2935 lines
105 KiB
Python
2935 lines
105 KiB
Python
"""ENVI/SARscape integration service via envipyengine.
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Single execution engine: envipyengine → taskengine.exe subprocess.
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Provides Import and D-InSAR workflows with smart chaining
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(D-InSAR auto-detects missing imports and runs them first).
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"""
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from __future__ import annotations
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import json
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import math
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import os
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import subprocess
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import sys
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import time
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import defusedxml.ElementTree as ET
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from contextlib import contextmanager
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from concurrent.futures import ThreadPoolExecutor, TimeoutError as FuturesTimeoutError
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from datetime import datetime
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from glob import glob
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from typing import Any, Dict, List, Optional
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from ..config import get_env_text, settings
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from ..process_utils import is_any_process_running
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from .dinsar_naming import (
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PAIR_META_FILENAME,
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build_fallback_pair_key,
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build_run_key,
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find_json_sidecar,
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write_run_metadata,
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)
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from .dinsar_result_layout_service import get_run_native_output_dir
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_BACKEND_DIR = type(settings).BACKEND_DIR
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# ---------------------------------------------------------------------------
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# Config helpers
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# ---------------------------------------------------------------------------
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def _read_env(name: str, default: Optional[str] = None) -> Optional[str]:
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return get_env_text(name, default)
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# ---------------------------------------------------------------------------
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# Path helpers
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# ---------------------------------------------------------------------------
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def _normalize_path(value: Any) -> str:
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"""Normalize to forward-slash path (ENVI convention)."""
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normalized = str(value or "").strip().strip('"').strip("'")
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if not normalized:
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return ""
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return normalized.replace("\\", "/")
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def _to_local_path(value: Any) -> str:
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"""Normalize to OS-native path."""
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raw = str(value or "").strip().strip('"').strip("'")
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if not raw:
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return ""
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return os.path.normpath(raw.replace("/", os.sep))
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def get_envi_runner_python() -> str:
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configured = _to_local_path(getattr(settings, "PYTHON_PATH", "") or "")
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if configured:
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return configured
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return os.path.normpath(sys.executable)
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def get_envi_taskengine_cwd() -> str:
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"""Dedicated cwd for envipyengine/taskengine temp files.
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SARscape can create zero-byte env_*.xyz and IDL*.tmp files in the current
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working directory. Keep those files under runtime instead of the repo root.
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"""
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base_dir = _to_local_path(
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getattr(settings, "IDL_WORKER_RUNTIME_DIR", "")
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or os.path.join(_BACKEND_DIR, "runtime", "idl_worker")
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)
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cwd = os.path.join(base_dir, "envi_cwd")
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os.makedirs(cwd, exist_ok=True)
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return os.path.normpath(os.path.abspath(cwd))
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def get_envi_custom_code_dir() -> str:
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envi_root = _envi_install_root()
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if not envi_root:
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return ""
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candidates = [
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os.path.join(envi_root, "user_custom_code"),
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os.path.join(envi_root, "custom_code"),
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]
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for path in candidates:
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if os.path.isdir(path):
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return os.path.normpath(os.path.abspath(path))
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return ""
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def get_envi_runner_cwd() -> str:
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return get_envi_taskengine_cwd()
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def get_envi_runner_env() -> Dict[str, str]:
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env = os.environ.copy()
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project_root = os.path.normpath(os.path.abspath(type(settings).PROJECT_ROOT))
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taskengine_cwd = get_envi_taskengine_cwd()
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existing = [part for part in str(env.get("PYTHONPATH") or "").split(os.pathsep) if str(part).strip()]
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ordered = [project_root, *existing]
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deduped: List[str] = []
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seen = set()
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for raw_path in ordered:
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try:
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key = os.path.normcase(os.path.normpath(os.path.abspath(str(raw_path))))
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except Exception:
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key = str(raw_path)
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if key in seen:
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continue
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seen.add(key)
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deduped.append(str(raw_path))
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env["PYTHONPATH"] = os.pathsep.join(deduped)
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env["TEMP"] = taskengine_cwd
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env["TMP"] = taskengine_cwd
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env["IDL_TMPDIR"] = taskengine_cwd
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custom_code_dir = get_envi_custom_code_dir()
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if custom_code_dir:
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env["ENVI_CUSTOM_CODE"] = custom_code_dir
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return env
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@contextmanager
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def _envi_taskengine_runtime_context():
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"""Run in-process ENVI calls from the dedicated runtime cwd."""
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target_cwd = get_envi_taskengine_cwd()
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old_cwd = os.getcwd()
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old_env = {name: os.environ.get(name) for name in ("TEMP", "TMP", "IDL_TMPDIR")}
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os.environ["TEMP"] = target_cwd
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os.environ["TMP"] = target_cwd
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os.environ["IDL_TMPDIR"] = target_cwd
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try:
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os.chdir(target_cwd)
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yield target_cwd
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finally:
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os.chdir(old_cwd)
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for name, value in old_env.items():
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if value is None:
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os.environ.pop(name, None)
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else:
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os.environ[name] = value
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def build_envi_runner_command(*args: Any) -> List[str]:
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command = [
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get_envi_runner_python(),
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"-m",
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"backend.app.services.envi_runner_cli",
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]
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command.extend(str(arg) for arg in args if arg is not None)
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return command
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def _list_taskengine_pids() -> set[int]:
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"""Return taskengine.exe PIDs on Windows without importing optional deps."""
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if os.name != "nt":
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return set()
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try:
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completed = subprocess.run(
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[
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"powershell.exe",
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"-NoProfile",
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"-Command",
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"Get-Process taskengine -ErrorAction SilentlyContinue | ForEach-Object { $_.Id }",
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],
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capture_output=True,
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text=True,
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timeout=5,
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check=False,
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)
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except Exception:
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return set()
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pids: set[int] = set()
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for line in str(completed.stdout or "").splitlines():
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raw = line.strip()
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if raw.isdigit():
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pids.add(int(raw))
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return pids
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def _stop_taskengine_pids(pids: set[int]) -> List[int]:
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"""Stop specific taskengine.exe PIDs; avoids killing pre-existing sessions."""
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stopped: List[int] = []
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if os.name != "nt":
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return stopped
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for pid in sorted(pids):
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try:
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subprocess.run(
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[
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"powershell.exe",
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"-NoProfile",
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"-Command",
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f"Stop-Process -Id {int(pid)} -Force -ErrorAction SilentlyContinue",
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],
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capture_output=True,
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text=True,
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timeout=10,
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check=False,
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)
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stopped.append(int(pid))
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except Exception:
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continue
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return stopped
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def _cleanup_new_taskengine_processes(existing_pids: set[int]) -> Dict[str, Any]:
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"""Best-effort cleanup for taskengine.exe children spawned by a timed-out runner."""
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existing = set(existing_pids or set())
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first_targets = _list_taskengine_pids() - existing
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stopped = _stop_taskengine_pids(first_targets)
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# taskengine can take a moment to detach from the runner process. Re-check once.
