menlo, monospace; +} + +* { + box-sizing: border-box; +} + +html, +body, +#root { + height: 100%; + margin: 0; + background: var(--bg); + color: var(--text); + font-family: + system-ui, + -apple-system, + "Segoe UI", + sans-serif; + font-size: 14px; +} + +.app { + display: grid; + grid-template-rows: 48px 1fr; + height: 100vh; +} + +.topbar { + display: flex; + align-items: stretch; + background: var(--panel); + border-bottom: 1px solid var(--border); +} + +.topbar .title { + font-weight: 600; + font-size: 15px; + padding: 0 16px; + display: flex; + align-items: center; + border-right: 1px solid var(--border); + letter-spacing: 0.5px; +} + +.topbar-tabs { + display: flex; +} + +.topbar-tabs .tab { + padding: 0 20px; + display: flex; + align-items: center; + cursor: pointer; + color: var(--muted); + font-size: 12px; + text-transform: uppercase; + letter-spacing: 0.5px; + border-bottom: 2px solid transparent; +} + +.topbar-tabs .tab.active { + color: var(--text); + border-bottom-color: var(--accent); + background: var(--panel-2); +} + +.content { + overflow: hidden; + min-height: 0; +} + +.content.split { + display: grid; + grid-template-columns: 380px 1fr; + height: 100%; +} + +.content.full { + overflow-y: auto; + padding: 24px 32px; +} + +.content.full > * { + max-width: 920px; + margin: 0 auto; +} + +.sidebar { + background: var(--panel); + border-right: 1px solid var(--border); + overflow-y: auto; + display: flex; + flex-direction: column; +} + +.panel { + padding: 12px 16px; + flex: 1; + overflow-y: auto; +} + +.panel h2 { + font-size: 13px; + margin: 12px 0 6px; + color: var(--muted); + text-transform: uppercase; + letter-spacing: 0.5px; +} + +label { + display: block; + font-size: 12px; + color: var(--muted); + margin: 8px 0 2px; +} + +input, +select, +textarea { + width: 100%; + background: var(--bg); + color: var(--text); + border: 1px solid var(--border); + border-radius: 3px; + padding: 6px 8px; + font-family: inherit; + font-size: 13px; +} + +button { + background: var(--accent-2); + color: white; + border: none; + border-radius: 3px; + padding: 6px 12px; + cursor: pointer; + font-size: 13px; + font-weight: 500; +} + +button:hover { + background: var(--accent); +} + +button:disabled { + background: var(--border); + color: var(--muted); + cursor: not-allowed; +} + +button.secondary { + background: var(--panel-2); + color: var(--text); + border: 1px solid var(--border); +} + +button.danger { + background: #5a2323; +} + +.row { + display: flex; + gap: 8px; + margin: 8px 0; +} + +.row > * { + flex: 1; +} + +.map { + position: relative; + height: 100%; +} + +.leaflet-container { + height: 100%; + width: 100%; + background: #0e1216; +} + +.track-list { + list-style: none; + padding: 0; + margin: 4px 0 0; + display: grid; + grid-template-columns: repeat(auto-fill, minmax(110px, 1fr)); + gap: 4px; +} + +.track-item { + display: flex; + align-items: center; + gap: 6px; + padding: 4px 8px; + background: var(--panel-2); + border: 1px solid var(--border); + border-radius: 3px; + cursor: pointer; + font-size: 12px; +} + +.track-item:hover { + border-color: var(--accent); +} + +.track-item.selected { + border-color: var(--accent); + background: #1f3654; +} + +.track-num { + font-family: var(--mono); + font-weight: 600; + color: var(--text); +} + +.track-dir { + font-size: 10px; + font-weight: 600; + padding: 1px 4px; + border-radius: 2px; + background: var(--panel); + color: var(--muted); +} + +.track-dir.ASCENDING { + color: #9be7ff; +} + +.track-dir.DESCENDING { + color: #ffc78a; +} + +.track-count { + margin-left: auto; + font-family: var(--mono); + color: var(--muted); + font-size: 11px; +} + +.burst-list { + list-style: none; + padding: 0; + margin: 4px 0 0; + display: flex; + flex-direction: column; + gap: 3px; +} + +.burst-item { + display: flex; + align-items: center; + gap: 8px; + padding: 4px 8px; + background: var(--panel-2); + border: 1px solid var(--border); + border-radius: 3px; + cursor: pointer; + font-size: 12px; +} + +.burst-item:hover { + border-color: var(--accent); +} + +.burst-item.selected { + border-color: var(--accent); + background: #1f3654; +} + +.burst-item input[type="checkbox"] { + width: auto; + margin: 0; + cursor: pointer; +} + +.burst-id { + font-family: var(--mono); + color: var(--text); + flex: 1; +} + +.burst-count { + font-family: var(--mono); + color: var(--muted); + font-size: 11px; +} + +.granule-list { + max-height: 320px; + overflow-y: auto; + border: 1px solid var(--border); + border-radius: 3px; + margin-top: 6px; +} + +.granule-item { + display: flex; + flex-direction: column; + padding: 4px 8px; + border-bottom: 1px solid var(--border); + font-size: 11px; +} + +.granule-item:last-child { + border-bottom: none; +} + +.granule-item.excluded .granule-name { + text-decoration: line-through; + color: var(--muted); +} + +.granule-name { + font-family: var(--mono); + word-break: break-all; +} + +.granule-meta { + color: var(--muted); + font-size: 10px; + font-family: var(--mono); +} + +.job-list { + list-style: none; + padding: 0; + margin: 0; +} + +.job-item { + padding: 8px 12px; + border-bottom: 1px solid var(--border); + cursor: pointer; +} + +.job-item:hover { + background: var(--panel-2); +} + +.job-item.selected { + background: var(--panel-2); + border-left: 3px solid var(--accent); +} + +.job-name { + font-weight: 500; + margin-bottom: 2px; +} + +.job-meta { + font-size: 11px; + color: var(--muted); + font-family: var(--mono); +} + +.status { + display: inline-block; + padding: 1px 6px; + border-radius: 2px; + font-size: 10px; + text-transform: uppercase; + font-family: var(--mono); +} + +.status.pending { + background: var(--panel-2); + color: var(--muted); +} + +.status.running { + background: #2d4a6e; + color: var(--accent); +} + +.status.completed { + background: #2d5a3a; + color: var(--ok); +} + +.status.failed { + background: #5a2d2d; + color: var(--err); +} + +.status.cancelled { + background: var(--panel-2); + color: var(--warn); +} + +.log-window { + background: #0d0d0d; + border: 1px solid var(--border); + font-family: var(--mono); + font-size: 11px; + color: #d4d4d4; + padding: 8px; + height: 280px; + overflow-y: scroll; + white-space: pre-wrap; + word-break: break-all; +} + +.step-bar { + display: flex; + gap: 4px; + margin: 8px 0; +} + +.step { + flex: 1; + height: 4px; + background: var(--border); + border-radius: 