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time.sleep(1)
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second_targets = _list_taskengine_pids() - existing
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stopped.extend(pid for pid in _stop_taskengine_pids(second_targets) if pid not in stopped)
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time.sleep(1)
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remaining = sorted(_list_taskengine_pids() - existing)
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return {
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"taskengine_cleanup_attempted": True,
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"taskengine_stopped_pids": sorted(set(stopped)),
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"taskengine_remaining_new_pids": remaining,
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}
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def probe_envi_runner() -> Dict[str, Any]:
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python_path = get_envi_runner_python()
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project_root = get_envi_runner_cwd()
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result: Dict[str, Any] = {
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"python_path": python_path,
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"cwd": project_root,
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"ready": False,
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"returncode": None,
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"message": "",
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}
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if not python_path:
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result["message"] = "PYTHON_PATH is empty."
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return result
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if not os.path.isfile(python_path):
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result["message"] = f"Python executable not found: {python_path}"
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return result
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if not os.path.isdir(project_root):
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result["message"] = f"Project root not found: {project_root}"
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return result
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try:
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completed = subprocess.run(
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build_envi_runner_command("--help"),
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cwd=project_root,
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env=get_envi_runner_env(),
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capture_output=True,
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text=True,
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timeout=20,
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check=False,
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)
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except Exception as exc:
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result["message"] = str(exc)
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return result
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result["returncode"] = int(completed.returncode)
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if completed.returncode == 0:
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result["ready"] = True
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result["message"] = "Runner entrypoint is available."
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return result
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stderr_text = str(completed.stderr or "").strip()
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stdout_text = str(completed.stdout or "").strip()
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result["message"] = (stderr_text or stdout_text or f"returncode={completed.returncode}")[:1000]
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return result
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# ---------------------------------------------------------------------------
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# Configuration (read once at import time)
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# ---------------------------------------------------------------------------
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IDL_EXECUTABLE = _read_env(
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"IDL_EXECUTABLE",
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r"C:\Program Files\Harris\ENVI56\IDL88\bin\bin.x86_64\idl.exe",
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)
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IDL_WORKBENCH_PATH = _read_env(
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"IDL_WORKBENCH_PATH",
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r"C:\Program Files\Harris\ENVI56\IDL88\bin\bin.x86_64\idlde.exe",
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)
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# ---------------------------------------------------------------------------
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# envipyengine config bootstrap
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# ---------------------------------------------------------------------------
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# envipyengine reads taskengine path from %LOCALAPPDATA%\envipyengine\settings.cfg.
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# To avoid per-machine manual setup, we redirect LOCALAPPDATA to the project's
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# runtime dir and auto-generate settings.cfg from IDL_EXECUTABLE at first use.
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_ENVIPY_CONFIG_BASE = os.path.join(_BACKEND_DIR, "runtime")
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_TASKENGINE_EXE = os.path.join(os.path.dirname(IDL_EXECUTABLE), "taskengine.exe") if IDL_EXECUTABLE else ""
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def _ensure_envipyengine_config() -> None:
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"""Write envipyengine settings.cfg into the project runtime dir and
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redirect LOCALAPPDATA so envipyengine picks it up automatically.
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||
Safe to call multiple times (no-op if already configured correctly).
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||
"""
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if not _TASKENGINE_EXE:
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return
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||
cfg_dir = os.path.join(_ENVIPY_CONFIG_BASE, "envipyengine")
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cfg_path = os.path.join(cfg_dir, "settings.cfg")
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expected = (
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f"[envipyengine]\n"
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||
f"engine = {_TASKENGINE_EXE}\n\n"
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||
f"[engine-environment]\n"
|
||
)
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||
try:
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||
with open(cfg_path, "r", encoding="utf-8") as _cfg_f:
|
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if _cfg_f.read() == expected:
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||
os.environ["LOCALAPPDATA"] = _ENVIPY_CONFIG_BASE
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||
return
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||
except OSError as exc:
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||
print(f"[WARN] _ensure_config: {exc}")
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os.makedirs(cfg_dir, exist_ok=True)
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with open(cfg_path, "w", encoding="utf-8") as f:
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f.write(expected)
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os.environ["LOCALAPPDATA"] = _ENVIPY_CONFIG_BASE
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||
DEM_BASE_FILE = _to_local_path(
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||
_read_env("IDL_DINSAR_DEM_BASE_FILE", "")
|
||
)
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||
RUNTIME_DIR = _read_env(
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||
"IDL_WORKER_RUNTIME_DIR",
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||
os.path.join(_BACKEND_DIR, "runtime", "idl_worker"),
|
||
)
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DEFAULT_TIMEOUT = int(_read_env("IDL_WORKER_DEFAULT_TIMEOUT_SECONDS", "14400") or 14400)
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MAX_TIMEOUT = int(_read_env("IDL_WORKER_MAX_TIMEOUT_SECONDS", "43200") or 43200)
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||
|
||
# Custom D-InSAR parameters (step-by-step mode)
|
||
CUSTOM_TARGET_RESOLUTION_M = float(
|
||
_read_env("IDL_DINSAR_CUSTOM_TARGET_RESOLUTION_M", "10.0") or 10.0
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||
)
|
||
CUSTOM_FILTER_METHOD = _read_env("IDL_DINSAR_CUSTOM_FILTER_METHOD", "GOLDSTEIN")
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||
CUSTOM_UNWRAP_COH_THRESHOLD = float(
|
||
_read_env("IDL_DINSAR_CUSTOM_UNWRAP_COH_THRESHOLD", "0.05") or 0.05
|
||
)
|
||
CUSTOM_GCP_COH_THRESHOLD = float(
|
||
_read_env("IDL_DINSAR_CUSTOM_GCP_COH_THRESHOLD", "0.7") or 0.7
|
||
)
|
||
CUSTOM_GCP_NUMBER = int(
|
||
_read_env("IDL_DINSAR_CUSTOM_GCP_NUMBER", "100") or 100
|
||
)
|
||
CUSTOM_GEOCODING_COH_THRESHOLD = float(
|
||
_read_env("IDL_DINSAR_CUSTOM_GEOCODING_COH_THRESHOLD", "0.0") or 0.0
|
||
)
|
||
CUSTOM_GEOCODING_PIXEL_SIZE_M = float(
|
||
_read_env("IDL_DINSAR_CUSTOM_GEOCODING_PIXEL_SIZE_M", "10.0") or 10.0
|
||
)
|
||
|
||
# Timeout for individual envipyengine task.execute() calls (seconds).
|
||
# If envipyengine hangs after the task completes, this ensures we don't
|
||
# block forever. The caller's except block will use fallback file scanning.
|
||
_ENVI_TASK_TIMEOUT = int(_read_env("ENVI_TASK_TIMEOUT_SECONDS", "300") or 300)