2px; +} + +.step.done { + background: var(--accent); +} + +.step.active { + background: var(--accent); + animation: pulse 1.5s infinite; +} + +@keyframes pulse { + 0%, + 100% { + opacity: 1; + } + 50% { + opacity: 0.4; + } +} + +.manifest { + font-family: var(--mono); + font-size: 11px; +} + +.manifest .file { + display: flex; + justify-content: space-between; + padding: 2px 0; + border-bottom: 1px dashed var(--border); +} + +.manifest .file .path { + color: var(--text); + word-break: break-all; +} + +.manifest .file .size { + color: var(--muted); + white-space: nowrap; + margin-left: 8px; +} + +.error { + color: var(--err); + font-size: 12px; + margin: 6px 0; +} + +.muted { + color: var(--muted); + font-size: 12px; +} + +.config-page { + padding-bottom: 64px; +} + +.config-header { + border-bottom: 1px solid var(--border); + padding-bottom: 12px; + margin-bottom: 16px; +} + +.config-grid { + display: flex; + gap: 24px; + align-items: flex-end; + margin-bottom: 24px; +} + +.config-name { + flex: 1; + max-width: 320px; +} + +.config-workflow-type { + display: flex; + flex-direction: column; + gap: 4px; +} + +.config-workflow-label { + font-size: 12px; + color: var(--muted); + text-transform: uppercase; + letter-spacing: 0.5px; +} + +.workflow-toggle { + display: flex; + gap: 0; + border: 1px solid var(--border); + border-radius: 4px; + overflow: hidden; +} + +.workflow-toggle button { + flex: 1; + padding: 5px 14px; + border: none; + border-radius: 0; + font-size: 13px; + cursor: pointer; + background: var(--surface); + color: var(--muted); + transition: background 0.1s, color 0.1s; +} + +.workflow-toggle button:first-child { + border-right: 1px solid var(--border); +} + +.workflow-toggle button.active { + background: var(--accent); + color: #fff; +} + +.workflow-toggle button:hover:not(.active) { + background: var(--border); + color: var(--text); +} + +.config-toggle { + display: flex; + align-items: center; + gap: 6px; + cursor: pointer; + color: var(--text); + font-size: 13px; +} + +.config-toggle input { + width: auto; +} + +/* RJSF compact dark overrides */ +.rjsf .form-group { + margin-bottom: 8px; +} +.rjsf legend { + font-size: 12px; + color: var(--muted); + text-transform: uppercase; + letter-spacing: 0.5px; + border-bottom: 1px solid var(--border); + padding-bottom: 2px; + margin: 12px 0 6px; +} +.rjsf .field-description { + color: var(--muted); + font-size: 11px; + margin-bottom: 2px; +} +.rjsf .control-label { + font-size: 12px; + color: var(--muted); +} +.rjsf .array-item { + border: 1px solid var(--border); + padding: 6px; + border-radius: 3px; + margin-bottom: 4px; +} +.rjsf .panel { + padding: 0; +} + +.rjsf .field-object > fieldset { + border: 1px solid var(--border); + border-radius: 4px; + padding: 12px 16px; + margin: 8px 0; + background: var(--panel-2); +} + +/* Two-up layout for top-level scalar fields when there's room. */ +.content.full .rjsf > .form-group > .field-object > fieldset > .form-group { + width: 100%; +} + +.rjsf .row-fluid { + display: grid; + grid-template-columns: repeat(auto-fit, minmax(220px, 1fr)); + gap: 16px; +} diff --git a/src/sweets/web/frontend/src/types.ts b/src/sweets/web/frontend/src/types.ts new file mode 100644 index 0000000..105c1af --- /dev/null +++ b/src/sweets/web/frontend/src/types.ts @@ -0,0 +1,93 @@ +export type SourceKind = "safe" | "opera-cslc" | "nisar-gslc"; + +export interface SearchRequest { + source: SourceKind; + bbox: [number, number, number, number]; + start: string; + end: string; + track?: number | null; + frame?: number | null; +} + +export interface SearchFeatureProps { + name: string; + date: string; + track?: number | null; + burst_id?: string | null; + frame?: number | null; + url?: string | null; + flight_direction?: "ASCENDING" | "DESCENDING" | null; + in_coverage: boolean; +} + +export interface TrackSummary { + track: number; + flight_direction?: "ASCENDING" | "DESCENDING" | null; + count: number; +} + +export interface SearchFeature { + type: "Feature"; + properties: SearchFeatureProps; + geometry: GeoJSON.Polygon | GeoJSON.MultiPolygon; +} + +export interface CoverageSummary { + num_bursts?: number; + num_dates?: number; + num_features_in_coverage?: number; + num_features_excluded?: number; + num_options?: number; +} + +export interface SearchResponse { + type: "FeatureCollection"; + features: SearchFeature[]; + count: number; + source: SourceKind; + coverage: CoverageSummary; + tracks: TrackSummary[]; +} + +export type JobStatus = + | "pending" + | "running" + | "completed" + | "failed" + | "cancelled"; + +export interface Job { + id: number; + name: string; + status: JobStatus; + current_step: number; + config: Record; + work_dir: string | null; + error_message: string | null; + created_at: string; + started_at: string | null; + completed_at: string | null; +} + +export interface ManifestEntry { + path: string; + size: number; + kind: string; +} + +export interface Manifest { + job_id: number; + work_dir: string | null; + exists: boolean; + entries: ManifestEntry[]; +} + +export interface BowserHandoff { + job_id: number; + dolphin_dir: string; + command: string; + url: string | null; + ran: boolean; + stdout: string; + stderr: string; +} diff --git a/src/sweets/web/frontend/tsconfig.json b/src/sweets/web/frontend/tsconfig.json new file mode 100644 index 0000000..cca1415 --- /dev/null +++ b/src/sweets/web/frontend/tsconfig.json @@ -0,0 +1,22 @@ +{ + "compilerOptions": { + "target": "ES2022", + "lib": ["ES2022", "DOM", "DOM.Iterable"], + "module": "ESNext", + "moduleResolution": "bundler", + "jsx": "react-jsx", + "strict": true, + "noUnusedLocals": true, + "noUnusedParameters": true, + "noFallthroughCasesInSwitch": true, + "skipLibCheck": true, + "esModuleInterop": true, + "allowSyntheticDefaultImports": true, + "isolatedModules": true, + "resolveJsonModule": true, + "useDefineForClassFields": true, + "allowImportingTsExtensions": false, + "noEmit": true + }, + "include": ["src"] +} diff --git a/src/sweets/web/frontend/vite.config.ts b/src/sweets/web/frontend/vite.config.ts new file mode 100644 index 0000000..0274538 --- /dev/null +++ b/src/sweets/web/frontend/vite.config.ts @@ -0,0 +1,20 @@ +import { defineConfig } from "vite"; +import react from "@vitejs/plugin-react"; + +export default defineConfig({ + plugins: [react()], + server: { + port: 5173, + proxy: { + "/api": { + target: "http://localhost:8000", + changeOrigin: true, + ws: true, + }, + }, + }, + build: { + outDir: "dist", + emptyOutDir: true, + }, +}); diff --git a/src/sweets/web/models/__init__.py b/src/sweets/web/models/__init__.py new file mode 100644 index 0000000..ef30178 --- /dev/null +++ b/src/sweets/web/models/__init__.py @@ -0,0 +1,7 @@ +"""Database models for sweets web UI.""" + +from __future__ import annotations + +from sweets.web.models.job import Job, JobCreate, JobRead, JobStatus, JobUpdate + +__all__ = ["Job", "JobCreate", "JobRead", "JobUpdate", "JobStatus"] diff --git a/src/sweets/web/models/database.py b/src/sweets/web/models/database.py new file mode 100644 index 0000000..70045da --- /dev/null +++ b/src/sweets/web/models/database.py @@ -0,0 +1,29 @@ +"""Database setup and session management.""" + +from __future__ import annotations + +from pathlib import Path + +from sqlmodel import Session, SQLModel, create_engine + +# Default to ~/.sweets/sweets.db +DEFAULT_DB_PATH = Path.home() / ".sweets" / "sweets.db" + + +def _database_url() -> str: + DEFAULT_DB_PATH.parent.mkdir(parents=True, exist_ok=True) + return f"sqlite:///{DEFAULT_DB_PATH}" + + +engine = create_engine(_database_url(), echo=False) + + +def create_db_and_tables(): + """Create all database tables.""" + SQLModel.metadata.create_all(engine) + + +def get_session(): + """Yield a database session.""" + with Session(engine) as session: + yield session diff --git a/src/sweets/web/models/job.py b/src/sweets/web/models/job.py new file mode 100644 index 0000000..84b7de3 --- /dev/null +++ b/src/sweets/web/models/job.py @@ -0,0 +1,77 @@ +"""Job model for tracking workflow executions.""" + +from __future__ import annotations + +from datetime import datetime +from enum import Enum +from typing import Any + +from pydantic import field_validator +from sqlmodel import Column, Field, SQLModel +from sqlalchemy import JSON + + +class JobStatus(str, Enum): + """Status of a workflow job.""" + + PENDING = "pending" + RUNNING = "running" + COMPLETED = "completed" + FAILED = "failed" + CANCELLED = "cancelled" + + +class JobBase(SQLModel): + """Base job fields shared between create/update/read.""" + + name: str = Field(index=True) + config: dict[str, Any] = Field(default_factory=dict, sa_column=Column(JSON)) + work_dir: str | None = None + + +class Job(JobBase, table=True): # type: ignore[call-arg] + """Job database model.""" + + id: int | None = Field(default=None, primary_key=True) + status: JobStatus = Field(default=JobStatus.PENDING) + current_step: int = Field(default=0) + error_message: str | None = None + created_at: datetime = Field(default_factory=datetime.utcnow) + started_at: datetime | None = None + completed_at: datetime | None = None + pid: int | None = None # Process ID for running jobs + + +class JobCreate(JobBase): + """Schema for creating a new job.""" + + @field_validator("config", mode="before") + @classmethod + def validate_config(cls, v: dict[str, Any]) -> dict[str, Any]: + # Basic validation - more thorough validation happens in Workflow + assert "bbox" in v or "wkt" in v, "Must specify bbox or wkt" + return v + + +class JobUpdate(SQLModel): + """Schema for updating a job. + + User-facing fields only. ``pid`` and ``status`` are internal — they're + set by the executor / cancel endpoint and shouldn't be writable via + PATCH (a client setting ``pid=12345`` could mis-target a SIGTERM). + """ + + name: str | None = None + error_message: str | None = None + + +class JobRead(JobBase): + """Schema for reading a job (response model).""" + + id: int + status: JobStatus + current_step: int + error_message: str | None + created_at: datetime + started_at: datetime | None + completed_at: datetime | None diff --git a/src/sweets/web/services/__init__.py b/src/sweets/web/services/__init__.py new file mode 100644 index 0000000..ae747da --- /dev/null +++ b/src/sweets/web/services/__init__.py @@ -0,0 +1,3 @@ +"""Services for sweets web UI.""" + +from __future__ import annotations diff --git a/src/sweets/web/services/executor.py b/src/sweets/web/services/executor.py new file mode 100644 index 0000000..94cd610 --- /dev/null +++ b/src/sweets/web/services/executor.py @@ -0,0 +1,145 @@ +"""Job execution service with log streaming.""" + +from __future__ import annotations + +import subprocess +import sys +import threading +from datetime import datetime, timezone +from pathlib import Path +from tempfile import NamedTemporaryFile + +import yaml +from sqlmodel import Session + +from sweets.web.models import Job, JobStatus +from sweets.web.models.database import engine +from sweets.web.services.log_manager import log_manager + + +def _utcnow() -> datetime: + """Timezone-aware UTC now (``datetime.utcnow`` is deprecated in 3.12+).""" + return datetime.now(timezone.utc) + + +def _stream_output(proc: subprocess.Popen, job_id: int): + """Read subprocess output line by line and stream to log manager.""" + assert proc.stdout is not None + for line in iter(proc.stdout.readline, ""): + if not line: + break + line = line.rstrip("\n\r") + log_manager.append_log(job_id, line) + proc.stdout.close() + + +def run_workflow_sync(job_id: int, config: dict): + """Run a workflow synchronously (call from background thread/task). + + This function: + 1. Writes config to a temp YAML file + 2. Spawns `sweets run` subprocess + 3. Streams stdout to log_manager line by line + 4. Updates job status in database when complete + """ + # Write config to temp file + with NamedTemporaryFile( + mode="w", suffix=".yaml", delete=False, prefix=f"sweets_job_{job_id}_" + ) as f: + yaml.safe_dump(config, f) + config_path = Path(f.name) + + with Session(engine) as session: + job = session.get(Job, job_id) + assert job is not None + + job.status = JobStatus.RUNNING + job.started_at = _utcnow() + # Cache the resolved work_dir on the Job row so the manifest / + # bowser-handoff endpoints can find it without re-parsing the config. + # Fall back to the server's cwd because that's what Workflow's + # `default_factory=Path.cwd` would resolve to inside the subprocess. + if not job.work_dir: + job.work_dir = str(config.get("work_dir") or Path.cwd()) + session.add(job) + session.commit() + + log_manager.append_log(job_id, f"Starting workflow for job {job_id}") + log_manager.append_log(job_id, f"Config: {config_path}") + + final_status: JobStatus = JobStatus.FAILED + try: + # Dispatch to the appropriate subcommand based on config contents. + # IFG configs carry a top-level "crossmul" key; displacement configs + # carry "dolphin". Default to "run" for any unrecognised shape. + subcommand = "ifg-run" if "crossmul" in config else "run" + + # Run sweets as subprocess + proc = subprocess.Popen( + [sys.executable, "-m", "sweets", subcommand, str(config_path)], + stdout=subprocess.PIPE, + stderr=subprocess.STDOUT, + text=True, + bufsize=1, # Line buffered + ) + + # Update PID in database + with Session(engine) as session: + job = session.get(Job, job_id) + assert job is not None + job.pid = proc.pid + session.add(job) + session.commit() + + log_manager.append_log(job_id, f"Process started with PID {proc.pid}") + + # Stream output in a separate thread (so we can handle it async if needed) + _stream_output(proc, job_id) + + # Wait for process to complete + return_code = proc.wait() + + if return_code == 0: + final_status = JobStatus.COMPLETED + log_manager.append_log(job_id, "Workflow completed successfully") + else: + final_status = JobStatus.FAILED + log_manager.append_log( + job_id, f"Workflow failed with exit code {return_code}" + ) + + except Exception as e: + final_status = JobStatus.FAILED + log_manager.append_log(job_id, f"Error: {e}") + + finally: + # Update job status + with Session(engine) as session: + job = session.get(Job, job_id) + assert job is not None + job.status = final_status + job.completed_at = _utcnow() + job.current_step = log_manager.get_current_step(job_id) + job.pid = None + + # Store last N lines as error message if failed + if final_status == JobStatus.FAILED: + history = log_manager.get_buffer(job_id).get_history() + job.error_message = "\n".join(history[-50:]) + + session.add(job) + session.commit() + + # Clean up temp config file + config_path.unlink(missing_ok=True) + + +def start_job_background(job_id: int, config: dict): + """Start a job in a background thread.""" + thread = threading.Thread( + target=run_workflow_sync, + args=(job_id, config), + daemon=True, + ) + thread.start() + return thread diff --git a/src/sweets/web/services/log_manager.py b/src/sweets/web/services/log_manager.py new file mode 100644 index 0000000..cd8e030 --- /dev/null +++ b/src/sweets/web/services/log_manager.py @@ -0,0 +1,129 @@ +"""Log management for streaming job output via WebSocket. + +Producer/consumer model: the executor runs the workflow subprocess in a +background thread and pushes each stdout line through ``append_log``. +WebSocket consumers subscribe to a per-job ``asyncio.Queue``. Because the +producer thread is *not* on the asyncio event loop, we route every queue +write through ``loop.call_soon_threadsafe`` so the queue's internal +``_wakeup`` machinery stays loop-bound. +""" + +from __future__ import annotations + +import asyncio +import re +import threading +from collections import defaultdict +from dataclasses import dataclass, field + +# Best-effort regex map from log lines to a 1-5 step bucket. Patterns are +# matched against pipeline log output that we don't control (dolphin / +# sweets.core / COMPASS subprocesses), so this is heuristic — the UI uses +# `max(current_step, this)` and we never go backward, so a missed transition +# only delays the indicator, never corrupts it. +STEP_PATTERNS = [ + (1, re.compile(r"(Downloading|Querying ASF|download)", re.IGNORECASE)), + (2, re.compile(r"(Creating GSLCs|Geocoding|geocode)", re.IGNORECASE)), + (3, re.compile(r"(Creating.*interferogram|burst interferogram)", re.IGNORECASE)), + (4, re.compile(r"(Stitching|stitch.*interferogram)", re.IGNORECASE)), + (5, re.compile(r"(Unwrapping|unwrap)", re.IGNORECASE)), +] + + +@dataclass(eq=False) +class _Subscriber: + """A single WebSocket consumer pinned to the event loop that owns it.""" + + queue: asyncio.Queue + loop: asyncio.AbstractEventLoop + + +@dataclass +class JobLogBuffer: + """Buffer for a single job's logs.""" + + lines: list[str] = field(default_factory=list) + current_step: int = 0 + subscribers: set[_Subscriber] = field(default_factory=set) + # Plain threading lock — `append` is called from the executor thread + # and `subscribe`/`unsubscribe` from the asyncio loop thread, so we + # need cross-thread safety, not asyncio cooperation. + _lock: threading.Lock = field(default_factory=threading.Lock) + + def append(self, line: str): + """Add a log line and notify subscribers. + + Safe to call from any thread; queue writes are dispatched onto + each subscriber's owning event loop via ``call_soon_threadsafe``. + """ + self.lines.append(line) + + for step_num, pattern in STEP_PATTERNS: + if pattern.search(line) and step_num > self.current_step: + self.current_step = step_num + break + + msg = {"type": "log", "line": line, "step": self.current_step} + with self._lock: + subs = list(self.subscribers) + for sub in subs: + sub.loop.call_soon_threadsafe(_safe_put, sub.queue, msg) + + def subscribe(self) -> asyncio.Queue: + """Subscribe to log updates. Must be called from inside the event loop.""" + queue: asyncio.Queue = asyncio.Queue(maxsize=1000) + sub = _Subscriber(queue=queue, loop=asyncio.get_running_loop()) + with self._lock: + self.subscribers.add(sub) + # Stash the wrapper on the queue so unsubscribe doesn't have to + # rescan the whole subscriber set. + queue._sweets_sub = sub # type: ignore[attr-defined] + return queue + + def unsubscribe(self, queue: asyncio.Queue): + """Unsubscribe from log updates.""" + sub = getattr(queue, "_sweets_sub", None) + if sub is None: + return + with self._lock: + self.subscribers.discard(sub) + + def get_history(self) -> list[str]: + """Get all buffered log lines.""" + return list(self.lines) + + +def _safe_put(queue: asyncio.Queue, msg: dict) -> None: + """put_nowait, swallowing QueueFull so a stalled client can't OOM us.""" + try: + queue.put_nowait(msg) + except asyncio.QueueFull: + pass + + +class LogManager: + """Manages log buffers for all jobs.""" + + def __init__(self): + self._buffers: dict[int, JobLogBuffer] = defaultdict(JobLogBuffer) + + def get_buffer(self, job_id: int) -> JobLogBuffer: + """Get or create a log buffer for a job.""" + return self._buffers[job_id] + + def append_log(self, job_id: int, line: str): + """Append a log line to a job's buffer.""" + self._buffers[job_id].append(line) + + def clear_buffer(self, job_id: int): + """Clear a job's log buffer.""" + if job_id in