|
||
|
||
# Global mutex: taskengine.exe is a singleton process and cannot handle
|
||
# concurrent calls. All execute_envi_task() calls must be serialized.
|
||
import threading
|
||
_ENVI_GLOBAL_LOCK = threading.Lock()
|
||
|
||
|
||
SARSCAPE_SBAS_NATIVE_WORKFLOW_CANDIDATES = [
|
||
"wf_sbas",
|
||
"wf_esbas",
|
||
]
|
||
|
||
SARSCAPE_SBAS_SUPPORT_TASK_CANDIDATES = [
|
||
"SARscape_setting_output_folders",
|
||
"SARsLoadPreferences",
|
||
"SARsImportSarSelector",
|
||
"SARscapeSuggestLooks",
|
||
"SARscapeEnviuriToShape",
|
||
]
|
||
|
||
SARSCAPE_SBAS_STACK_TASK_CANDIDATES = [
|
||
"SARsInSARStackSBASGenerateConnectionGraph",
|
||
"SARsInSARStackSBASInterferogramGeneration",
|
||
"SARsInSARStackSBASInversionStep1",
|
||
"SARsInSARStackSBASInversionStep2",
|
||
"SARsInSARStackSBASGeocode",
|
||
"SARsInSARStackSBASVariogram",
|
||
"SARsInSARStackESBASInterferogramGeneration",
|
||
"SARsInSARStackESBASInversion",
|
||
"SARsInSARStackESBASGeocode",
|
||
"SARsInSARConnectionGraphESBAS",
|
||
]
|
||
|
||
SARSCAPE_SBAS_TASK_CANDIDATES = [
|
||
*SARSCAPE_SBAS_NATIVE_WORKFLOW_CANDIDATES,
|
||
*SARSCAPE_SBAS_SUPPORT_TASK_CANDIDATES,
|
||
*SARSCAPE_SBAS_STACK_TASK_CANDIDATES,
|
||
]
|
||
|
||
|
||
# ---------------------------------------------------------------------------
|
||
# Progress file for subprocess ↔ job handler communication
|
||
# ---------------------------------------------------------------------------
|
||
|
||
def _progress_file_path(job_id: str) -> str:
|
||
"""Return the path to the progress JSON file for a given job."""
|
||
return os.path.join(RUNTIME_DIR, f"job_{job_id}_progress.json")
|
||
|
||
|
||
def _write_progress(
|
||
job_id: Optional[str],
|
||
step: int,
|
||
total_steps: int,
|
||
message: str,
|
||
output_dir: str = "",
|
||
pair_index: int = 0,
|
||
total_pairs: int = 0,
|
||
pair_name: str = "",
|
||
) -> None:
|
||
"""Write a progress JSON file (atomic via tmp+rename).
|
||
|
||
The job handler monitors this file's mtime to determine liveness.
|
||
pair_index/total_pairs track which pair is being processed in a batch.
|
||
"""
|
||
if not job_id:
|
||
return
|
||
try:
|
||
os.makedirs(RUNTIME_DIR, exist_ok=True)
|
||
progress_file = _progress_file_path(job_id)
|
||
data = {
|
||
"step": step,
|
||
"total_steps": total_steps,
|
||
"message": message,
|
||
"output_dir": output_dir,
|
||
"pair_index": pair_index,
|
||
"total_pairs": total_pairs,
|
||
"pair_name": pair_name,
|
||
"timestamp": time.time(),
|
||
}
|
||
tmp = progress_file + ".tmp"
|
||
with open(tmp, "w", encoding="utf-8") as f:
|
||
json.dump(data, f)
|
||
os.replace(tmp, progress_file)
|
||
except Exception as exc:
|
||
print(f"[WARN] _write_progress: {exc}")
|
||
|
||
|
||
# ---------------------------------------------------------------------------
|
||
# Directory scanning
|
||
# ---------------------------------------------------------------------------
|
||
|
||
def _collect_task_folders(root_dir: str) -> List[str]:
|
||
"""Return sorted list of Task_* directories under root_dir."""
|
||
pattern = os.path.join(root_dir, "Task_*")
|
||
return sorted(p for p in glob(pattern) if os.path.isdir(p))
|
||
|
||
|
||
def _find_meta_files(data_dir: str) -> List[str]:
|
||
return sorted(glob(os.path.join(data_dir, "*.meta.xml")))
|
||
|
||
|
||
def _has_sml(data_dir: str) -> bool:
|
||
return bool(glob(os.path.join(data_dir, "*.sml")))
|
||
|
||
|
||
def _first_sml_base(data_dir: str) -> Optional[str]:
|
||
"""Return base path (without .sml) of the first .sml file, or None."""
|
||
smls = sorted(glob(os.path.join(data_dir, "*.sml")))
|
||
return smls[0][:-4] if smls else None
|
||
|
||
|
||
def _utc_now_text() -> str:
|
||
return datetime.utcnow().isoformat(timespec="seconds") + "Z"
|
||
|
||
|
||
def _resolve_dinsar_pair_identity(task_dir: str, task_name: str) -> tuple[str, str, Dict[str, Any]]:
|
||
pair_meta = find_json_sidecar(task_dir, PAIR_META_FILENAME, max_levels=0) or {}
|
||
task_alias = str(pair_meta.get("task_alias") or task_name).strip() or task_name
|
||
pair_key = str(pair_meta.get("pair_key") or "").strip() or build_fallback_pair_key(task_alias, task_dir)
|
||
return task_alias, pair_key, pair_meta
|
||
|
||
|
||
def _write_envi_run_sidecar(
|
||
output_dir: str,
|
||
*,
|
||
engine_code: str,
|
||
profile_code: str,
|
||
root_dir: str,
|
||
task_dir: str,
|
||
task_name: str,
|
||
task_alias: str,
|
||
pair_key: str,
|
||
run_key: str,
|
||
pair_meta: Dict[str, Any],
|
||
started_at: str,
|
||
params: Dict[str, Any],
|
||
metrics: Dict[str, Any],
|
||
native_output_dir: Optional[str] = None,
|
||
) -> None:
|
||
write_run_metadata(
|
||
output_dir,
|
||
{
|
||
"run_key": run_key,
|
||
"pair_key": pair_key,
|
||
"task_name": task_name,
|
||
"task_alias": task_alias,
|
||
"engine_code": engine_code,
|
||
"profile_code": profile_code,
|
||
"source_root": os.path.normpath(root_dir),
|
||
"task_dir": os.path.normpath(task_dir),
|
||
"output_dir": os.path.normpath(output_dir),
|
||
"native_output_dir": os.path.normpath(native_output_dir or output_dir),
|
||
"started_at": started_at,
|
||
"finished_at": _utc_now_text(),
|
||
"params": params,
|
||
"metrics": metrics,
|
||
"master_path": pair_meta.get("master_path"),
|
||
"slave_path": pair_meta.get("slave_path"),
|
||
"master_satellite": pair_meta.get("master_satellite"),
|
||
"slave_satellite": pair_meta.get("slave_satellite"),
|
||
"master_imaging_date": pair_meta.get("master_imaging_date"),
|
||
"slave_imaging_date": pair_meta.get("slave_imaging_date"),
|
||
"master_imaging_mode": pair_meta.get("master_imaging_mode"),
|
||
"slave_imaging_mode": pair_meta.get("slave_imaging_mode"),
|
||
"master_polarization": pair_meta.get("master_polarization"),
|
||
"slave_polarization": pair_meta.get("slave_polarization"),
|
||
"time_baseline_days": pair_meta.get("time_baseline_days"),
|
||
"spatial_baseline_meters": pair_meta.get("spatial_baseline_meters"),
|
||
"scene_pair_uid": pair_meta.get("scene_pair_uid") or pair_meta.get("pair_uid"),
|
||
"pair_uid": pair_meta.get("pair_uid") or pair_meta.get("scene_pair_uid"),
|
||
"network_run_id": pair_meta.get("network_run_id"),
|
||
"network_edge_id": pair_meta.get("network_edge_id"),
|
||
"policy_version": pair_meta.get("policy_version"),
|
||
"selection_strategy": pair_meta.get("selection_strategy"),
|
||
},
|
||
)
|
||
|
||
|
||
def _build_sarscapedata(base_path: str) -> Dict[str, Any]:
|
||
"""Build a SARSCAPEDATA hash from a base path (without extension).