self._buffers: + del self._buffers[job_id] + + def get_current_step(self, job_id: int) -> int: + """Get the current workflow step for a job.""" + return self._buffers[job_id].current_step + + +# Global log manager instance +log_manager = LogManager() diff --git a/tests/test_burst_alignment.py b/tests/test_burst_alignment.py new file mode 100644 index 0000000..1912c7f --- /dev/null +++ b/tests/test_burst_alignment.py @@ -0,0 +1,326 @@ +"""Tests for sweets._burst_alignment. + +Pure math helpers are tested without I/O. +Integration tests use synthetic overlapping GeoTIFFs written to tmp_path. +""" + +from __future__ import annotations + +import numpy as np +import pytest +import rasterio +from rasterio.transform import from_bounds + +from sweets._burst_alignment import ( + BurstCorrection, + _aggregate_pair, + _apply_correction, + _solve_offset_lsq, + _valid_mask, + _weighted_median, + _wrap, + _wrap_scalar, + align_bursts, + apply_burst_offsets, + estimate_burst_offsets, +) + +# --------------------------------------------------------------------------- +# helpers / fixtures +# --------------------------------------------------------------------------- + +RNG = np.random.default_rng(42) +_CRS = rasterio.CRS.from_epsg(32610) + +# 100m pixels; A covers y=[0,10000], B covers y=[-5000,5000]. +# Overlap y=[0,5000] → bottom 50 rows of A and top 50 rows of B. +_TRANSFORM_A = from_bounds(0, 0, 10_000, 10_000, 100, 100) +_TRANSFORM_B = from_bounds(0, -5_000, 10_000, 5_000, 100, 100) +_KNOWN_OFFSET = 0.35 # radians (well below pi, suitable for wrapped data too) + + +def _write_tif(path, data, transform, crs=_CRS, nodata=None): + dtype = "complex64" if np.iscomplexobj(data) else "float32" + with rasterio.open( + path, + "w", + driver="GTiff", + height=data.shape[0], + width=data.shape[1], + count=1, + dtype=dtype, + crs=crs, + transform=transform, + nodata=nodata, + ) as dst: + dst.write(data, 1) + + +@pytest.fixture +def burst_tifs_real(tmp_path): + """Two overlapping unwrapped-phase GeoTIFFs with a known constant offset in B.""" + data_a = np.ones((100, 100), dtype=np.float32) + data_b = np.ones((100, 100), dtype=np.float32) + # Top 50 rows of B spatially overlap bottom 50 rows of A. + data_b[:50, :] = data_a[50:, :] + _KNOWN_OFFSET + + pa = tmp_path / "burst_a.tif" + pb = tmp_path / "burst_b.tif" + _write_tif(pa, data_a, _TRANSFORM_A) + _write_tif(pb, data_b, _TRANSFORM_B) + return pa, pb + + +@pytest.fixture +def burst_tifs_complex(tmp_path): + """Two overlapping wrapped-phase GeoTIFFs with a known constant phase offset in B.""" + data_a = np.ones((100, 100), dtype=np.complex64) + data_b = np.ones((100, 100), dtype=np.complex64) + data_b[:50, :] = data_a[50:, :] * np.exp(1j * _KNOWN_OFFSET).astype(np.complex64) + + pa = tmp_path / "burst_a.tif" + pb = tmp_path / "burst_b.tif" + _write_tif(pa, data_a, _TRANSFORM_A) + _write_tif(pb, data_b, _TRANSFORM_B) + return pa, pb + + +# --------------------------------------------------------------------------- +# BurstCorrection +# --------------------------------------------------------------------------- + + +def test_burst_correction_evaluate_constant(): + corr = BurstCorrection(offset=0.3, x_ref=0.0, y_ref=0.0) + x = np.array([1.0, 2.0]) + y = np.array([3.0, 4.0]) + np.testing.assert_allclose(corr.evaluate(x, y), 0.3) + + +def test_burst_correction_evaluate_planar(): + corr = BurstCorrection(offset=0.1, cx=0.01, cy=0.02, x_ref=0.0, y_ref=0.0) + assert corr.evaluate(np.array([100.0]), np.array([0.0]))[0] == pytest.approx( + 0.1 + 0.01 * 100.0 + ) + + +def test_burst_correction_is_planar(): + assert not BurstCorrection(offset=1.0).is_planar + assert BurstCorrection(cx=0.001).is_planar + assert BurstCorrection(cy=0.001).is_planar + + +# --------------------------------------------------------------------------- +# _wrap_scalar / _wrap +# --------------------------------------------------------------------------- + + +@pytest.mark.parametrize( + "x, expected", + [ + (0.0, 0.0), + (np.pi, -np.pi), # boundary wraps to -pi + (np.pi + 0.1, -np.pi + 0.1), + (-np.pi - 0.1, np.pi - 0.1), + (2 * np.pi, 0.0), + ], +) +def test_wrap_scalar(x, expected): + assert _wrap_scalar(x) == pytest.approx(expected, abs=1e-10) + + +def test_wrap_array_in_range(): + x = np.linspace(-4 * np.pi, 4 * np.pi, 200) + w = _wrap(x) + assert (w >= -np.pi).all() and (w < np.pi).all() + + +# --------------------------------------------------------------------------- +# _weighted_median +# --------------------------------------------------------------------------- + + +def test_weighted_median_equal_weights(): + # _weighted_median uses continuous CDF interpolation, which gives the + # midpoint between the two central values for an even-count uniform sample. + v = np.array([1.0, 2.0, 3.0, 4.0, 5.0]) + w = np.ones(5) + result = _weighted_median(v, w) + # Interp at CDF=0.5 lands between the 2nd (0.4) and 3rd (0.6) values → 2.5 + assert result == pytest.approx(2.5, abs=0.1) + + +def test_weighted_median_heavy_tail(): + v = np.array([1.0, 2.0, 10.0]) + w = np.array([1.0, 1.0, 100.0]) + assert _weighted_median(v, w) > 5.0 # pulled toward the heavy-weight sample + + +# --------------------------------------------------------------------------- +# _aggregate_pair +# --------------------------------------------------------------------------- + + +def test_aggregate_pair_mean_real(): + v = np.array([0.2, 0.3, 0.4]) + w = np.ones(3) + assert _aggregate_pair(v, w, method="mean", is_complex=False) == pytest.approx(0.3) + + +def test_aggregate_pair_mean_complex_recovers_phase(): + phase = 0.5 + v = np.array([phase, phase, phase]) + w = np.ones(3) + assert _aggregate_pair(v, w, method="mean", is_complex=True) == pytest.approx( + phase, abs=1e-5 + ) + + +def test_aggregate_pair_median_real(): + v = np.array([0.1, 0.3, 10.0]) # outlier at 10.0 + w = np.ones(3) + result = _aggregate_pair(v, w, method="median", is_complex=False) + assert abs(result - 0.3) < 0.5 # median ignores the outlier + + +# --------------------------------------------------------------------------- +# _valid_mask +# --------------------------------------------------------------------------- + + +def test_valid_mask_real_nodata(): + arr = np.array([1.0, np.nan, 0.0, 2.0]) + v = _valid_mask(arr, nodata=0.0) + assert list(v) == [True, False, False, True] + + +def test_valid_mask_complex_excludes_zero(): + arr = np.array([1 + 0j, 0 + 0j, 1 + 1j, np.nan + 0j], dtype=np.complex64) + v = _valid_mask(arr, nodata=None) + assert list(v) == [True, False, True, False] + + +# --------------------------------------------------------------------------- +# _solve_offset_lsq +# --------------------------------------------------------------------------- + + +def test_solve_offset_lsq_two_bursts(): + offset = 0.4 + # Burst 1 is +offset ahead of burst 0. + pair_eqs: list[tuple[int, int, float, float]] = [(0, 1, offset, 1.0)] + deltas = _solve_offset_lsq(pair_eqs, n_bursts=2, anchor_index=0, is_complex=False) + assert deltas[0] == pytest.approx(0.0, abs=1e-6) + assert deltas[1] == pytest.approx(offset, abs=1e-4) + + +def test_solve_offset_lsq_three_bursts_chain(): + # 0 → 1 (offset 0.3), 1 → 2 (offset -0.2). Anchor = 0. + pair_eqs: list[tuple[int, int, float, float]] = [ + (0, 1, 0.3, 1.0), + (1, 2, -0.2, 1.0), + ] + deltas = _solve_offset_lsq(pair_eqs, n_bursts=3, anchor_index=0, is_complex=False) + assert deltas[0] == pytest.approx(0.0, abs=1e-5) + assert deltas[1] == pytest.approx(0.3, abs=1e-4) + assert deltas[2] == pytest.approx(0.1, abs=1e-4) + + +def test_solve_offset_lsq_no_equations_returns_zeros(): + deltas = _solve_offset_lsq([], n_bursts=3, anchor_index=0, is_complex=False) + np.testing.assert_array_equal(deltas, 0.0) + + +# --------------------------------------------------------------------------- +# _apply_correction +# --------------------------------------------------------------------------- + + +def test_apply_correction_real_removes_offset(): + arr = np.full((10, 10), 2.0, dtype=np.float32) + corr = BurstCorrection(offset=0.5) + transform = _TRANSFORM_A + out = _apply_correction(arr, corr, nodata=None, transform=transform) + np.testing.assert_allclose(out, 1.5, atol=1e-6) + + +def test_apply_correction_complex_removes_phase(): + phase = 0.4 + arr = np.exp(1j * phase).astype(np.complex64) * np.ones( + (10, 10), dtype=np.complex64 + ) + corr = BurstCorrection(offset=phase) + out = _apply_correction(arr, corr, nodata=None, transform=_TRANSFORM_A) + np.testing.assert_allclose(np.angle(out), 0.0, atol=1e-5) + + +def test_apply_correction_preserves_nodata(): + arr = np.array([[1.0, 0.0, 2.0]], dtype=np.float32) # 0.0 is nodata + corr = BurstCorrection(offset=0.5) + out = _apply_correction(arr, corr, nodata=0.0, transform=_TRANSFORM_A) + assert out[0, 1] == 0.0 # nodata pixel unchanged + + +# --------------------------------------------------------------------------- +# estimate_burst_offsets — integration +# --------------------------------------------------------------------------- + + +def test_estimate_offsets_real_recovers_constant(burst_tifs_real): + pa, pb = burst_tifs_real + corrections = estimate_burst_offsets([pa, pb], degree=0) + assert corrections[pa].offset == pytest.approx(0.0, abs=1e-4) + assert corrections[pb].offset == pytest.approx(_KNOWN_OFFSET, abs=0.05) + + +def test_estimate_offsets_complex_recovers_phase(burst_tifs_complex): + pa, pb = burst_tifs_complex + corrections = estimate_burst_offsets([pa, pb], degree=0) + assert corrections[pa].offset == pytest.approx(0.0, abs=1e-4) + assert corrections[pb].offset == pytest.approx(_KNOWN_OFFSET, abs=0.05) + + +def test_estimate_offsets_single_file_returns_zero(burst_tifs_real): + pa, _ = burst_tifs_real + corrections = estimate_burst_offsets([pa], degree=0) + assert corrections[pa].offset == pytest.approx(0.0) + + +# --------------------------------------------------------------------------- +# apply_burst_offsets — integration +# --------------------------------------------------------------------------- + + +def test_apply_offsets_zeroes_seam(burst_tifs_real, tmp_path): + pa, pb = burst_tifs_real + corrections = estimate_burst_offsets([pa, pb], degree=0) + out_dir = tmp_path / "aligned" + apply_burst_offsets([pa, pb], corrections, out_dir) + + pa_out = out_dir / "burst_a.aligned.tif" + pb_out = out_dir / "burst_b.aligned.tif" + assert pa_out.exists() + assert pb_out.exists() + + # Read the corrected data and verify the overlap values match. + with rasterio.open(pa_out) as src: + a_corrected = src.read(1) + with rasterio.open(pb_out) as src: + b_corrected = src.read(1) + + # Bottom 50 rows of A and top 50 rows of B overlap spatially. + # After correction their values should be close. + np.testing.assert_allclose(a_corrected[50:, :], b_corrected[:50, :], atol=0.1) + + +# --------------------------------------------------------------------------- +# align_bursts — end-to-end +# --------------------------------------------------------------------------- + + +def test_align_bursts_returns_corrected_paths(burst_tifs_real, tmp_path): + pa, pb = burst_tifs_real + out_paths, corrections = align_bursts([pa, pb], tmp_path / "aligned") + assert len(out_paths) == 2 + assert all(p.exists() for p in out_paths) + assert corrections[pb].offset == pytest.approx(_KNOWN_OFFSET, abs=0.05) diff --git a/tests/test_crossmul.py b/tests/test_crossmul.py new file mode 100644 index 0000000..265dcfb --- /dev/null +++ b/tests/test_crossmul.py @@ -0,0 +1,355 @@ +"""Tests for sweets._crossmul. + +Pure math helpers are tested with synthetic numpy arrays (no I/O). +run_crossmul is tested with small GeoTIFF SLCs written to tmp_path. +""" + +from __future__ import annotations + +import numpy as np +import pytest +import rasterio +from rasterio.transform import from_bounds + +from sweets._crossmul import ( + CrossmulOptions, + _boxcar_multilook, + _compute_coherence, + _gaussian_kernel_1d, + _gaussian_multilook, + _output_geotransform, + run_crossmul, +) + +# --------------------------------------------------------------------------- +# helpers +# --------------------------------------------------------------------------- + +RNG = np.random.default_rng(0) + + +def _make_slc(shape: tuple[int, int]) -> np.ndarray: + """Unit-amplitude complex SLC with random phase.""" + phase = RNG.uniform(-np.pi, np.pi, shape).astype(np.float32) + return np.exp(1j * phase).astype(np.complex64) + + +@pytest.fixture +def slc_geotiffs(tmp_path): + """Two 40-row × 80-col complex64 GeoTIFFs for run_crossmul integration tests.""" + transform = from_bounds(0, 0, 8000, 4000, 80, 40) + crs = rasterio.CRS.from_epsg(32610) + + # ifg = ref * conj(sec) = |ref|^2 * exp(j*(phi_ref - phi_sec)) + # sec leads by known_phase → ifg phase = -known_phase + known_phase = 0.7 + ref_data = _make_slc((40, 