|
||
|
||
envipyengine/taskengine expects SARSCAPEDATA parameters as a Hash:
|
||
{"url": "...", "factory": "ENVISARscapedata", "auxiliary_url": [...]}
|
||
Passing a plain string causes hydration failure.
|
||
"""
|
||
normalized = _normalize_path(base_path)
|
||
return {
|
||
"url": normalized,
|
||
"factory": "ENVISARscapedata",
|
||
"auxiliary_url": [
|
||
normalized + ".sml",
|
||
normalized + ".hdr",
|
||
],
|
||
}
|
||
|
||
|
||
# ---------------------------------------------------------------------------
|
||
# Core: execute a single ENVI task via envipyengine
|
||
# ---------------------------------------------------------------------------
|
||
|
||
def execute_envi_task(task_name: str, parameters: Dict[str, Any]) -> Dict[str, Any]:
|
||
"""Call envipyengine to execute one ENVI/SARscape task.
|
||
|
||
Returns the outputParameters dict from the task result so callers
|
||
can directly access output SARSCAPEDATA by parameter name.
|
||
Raises RuntimeError on timeout (envipyengine hang).
|
||
|
||
NOTE: taskengine.exe is a singleton — calls are serialized via _ENVI_GLOBAL_LOCK.
|
||
"""
|
||
try:
|
||
_ensure_envipyengine_config()
|
||
from envipyengine import Engine
|
||
except ImportError as exc:
|
||
raise RuntimeError(
|
||
"envipyengine is not installed. "
|
||
"Install it with: pip install envipyengine"
|
||
) from exc
|
||
|
||
with _ENVI_GLOBAL_LOCK:
|
||
with _envi_taskengine_runtime_context():
|
||
engine = Engine("ENVI")
|
||
task = engine.task(task_name)
|
||
existing_taskengine_pids = _list_taskengine_pids()
|
||
|
||
# Run with timeout to handle envipyengine hangs
|
||
with ThreadPoolExecutor(max_workers=1) as pool:
|
||
future = pool.submit(task.execute, parameters)
|
||
try:
|
||
result = future.result(timeout=_ENVI_TASK_TIMEOUT)
|
||
except FuturesTimeoutError:
|
||
try:
|
||
cleanup = _cleanup_new_taskengine_processes(existing_taskengine_pids)
|
||
stopped = cleanup.get("taskengine_stopped_pids") or []
|
||
remaining = cleanup.get("taskengine_remaining_new_pids") or []
|
||
print(
|
||
"[WARN] execute_envi_task: task timed out; "
|
||
f"stopped_new_taskengine_pids={stopped}; "
|
||
f"remaining_new_taskengine_pids={remaining}"
|
||
)
|
||
except Exception as _exc:
|
||
print(f"[WARN] execute_envi_task: taskengine cleanup failed — {_exc}")
|
||
raise RuntimeError(
|
||
f"Task {task_name} timed out after {_ENVI_TASK_TIMEOUT}s "
|
||
f"(envipyengine hung). Output files may still exist."
|
||
)
|
||
|
||
# taskengine returns {"outputParameters": {...}, ...}
|
||
return result.get("outputParameters", result)
|
||
|
||
|
||
def _unwrap_sarscapedata(value: Any) -> Any:
|
||
"""Unwrap SARSCAPEDATA output from envipyengine.
|
||
|
||
taskengine returns output SARSCAPEDATA as a list: [{url, factory, ...}].
|
||
Input parameters expect a plain dict: {url, factory, ...}.
|
||
"""
|
||
if isinstance(value, list) and len(value) == 1 and isinstance(value[0], dict):
|
||
return value[0]
|
||
return value
|
||
|
||
|
||
def _configured_sarscape_sbas_task_candidates() -> List[str]:
|
||
configured = str(_read_env("SARSCAPE_SBAS_TASK_NAMES", "") or "").strip()
|
||
if not configured:
|
||
return list(SARSCAPE_SBAS_TASK_CANDIDATES)
|
||
names: List[str] = []
|
||
for raw in configured.replace(";", ",").split(","):
|
||
name = raw.strip()
|
||
if name and name not in names:
|
||
names.append(name)
|
||
return names or list(SARSCAPE_SBAS_TASK_CANDIDATES)
|
||
|
||
|
||
def _envi_install_root() -> str:
|
||
executable = _to_local_path(IDL_EXECUTABLE)
|
||
if not executable:
|
||
return ""
|
||
return os.path.abspath(os.path.join(os.path.dirname(executable), "..", "..", ".."))
|
||
|
||
|
||
def _static_envi_task_template_path(task_name: str) -> str:
|
||
name = str(task_name or "").strip()
|
||
if not name:
|
||
return ""
|
||
envi_root = _envi_install_root()
|
||
if not envi_root:
|
||
return ""
|
||
candidates = [
|
||
os.path.join(envi_root, "user_custom_code", f"{name}.task"),
|
||
os.path.join(envi_root, "resource", "templates", "tasks", "SARscape", f"{name}.task"),
|
||
os.path.join(envi_root, "resource", "templates", "tasks", f"{name}.task"),
|
||
]
|
||
for path in candidates:
|
||
if os.path.isfile(path):
|
||
return path
|
||
return ""
|
||
|
||
|
||
def _json_safe_parameter(value: Any) -> Any:
|
||
if isinstance(value, dict):
|
||
return {str(key): _json_safe_parameter(item) for key, item in value.items()}
|
||
if isinstance(value, (list, tuple)):
|
||
return [_json_safe_parameter(item) for item in value]
|
||
if value is None or isinstance(value, (str, int, float, bool)):
|
||
return value
|
||
return str(value)
|
||
|
||
|
||
def _summarize_task_parameters(raw_parameters: Any) -> Dict[str, Any]:
|
||
safe_parameters = _json_safe_parameter(raw_parameters)
|
||
input_names: List[str] = []
|
||
output_names: List[str] = []
|
||
required_input_names: List[str] = []
|
||
|
||
if isinstance(safe_parameters, dict):
|
||
iterable = safe_parameters.values()
|
||
elif isinstance(safe_parameters, list):
|
||
iterable = safe_parameters
|
||
else:
|
||
iterable = []
|
||
|
||
for item in iterable:
|
||
if not isinstance(item, dict):
|
||
continue
|
||
name = str(item.get("name") or item.get("NAME") or "").strip()
|
||
direction = str(item.get("direction") or item.get("DIRECTION") or "").strip().lower()
|
||
required = bool(item.get("required") or item.get("REQUIRED"))
|
||
if not name:
|
||
continue
|
||
if direction == "input":
|
||
input_names.append(name)
|
||
if required:
|
||
required_input_names.append(name)
|
||
elif direction == "output":
|
||
output_names.append(name)
|
||
|
||
return {
|
||
"parameter_count": (
|
||
len(safe_parameters)
|
||
if isinstance(safe_parameters, (dict, list))
|
||
else 0
|
||
),
|
||
"input_names": input_names,
|
||
"required_input_names": required_input_names,
|
||
"output_names": output_names,
|
||
"parameters": safe_parameters,
|
||
}
|
||
|
||
|
||
def list_envi_tasks() -> Dict[str, Any]:
|
||
"""List ENVI task names without instantiating individual task parameters."""