80)) + sec_data = ref_data * np.exp(1j * known_phase).astype(np.complex64) + + paths = {} + for name, data in (("ref.tif", ref_data), ("sec.tif", sec_data)): + p = tmp_path / name + with rasterio.open( + p, + "w", + driver="GTiff", + height=40, + width=80, + count=1, + dtype="complex64", + crs=crs, + transform=transform, + ) as dst: + dst.write(data, 1) + paths[name] = p + + return paths["ref.tif"], paths["sec.tif"], known_phase + + +# --------------------------------------------------------------------------- +# _gaussian_kernel_1d +# --------------------------------------------------------------------------- + + +def test_gaussian_kernel_sums_to_one(): + k = _gaussian_kernel_1d(sigma=3.0) + assert abs(float(k.sum()) - 1.0) < 1e-6 + + +def test_gaussian_kernel_is_symmetric(): + k = _gaussian_kernel_1d(sigma=5.0) + np.testing.assert_allclose(k, k[::-1], atol=1e-7) + + +def test_gaussian_kernel_length(): + # radius = int(4.0 * sigma + 0.5); length = 2*radius + 1 + sigma = 4.0 + radius = int(4.0 * sigma + 0.5) + k = _gaussian_kernel_1d(sigma) + assert len(k) == 2 * radius + 1 + + +# --------------------------------------------------------------------------- +# _boxcar_multilook +# --------------------------------------------------------------------------- + + +@pytest.mark.parametrize("looks", [(4, 8), (2, 2), (3, 5)]) +def test_boxcar_output_shape(looks): + az, rg = looks + arr = np.ones((40, 80)) + out = _boxcar_multilook(arr, looks) + assert out.shape == (40 // az, 80 // rg) + + +def test_boxcar_constant_real(): + arr = np.full((20, 40), 3.5) + out = _boxcar_multilook(arr, (4, 8)) + np.testing.assert_allclose(out, 3.5, rtol=1e-6) + + +def test_boxcar_constant_complex(): + val = 1.0 + 2.0j + arr = np.full((20, 40), val, dtype=np.complex64) + out = _boxcar_multilook(arr, (4, 8)) + np.testing.assert_allclose(out, val, rtol=1e-5) + + +def test_boxcar_non_divisible_truncates(): + # 101 cols with rg_looks=40 → floor(101/40)=2 output cols, not ceil + arr = np.ones((40, 101)) + out = _boxcar_multilook(arr, (4, 40)) + assert out.shape == (10, 2) + + +# --------------------------------------------------------------------------- +# _gaussian_multilook +# --------------------------------------------------------------------------- + + +@pytest.mark.parametrize("looks", [(4, 8), (2, 4)]) +def test_gaussian_output_shape_matches_boxcar(looks): + arr = RNG.standard_normal((40, 80)).astype(np.float32) + assert _gaussian_multilook(arr, looks).shape == _boxcar_multilook(arr, looks).shape + + +def test_gaussian_smooths_constant_real(): + # Zero-padding at edges attenuates edge pixels, so only check interior. + arr = np.full((80, 160), 2.5, dtype=np.float32) + out = _gaussian_multilook(arr, (4, 8)) + interior = out[3:-3, 3:-3] + np.testing.assert_allclose(interior, 2.5, atol=0.05) + + +def test_gaussian_smooths_constant_complex(): + val = np.complex64(1.0 + 0.5j) + arr = np.full((80, 160), val, dtype=np.complex64) + out = _gaussian_multilook(arr, (4, 8)) + interior = out[3:-3, 3:-3] + np.testing.assert_allclose(interior.real, val.real, atol=0.05) + np.testing.assert_allclose(interior.imag, val.imag, atol=0.05) + + +def test_gaussian_non_divisible_truncates(): + # Regression: P2 fix — 101 cols with rg=40 must not produce 3 output cols. + arr = np.ones((40, 101), dtype=np.float32) + out = _gaussian_multilook(arr, (4, 40)) + assert out.shape == (10, 2) + + +# --------------------------------------------------------------------------- +# _output_geotransform — regression for P1 (no half-window origin shift) +# --------------------------------------------------------------------------- + + +def test_output_geotransform_origin_unchanged(): + gt = [100.0, 10.0, 0.0, 500.0, 0.0, -10.0] + out = _output_geotransform(gt, az_looks=10, rg_looks=40) + assert out[0] == 100.0, "x0 must not shift" + assert out[3] == 500.0, "y0 must not shift" + + +def test_output_geotransform_spacing_scaled(): + gt = [0.0, 10.0, 0.0, 0.0, 0.0, -10.0] + out = _output_geotransform(gt, az_looks=10, rg_looks=40) + assert out[1] == 400.0 # dx * rg_looks + assert out[5] == -100.0 # dy * az_looks + + +# --------------------------------------------------------------------------- +# _compute_coherence +# --------------------------------------------------------------------------- + + +def test_coherence_identical_slcs(): + # ref == sec → phase cancels, coherence == 1 + slc = _make_slc((10, 20)) + power = (slc.real**2 + slc.imag**2).astype(np.float32) + ifg = slc * np.conj(slc) + coh = _compute_coherence(ifg, power, power) + np.testing.assert_allclose(coh, 1.0, atol=1e-5) + + +def test_coherence_zero_power(): + ifg = np.zeros((4, 4), dtype=np.complex64) + power = np.zeros((4, 4), dtype=np.float32) + coh = _compute_coherence(ifg, power, power) + assert (coh == 0.0).all() + + +def test_coherence_clipped_to_unit_interval(): + # Feed deliberately large values; output must stay in [0, 1]. + ifg = np.full((4, 4), 1e10 + 0j, dtype=np.complex64) + power = np.ones((4, 4), dtype=np.float32) + coh = _compute_coherence(ifg, power, power) + assert (coh >= 0.0).all() and (coh <= 1.0).all() + + +# --------------------------------------------------------------------------- +# run_crossmul — integration (real GeoTIFF SLCs, subdataset="") +# --------------------------------------------------------------------------- + + +def test_run_crossmul_output_files_created(slc_geotiffs, tmp_path): + ref, sec, _ = slc_geotiffs + opts = CrossmulOptions(looks=(4, 8), lines_per_block=5) + ifg_p, coh_p = run_crossmul( + ref, + sec, + tmp_path / "pair", + date1="20200101", + date2="20200113", + options=opts, + subdataset="", + ) + assert ifg_p.exists() + assert coh_p.exists() + + +def test_run_crossmul_output_shape(slc_geotiffs, tmp_path): + ref, sec, _ = slc_geotiffs + opts = CrossmulOptions(looks=(4, 8), lines_per_block=5) + ifg_p, coh_p = run_crossmul( + ref, + sec, + tmp_path / "pair", + date1="20200101", + date2="20200113", + options=opts, + subdataset="", + ) + with rasterio.open(ifg_p) as ds: + assert ds.height == 40 // 4 + assert ds.width == 80 // 8 + + with rasterio.open(coh_p) as ds: + assert ds.height == 40 // 4 + assert ds.width == 80 // 8 + + +def test_run_crossmul_geotransform_no_origin_shift(slc_geotiffs, tmp_path): + ref, sec, _ = slc_geotiffs + opts = CrossmulOptions(looks=(4, 8)) + ifg_p, _ = run_crossmul( + ref, + sec, + tmp_path / "pair", + date1="20200101", + date2="20200113", + options=opts, + subdataset="", + ) + with rasterio.open(ref) as src: + ref_origin = (src.transform.c, src.transform.f) + with rasterio.open(ifg_p) as dst: + out_origin = (dst.transform.c, dst.transform.f) + assert ref_origin == pytest.approx( + out_origin + ), "origin must not shift after multilooking" + + +def test_run_crossmul_phase_recovery(slc_geotiffs, tmp_path): + ref, sec, known_phase = slc_geotiffs + opts = CrossmulOptions(looks=(4, 8), lines_per_block=5) + ifg_p, coh_p = run_crossmul( + ref, + sec, + tmp_path / "pair", + date1="20200101", + date2="20200113", + options=opts, + subdataset="", + ) + from dolphin.io import load_gdal + + ifg = load_gdal(ifg_p) + coh = load_gdal(coh_p) + + phase = np.angle(ifg[coh > 0.5]) + # run_crossmul computes ref * conj(sec), so phase = phi_ref - phi_sec = -known_phase + np.testing.assert_allclose(phase, -known_phase, atol=0.05) + + +def test_run_crossmul_skip_existing(slc_geotiffs, tmp_path): + ref, sec, _ = slc_geotiffs + opts = CrossmulOptions(looks=(4, 8)) + pair_dir = tmp_path / "pair" + + ifg_p, coh_p = run_crossmul( + ref, + sec, + pair_dir, + date1="20200101", + date2="20200113", + options=opts, + subdataset="", + ) + mtime_ifg = ifg_p.stat().st_mtime + mtime_coh = coh_p.stat().st_mtime + + # Second call without overwrite must not touch the files. + run_crossmul( + ref, + sec, + pair_dir, + date1="20200101", + date2="20200113", + options=opts, + subdataset="", + overwrite=False, + ) + assert ifg_p.stat().st_mtime == mtime_ifg + assert coh_p.stat().st_mtime == mtime_coh + + +def test_run_crossmul_overwrite_refreshes(slc_geotiffs, tmp_path): + ref, sec, _ = slc_geotiffs + opts = CrossmulOptions(looks=(4, 8)) + pair_dir = tmp_path / "pair" + + ifg_p, _ = run_crossmul( + ref, + sec, + pair_dir, + date1="20200101", + date2="20200113", + options=opts, + subdataset="", + ) + mtime_first = ifg_p.stat().st_mtime + + import time + + time.sleep(0.05) # ensure mtime can change + + run_crossmul( + ref, + sec, + pair_dir, + date1="20200101", + date2="20200113", + options=opts, + subdataset="", + overwrite=True, + ) + assert ifg_p.stat().st_mtime > mtime_first diff --git a/tests/test_web.py b/tests/test_web.py new file mode 100644 index 0000000..947d634 --- /dev/null +++ b/tests/test_web.py @@ -0,0 +1,131 @@ +"""Smoke tests for the sweets web API. + +Only exercises the always-available endpoints (no live ASF/CMR, no +subprocess spawn). Skipped wholesale when the ``web`` extras (fastapi, +sqlmodel, ...) aren't installed. +""" + +from __future__ import annotations + +import importlib.util + +import pytest + +if any( + importlib.util.find_spec(mod) is None for mod in ("fastapi", "sqlmodel", "httpx") +): + pytest.skip("web extras not installed", allow_module_level=True) + +from fastapi.testclient import TestClient # noqa: E402 + + +@pytest.fixture +def client(tmp_path, monkeypatch): + """A TestClient bound to an isolated on-disk SQLite DB.""" + db_path = tmp_path / "sweets.db" + monkeypatch.setattr( + "sweets.web.models.database.DEFAULT_DB_PATH", db_path, raising=True + ) + from sqlmodel import SQLModel, create_engine + + fresh_engine = create_engine(f"sqlite:///{db_path}", echo=False) + monkeypatch.setattr("sweets.web.models.database.engine", fresh_engine, raising=True) + # Repoint the modules that captured `engine` at import time. + import sweets.web.api.jobs as jobs_mod + import sweets.web.api.websocket as ws_mod + import sweets.web.app as app_mod + import sweets.web.services.executor as exec_mod + + for mod in (jobs_mod, ws_mod, exec_mod, app_mod): + monkeypatch.setattr(mod, "engine", fresh_engine, raising=False) + SQLModel.metadata.create_all(fresh_engine) + + return TestClient(app_mod.app) + + +def test_health(client): + r = client.get("/api/health") + assert r.status_code == 200 + assert r.json() == {"status": "ok"} + + +def test_schema_endpoint(client): + r = client.get("/api/schema") + assert r.status_code == 200 + schema = r.json() + # The Workflow schema must expose the discriminated `search` union so + # the frontend's RJSF form picks the right oneOf branch. + assert "properties" in schema + assert "search" in schema["properties"] + + +def test_create_job_rejects_missing_aoi(client): + """JobCreate's validator must reject a config with no bbox/wkt.""" + r = client.post("/api/jobs/", json={"name": "j", "config": {}}) + assert r.status_code in (400, 422) + + +def test_stale_running_jobs_are_swept(client): + """A RUNNING job left over from a previous server run should be reaped. + + Simulates the case where the server crashed mid-job: pid is dead (or + never existed), but the DB row still says RUNNING. The lifespan sweep + must flip it to FAILED so the user isn't stuck. + """ + from sweets.web.app import _sweep_stale_jobs + from sweets.web.models import Job, JobStatus + from sweets.web.models.database import engine + from sqlmodel import Session + + with Session(engine) as session: + stuck = Job( + name="zombie", + config={"bbox": [0.0, 0.0, 1.0, 1.0]}, + status=JobStatus.RUNNING, + pid=0, # PID 0 raises OSError on os.kill; that path is exercised + ) + session.add(stuck) + session.commit() + session.refresh(stuck) + stuck_id = stuck.id + + _sweep_stale_jobs() + + r = client.get(f"/api/jobs/{stuck_id}") + assert r.status_code == 200 + body = r.json() + assert body["status"] == "failed" + assert "server restart" in (body.get("error_message") or "") + + +def test_job_lifecycle_without_spawn(client): + """Create → list → fetch → delete a job without ever running it.""" + payload = { + "name": "smoke", + "config": {"bbox": [-118.5, 34.0, -118.0, 34.3]}, + } + r = client.post("/api/jobs/", json=payload) + assert r.status_code == 200, r.text + job = r.json() + job_id = job["id"] + assert job["status"] == "pending" + + r = client.get("/api/jobs/") + assert r.status_code == 200 + assert any(j["id"] == job_id for j in r.json()) + + r = client.get(f"/api/jobs/{job_id}") + assert r.status_code == 200 + assert r.json()["name"] == "smoke" + + # A pending job has no work_dir yet — the manifest should report + # exists=False rather than 500. + r = client.get(f"/api/jobs/{job_id}/manifest") + assert r.status_code == 200 + assert r.json()["exists"] is False + + r = client.delete(f"/api/jobs/{job_id}") + assert r.status_code == 200 + + r = client.get(f"/api/jobs/{job_id}") + assert r.status_code == 404