|
||
result: Dict[str, Any] = {
|
||
"ok": False,
|
||
"engine": "envipyengine",
|
||
"task_count": 0,
|
||
"tasks": [],
|
||
"error": None,
|
||
}
|
||
try:
|
||
_ensure_envipyengine_config()
|
||
from envipyengine import Engine
|
||
except ImportError:
|
||
result["error"] = (
|
||
"envipyengine is not installed. Install it with: pip install envipyengine"
|
||
)
|
||
return result
|
||
|
||
with _ENVI_GLOBAL_LOCK:
|
||
with _envi_taskengine_runtime_context():
|
||
try:
|
||
names = Engine("ENVI").tasks()
|
||
except Exception as exc:
|
||
result["error"] = str(exc)
|
||
return result
|
||
|
||
result["tasks"] = [str(name) for name in names]
|
||
result["task_count"] = len(result["tasks"])
|
||
result["ok"] = True
|
||
return result
|
||
|
||
|
||
def discover_sarscape_sbas_tasks() -> Dict[str, Any]:
|
||
"""Discover installed SARscape SBAS/E-SBAS task names by filtering Engine.tasks()."""
|
||
report = list_envi_tasks()
|
||
task_names = list(report.get("tasks") or [])
|
||
keywords = (
|
||
"StackSBAS",
|
||
"StackESBAS",
|
||
"ConnectionGraphESBAS",
|
||
)
|
||
explicit_names = set(SARSCAPE_SBAS_NATIVE_WORKFLOW_CANDIDATES) | set(SARSCAPE_SBAS_SUPPORT_TASK_CANDIDATES)
|
||
matches = [
|
||
name
|
||
for name in task_names
|
||
if (
|
||
str(name) in explicit_names
|
||
or (
|
||
str(name).startswith("SARsInSAR")
|
||
and any(keyword.lower() in str(name).lower() for keyword in keywords)
|
||
)
|
||
)
|
||
]
|
||
static_task_files: Dict[str, str] = {}
|
||
for name in SARSCAPE_SBAS_TASK_CANDIDATES:
|
||
path = _static_envi_task_template_path(name)
|
||
if path:
|
||
static_task_files[name] = path
|
||
if name not in matches:
|
||
matches.append(name)
|
||
preferred_order = [
|
||
*SARSCAPE_SBAS_NATIVE_WORKFLOW_CANDIDATES,
|
||
*SARSCAPE_SBAS_SUPPORT_TASK_CANDIDATES,
|
||
"SARsInSARStackSBASGenerateConnectionGraph",
|
||
"SARsInSARStackSBASInterferogramGeneration",
|
||
"SARsInSARStackSBASInversionStep1",
|
||
"SARsInSARStackSBASInversionStep2",
|
||
"SARsInSARStackSBASGeocode",
|
||
"SARsInSARStackSBASVariogram",
|
||
"SARsInSARStackESBASInterferogramGeneration",
|
||
"SARsInSARStackESBASInversion",
|
||
"SARsInSARStackESBASGeocode",
|
||
"SARsInSARConnectionGraphESBAS",
|
||
]
|
||
ordered: List[str] = []
|
||
for name in preferred_order:
|
||
if name in matches and name not in ordered:
|
||
ordered.append(name)
|
||
for name in sorted(matches):
|
||
if name not in ordered:
|
||
ordered.append(name)
|
||
|
||
return {
|
||
"ok": bool(report.get("ok")) and bool(ordered),
|
||
"engine": report.get("engine"),
|
||
"task_count": int(report.get("task_count") or 0),
|
||
"sarscape_sbas_task_count": len(ordered),
|
||
"sarscape_sbas_tasks": ordered,
|
||
"static_task_files": {
|
||
name: static_task_files[name]
|
||
for name in ordered
|
||
if name in static_task_files
|
||
},
|
||
"error": report.get("error"),
|
||
}
|
||
|
||
|
||
def inspect_envi_tasks(task_names: List[str]) -> Dict[str, Any]:
|
||
"""Inspect ENVI/SARscape tasks without executing them."""
|
||
started_at = _utc_now_text()
|
||
deduped_names: List[str] = []
|
||
for raw_name in task_names:
|
||
name = str(raw_name or "").strip()
|
||
if name and name not in deduped_names:
|
||
deduped_names.append(name)
|
||
|
||
result: Dict[str, Any] = {
|
||
"ok": False,
|
||
"engine": "envipyengine",
|
||
"started_at": started_at,
|
||
"finished_at": None,
|
||
"task_count": len(deduped_names),
|
||
"available_count": 0,
|
||
"missing_count": 0,
|
||
"tasks": [],
|
||
"error": None,
|
||
}
|
||
if not deduped_names:
|
||
result["error"] = "No task names provided."
|
||
result["finished_at"] = _utc_now_text()
|
||
return result
|
||
|
||
try:
|
||
_ensure_envipyengine_config()
|
||
from envipyengine import Engine
|
||
except ImportError as exc:
|
||
result["error"] = (
|
||
"envipyengine is not installed. Install it with: pip install envipyengine"
|
||
)
|
||
result["finished_at"] = _utc_now_text()
|
||
return result
|
||
|
||
with _ENVI_GLOBAL_LOCK:
|
||
with _envi_taskengine_runtime_context():
|
||
try:
|
||
engine = Engine("ENVI")
|
||
except Exception as exc:
|
||
result["error"] = f"Failed to initialize ENVI engine: {exc}"
|
||
result["finished_at"] = _utc_now_text()
|
||
return result
|
||
|
||
for task_name in deduped_names:
|
||
item: Dict[str, Any] = {
|
||
"name": task_name,
|
||
"available": False,
|
||
"error": None,
|
||
"parameter_count": 0,
|
||
"input_names": [],
|
||
"required_input_names": [],
|
||
"output_names": [],
|
||
"parameters": [],
|
||
}
|
||
try:
|
||
task = engine.task(task_name)
|
||
summary = _summarize_task_parameters(getattr(task, "parameters", []))
|
||
item.update(summary)
|
||
item["available"] = True
|
||
except Exception as exc:
|
||
item["error"] = str(exc)
|
||
result["tasks"].append(item)
|
||
|
||
result["available_count"] = sum(1 for item in result["tasks"] if item.get("available"))
|
||
result["missing_count"] = sum(1 for item in result["tasks"] if not item.get("available"))
|
||
result["ok"] = result["available_count"] > 0
|
||
result["finished_at"] = _utc_now_text()
|
||
return result
|
||
|
||
|
||
def inspect_sarscape_sbas_tasks(
|
||
task_names: Optional[List[str]] = None,
|
||
*,
|
||
include_parameters: bool = False,
|
||
) -> Dict[str, Any]:
|
||
"""Inspect likely SARscape SBAS/E-SBAS task names for the installed version."""
|
||
status = get_status()
|
||
discovery = discover_sarscape_sbas_tasks()
|
||
names = task_names or list(discovery.get("sarscape_sbas_tasks") or _configured_sarscape_sbas_task_candidates())
|
||
if include_parameters:
|
||
task_report = inspect_envi_tasks(names)
|
||
else:
|
||
discovered_set = set(discovery.get("sarscape_sbas_tasks") or [])
|
||
task_report = {
|
||
"ok": bool(discovery.get("ok")),
|
||
"engine": "envipyengine",
|
||
"task_count": len(names),
|
||
"available_count": sum(1 for name in names if name in discovered_set),
|
||
"missing_count": sum(1 for name in names if name not in discovered_set),
|
||
"tasks": [
|
||
{
|
||
"name": name,
|
||
"available": name in discovered_set,
|
||
"error": None if name in discovered_set else "Task name not listed by Engine.tasks().",
|
||
"parameter_count": None,
|
||
"input_names": [],
|
||
"required_input_names": [],
|
||
"output_names": [],
|
||
"parameters": [],
|
||
}
|
||
for name in names
|
||
],
|
||
"error": discovery.get("error"),
|
||
}
|
||
task_report["status"] = {
|
||
"idl_installed": status.get("idl_installed"),
|
||
"idl_executable": status.get("idl_executable"),
|
||
"runner_ready": status.get("runner_ready"),
|
||
"runner_python": status.get("runner_python"),
|
||
"runner_message": status.get("runner_message"),
|
||
"dem_base_file": status.get("dem_base_file"),
|
||
"dem_exists": status.get("dem_exists"),
|
||
}
|
||
task_report["candidate_source"] = (
|
||
"SARSCAPE_SBAS_TASK_NAMES"
|
||
if str(_read_env("SARSCAPE_SBAS_TASK_NAMES", "") or "").strip()
|
||
else "engine_task_list"
|
||
)
|
||
task_report["include_parameters"] = bool(include_parameters)
|
||
task_report["discovery"] = discovery
|
||
task_report["ready_for_pipeline_design"] = bool(task_report.get("ok"))
|
||
return task_report
|
||
|
||
|
||
def inspect_sarscape_sbas_tasks_subprocess(
|
||
task_names: Optional[List[str]] = None,
|
||
*,
|
||
timeout_seconds: int = 120,
|
||
include_parameters: bool = False,
|
||
) -> Dict[str, Any]:
|
||
"""Run SARscape SBAS task inspection through the isolated ENVI runner."""
|
||
command = build_envi_runner_command("--inspect-sarscape-sbas")
|
||
if include_parameters:
|
||
command.append("--include-parameters")
|
||
for name in task_names or []:
|
||
if str(name or "").strip():
|
||
command.extend(["--task-name", str(name).strip()])
|
||
existing_taskengine_pids = _list_taskengine_pids()
|
||
try:
|
||
completed = subprocess.run(
|
||
command,
|
||
cwd=get_envi_runner_cwd(),
|
||
env=get_envi_runner_env(),
|
||
capture_output=True,
|
||
text=True,
|
||
timeout=max(10, int(timeout_seconds or 120)),
|
||
check=False,
|
||
)
|
||
except subprocess.TimeoutExpired as exc:
|
||
cleanup = _cleanup_new_taskengine_processes(existing_taskengine_pids)
|
||
stdout_text = str(exc.stdout or "").strip()
|
||
stderr_text = str(exc.stderr or "").strip()
|
||
return {
|
||
"ok": False,
|
||
"returncode": None,
|
||
"timeout": True,
|
||
"timeout_seconds": max(10, int(timeout_seconds or 120)),
|
||
"stdout": stdout_text[:2000],
|
||
"stderr": stderr_text[:2000],
|
||
"error": (
|
||
"SARscape SBAS task inspection timed out. "
|
||
"Use lightweight discovery without include_parameters, or provide a manually verified task template."
|
||
),
|
||
"runner_command": command,
|
||
**cleanup,
|
||
}
|
||
stdout_text = str(completed.stdout or "").strip()
|
||
stderr_text = str(completed.stderr or "").strip()
|
||
try:
|
||
payload = json.loads(stdout_text) if stdout_text else {}
|
||
except Exception:
|
||
payload = {}
|
||
payload.setdefault("returncode", int(completed.returncode))
|
||
payload.setdefault("stdout", stdout_text[:2000])
|
||
payload.setdefault("stderr", stderr_text[:2000])
|
||
payload["runner_command"] = command
|
||
if completed.returncode != 0:
|
||
payload["ok"] = False
|
||
payload.setdefault("error", stderr_text or stdout_text or f"returncode={completed.returncode}")
|
||
return payload
|
||
|
||
|
||
# ---------------------------------------------------------------------------
|
||
# Import workflow
|
||
# ---------------------------------------------------------------------------
|
||
|
||
def _import_single_dir(
|
||
display_name: str,
|
||
data_dir: str,
|
||
log_lines: List[str],
|
||
) -> tuple:
|
||
"""Import all .meta.xml in one directory. Returns (processed, failed, skipped)."""
|
||
if _has_sml(data_dir):
|
||
log_lines.append(f"[skip] {display_name}: .sml already exists")
|
||
return 0, 0, 1
|
||
|
||
meta_files = _find_meta_files(data_dir)
|
||
if not meta_files:
|
||
log_lines.append(f"[skip] {display_name}: no *.meta.xml")
|
||
return 0, 0, 0
|
||
|
||
processed = 0
|
||
failed = 0
|
||
for meta_file in meta_files:
|
||
start = time.time()
|
||
try:
|
||
execute_envi_task(
|
||
"SARsImportLuTan1",
|
||
{
|
||
"INPUT_FILE_LIST": [meta_file],
|
||
"ROOT_URI_FOR_OUTPUT": data_dir,
|
||
},
|
||
)
|
||
elapsed = round(time.time() - start, 1)
|
||
processed += 1
|
||
log_lines.append(
|
||
f"[ok] import {display_name}: "
|
||
f"{os.path.basename(meta_file)} ({elapsed}s)"
|
||
)
|
||
except Exception as exc:
|
||
elapsed = round(time.time() - start, 1)
|
||
failed += 1
|
||
log_lines.append(
|
||
f"[err] import {display_name}: "
|
||
f"{os.path.basename(meta_file)} failed ({elapsed}s): {exc}"
|
||
)
|
||
return processed, failed, 0
|
||
|
||
|
||
def run_import_workflow(
|
||
root_dir: str,
|
||
num_to_process: int = 0,
|
||
timeout: int = DEFAULT_TIMEOUT,
|
||
) -> Dict[str, Any]:
|
||
"""Scan root_dir for raw SAR data and batch-import via SARsImportLuTan1.
|
||
|
||
Supports two layouts:
|
||
- Task_* folders with master/slave subdirs
|
||
- Flat folders containing .meta.xml directly
|
||
"""
|
||
root_dir = _to_local_path(root_dir)
|
||
if not root_dir or not os.path.isdir(root_dir):
|
||
raise ValueError(f"Import root directory does not exist: {root_dir}")
|
||
|
||
task_folders = _collect_task_folders(root_dir)
|
||
scan_mode = "task_folder"
|
||
if not task_folders:
|
||
task_folders = sorted(
|
||
p for p in glob(os.path.join(root_dir, "*")) if os.path.isdir(p)
|
||
)
|
||
scan_mode = "flat_folder"
|
||
|
||
log_lines: List[str] = [
|
||
f"[envi] import task=SARsImportLuTan1",
|
||
f"[envi] root_dir={root_dir}",
|
||
f"[envi] scan_mode={scan_mode}",
|
||
f"[envi] found folders={len(task_folders)}",
|
||
]
|
||
if not task_folders:
|
||
return {
|
||
"summary": {
|
||
"scan_mode": scan_mode,
|
||
"task_folders": 0,
|
||
"processed": 0,
|
||
"failed": 0,
|
||
"skipped": 0,
|
||
},
|
||
"log_lines": log_lines,
|
||
}
|
||
|
||
total_processed = 0
|
||
total_failed = 0
|
||
total_skipped = 0
|
||
|
||
for folder in task_folders:
|
||
if num_to_process > 0 and total_processed >= num_to_process:
|
||
log_lines.append(f"[envi] reached limit={num_to_process}")
|
||
break
|
||
name = os.path.basename(folder)
|
||
|
||
if scan_mode == "flat_folder":
|
||
candidates = [(name, folder)]
|
||
else:
|
||
candidates = []
|
||
for side in ("master", "slave"):
|
||
d = os.path.join(folder, side)
|
||
if os.path.isdir(d):
|
||
candidates.append((f"{name}/{side}", d))
|
||
else:
|
||
log_lines.append(f"[warn] {name}/{side} missing, skip")
|
||
|
||
for display, data_dir in candidates:
|
||
if num_to_process > 0 and total_processed >= num_to_process:
|
||
break
|
||
p, f, s = _import_single_dir(display, data_dir, log_lines)
|
||
total_processed += p
|
||
total_failed += f
|
||
total_skipped += s
|
||
|
||
if total_failed > 0 and total_processed == 0:
|
||
detail = "\n".join(log_lines[-20:])
|
||
raise RuntimeError(
|
||
f"All import tasks failed. failed={total_failed}.\n{detail}"
|
||
)
|
||
|
||
return {
|
||
"summary": {
|
||
"scan_mode": scan_mode,
|
||
"task_folders": len(task_folders),
|
||
"processed": total_processed,
|
||
"failed": total_failed,
|
||
"skipped": total_skipped,
|
||
},
|
||
"log_lines": log_lines,
|
||
}
|
||
|
||
|
||
# ---------------------------------------------------------------------------
|
||
# D-InSAR workflow (with smart chaining: auto-import if needed)
|
||
# ---------------------------------------------------------------------------
|
||
|
||
def run_dinsar_workflow(
|
||
root_dir: str,
|
||
num_to_process: int = 0,
|
||
timeout: int = DEFAULT_TIMEOUT,
|
||
timeout_seconds: Optional[int] = None,
|
||
job_id: Optional[str] = None,
|
||
run_key: Optional[str] = None,
|
||
profile_code: str = "metatask",
|
||
started_at: Optional[datetime] = None,
|
||
) -> Dict[str, Any]:
|
||
"""Run D-InSAR metatask on Task_* folders.
|
||
|
||
Smart chaining: for each Task_* folder, if master/slave lack .sml files,
|
||
automatically run Import first, then proceed with D-InSAR.
|
||
DEM path is read from .env (IDL_DINSAR_DEM_BASE_FILE).
|
||
"""
|
||
timeout = min(timeout_seconds or timeout or DEFAULT_TIMEOUT, MAX_TIMEOUT)
|
||
root_dir = _to_local_path(root_dir)
|
||
run_started_at = started_at or datetime.utcnow()
|
||
run_started_at_text = run_started_at.isoformat(timespec="seconds") + "Z"
|
||
resolved_run_key = run_key or build_run_key("sarscape", profile_code, started_at=run_started_at)
|
||
dem_base_file = DEM_BASE_FILE
|
||
if not root_dir or not os.path.isdir(root_dir):
|
||
raise ValueError(f"D-InSAR root directory does not exist: {root_dir}")
|
||
if not dem_base_file:
|
||
raise ValueError(
|
||
"DEM path not configured. Set IDL_DINSAR_DEM_BASE_FILE in .env"
|
||
)
|
||
|
||
task_folders = _collect_task_folders(root_dir)
|
||
log_lines: List[str] = [
|
||
f"[envi] dinsar metatask",
|
||
f"[envi] root_dir={root_dir}",
|
||
f"[envi] dem={dem_base_file}",
|
||
f"[envi] Task_* folders={len(task_folders)}",
|
||
]
|
||
if not task_folders:
|
||
return {
|
||
"summary": {
|
||
"task_folders": 0,
|
||
"processed": 0,
|
||
"failed": 0,
|
||
"skipped": 0,
|
||
"auto_imported": 0,
|
||
},
|
||
"log_lines": log_lines,
|
||
"task_results": [],
|
||
"output_dirs": [],
|
||
"run_key": resolved_run_key,
|
||
"profile_code": profile_code,
|
||
}
|
||
|
||
processed = 0
|
||
failed = 0
|
||
skipped = 0
|
||
auto_imported = 0
|
||
task_results: List[Dict[str, Any]] = []
|
||
output_dirs: List[str] = []
|
||
|
||
for folder in task_folders:
|
||
if num_to_process > 0 and processed >= num_to_process:
|
||
log_lines.append(f"[envi] reached limit={num_to_process}")
|
||
break
|
||
task_name = os.path.basename(folder)
|
||
task_alias, pair_key, pair_meta = _resolve_dinsar_pair_identity(folder, task_name)
|
||
master_dir = os.path.join(folder, "master")
|
||
slave_dir = os.path.join(folder, "slave")
|
||
|
||
if not os.path.isdir(master_dir) or not os.path.isdir(slave_dir):
|
||
skipped += 1
|
||
log_lines.append(f"[skip] {task_name}: master/slave dir missing")
|
||
task_results.append(
|
||
{
|
||
"task_name": task_name,
|
||
"task_alias": task_alias,
|
||
"pair_key": pair_key,
|
||
"run_key": resolved_run_key,
|
||
"task_dir": folder,
|
||
"success": False,
|
||
"status": "skipped",
|
||
"error": "master/slave dir missing",
|
||
}
|
||
)
|
||
continue
|
||
|
||
# --- Smart chaining: auto-import if .sml missing ---
|
||
for side, side_dir in [("master", master_dir), ("slave", slave_dir)]:
|
||
if not _has_sml(side_dir):
|
||
meta_files = _find_meta_files(side_dir)
|
||
if not meta_files:
|
||
log_lines.append(
|
||
f"[warn] {task_name}/{side}: no .sml and no .meta.xml"
|
||
)
|
||
continue
|
||
log_lines.append(
|
||
f"[auto-import] {task_name}/{side}: "
|
||
f"importing {len(meta_files)} file(s)"
|
||
)
|
||
for mf in meta_files:
|
||
start = time.time()
|
||
try:
|
||
execute_envi_task(
|
||
"SARsImportLuTan1",
|
||
{
|
||
"INPUT_FILE_LIST": [mf],
|
||
"ROOT_URI_FOR_OUTPUT": side_dir,
|
||
},
|
||
)
|
||
elapsed = round(time.time() - start, 1)
|
||
auto_imported += 1
|
||
log_lines.append(
|
||
f"[auto-import ok] {task_name}/{side}: "
|
||
f"{os.path.basename(mf)} ({elapsed}s)"
|
||
)
|
||
except Exception as exc:
|
||
elapsed = round(time.time() - start, 1)
|
||
log_lines.append(
|
||
f"[auto-import err] {task_name}/{side}: "
|
||
f"{os.path.basename(mf)} ({elapsed}s): {exc}"
|
||
)
|
||
|
||
# After auto-import, check .sml again
|
||
master_base = _first_sml_base(master_dir)
|
||
slave_base = _first_sml_base(slave_dir)
|
||
if not master_base or not slave_base:
|
||
skipped += 1
|
||
log_lines.append(
|
||
f"[skip] {task_name}: still missing .sml after import "
|
||
f"(master={'yes' if master_base else 'no'} "
|
||
f"slave={'yes' if slave_base else 'no'})"
|
||
)
|
||
task_results.append(
|
||
{
|
||
"task_name": task_name,
|
||
"task_alias": task_alias,
|
||
"pair_key": pair_key,
|
||
"run_key": resolved_run_key,
|
||
"task_dir": folder,
|
||
"success": False,
|
||
"status": "skipped",
|
||
"error": "missing .sml after import",
|
||
}
|
||
)
|
||
continue
|
||
|
||
output_dir = os.path.join(folder, "dinsar_results")
|
||
os.makedirs(output_dir, exist_ok=True)
|
||
|
||
start = time.time()
|
||
try:
|
||
execute_envi_task(
|
||
"SARsMetataskInSARDisplacementGeneration",
|
||
{
|
||
"REFERENCE_SARSCAPEDATA": _build_sarscapedata(master_base),
|
||
"SECONDARY_SARSCAPEDATA": _build_sarscapedata(slave_base),
|
||
"DEM_SARSCAPEDATA": _build_sarscapedata(dem_base_file),
|
||
"OUTPUT_FOLDER": _normalize_path(output_dir),
|
||
},
|
||
)
|
||
elapsed = round(time.time() - start, 1)
|
||
processed += 1
|
||
log_lines.append(f"[ok] dinsar {task_name} ({elapsed}s)")
|
||
_write_envi_run_sidecar(
|
||
output_dir,
|
||
engine_code="sarscape",
|
||
profile_code=profile_code,
|
||
root_dir=root_dir,
|
||
task_dir=folder,
|
||
task_name=task_name,
|
||
task_alias=task_alias,
|
||
pair_key=pair_key,
|
||
run_key=resolved_run_key,
|
||
pair_meta=pair_meta,
|
||
started_at=run_started_at_text,
|
||
params={
|
||
"timeout_seconds": timeout,
|
||
"workflow": "metatask",
|
||
"dem_base_file": dem_base_file,
|
||
},
|
||
metrics={
|
||
"elapsed_seconds": elapsed,
|
||
},
|
||
)
|
||
output_dirs.append(output_dir)
|
||
task_results.append(
|
||
{
|
||
"task_name": task_name,
|
||
"task_alias": task_alias,
|
||
"pair_key": pair_key,
|
||
"run_key": resolved_run_key,
|
||
"task_dir": folder,
|
||
"output_dir": output_dir,
|
||
"success": True,
|
||
"status": "ok",
|
||
"elapsed_seconds": elapsed,
|
||
}
|
||
)
|
||
except Exception as exc:
|
||
elapsed = round(time.time() - start, 1)
|
||
failed += 1
|
||
log_lines.append(
|
||
f"[err] dinsar {task_name} failed ({elapsed}s): {exc}"
|
||
)
|
||
task_results.append(
|
||
{
|
||
"task_name": task_name,
|
||
"task_alias": task_alias,
|
||
"pair_key": pair_key,
|
||
"run_key": resolved_run_key,
|
||
"task_dir": folder,
|
||
"output_dir": output_dir,
|
||
"success": False,
|
||
"status": "failed",
|
||
"elapsed_seconds": elapsed,
|
||
"error": str(exc),
|
||
}
|
||
)
|
||
|
||
if failed > 0 and processed == 0 and len(task_folders) > 0:
|
||
detail = "\n".join(log_lines[-20:])
|
||
raise RuntimeError(
|
||
f"All D-InSAR tasks failed. failed={failed}, "
|
||
f"skipped={skipped}.\n{detail}"
|
||
)
|
||
|
||
return {
|
||
"summary": {
|
||
"task_folders": len(task_folders),
|
||
"processed": processed,
|
||
"failed": failed,
|
||
"skipped": skipped,
|
||
"auto_imported": auto_imported,
|
||
},
|
||
"log_lines": log_lines,
|
||
"task_results": task_results,
|
||
"output_dirs": output_dirs,
|
||
"run_key": resolved_run_key,
|
||
"profile_code": profile_code,
|
||
}
|
||
|
||
|
||
# ---------------------------------------------------------------------------
|
||
# Custom D-InSAR workflow helpers
|
||
# ---------------------------------------------------------------------------
|
||
|
||
def _read_sml_parameter(sml_file: str, param_name: str) -> Optional[str]:
|
||
"""Read a parameter value from a SARscape .sml XML file.
|
||
|
||
SML files use a namespace (http://www.sarmap.ch/xml/SARscapeHeaderSchema),
|
||
so we strip the namespace prefix before comparing tag names.
|
||
"""
|
||
sml_path = _to_local_path(sml_file)
|
||
if not os.path.isfile(sml_path):
|
||
return None
|
||
try:
|
||
tree = ET.parse(sml_path)
|
||
root = tree.getroot()
|
||
tag_upper = param_name.upper()
|
||
for elem in root.iter():
|
||
# Strip namespace: {http://...}TagName -> TagName
|
||
local_tag = elem.tag.split("}")[-1] if "}" in elem.tag else elem.tag
|
||
if local_tag.upper() == tag_upper and elem.text:
|
||
return elem.text.strip()
|
||
except Exception as exc:
|
||
print(f"[WARN] _read_sml: {sml_path} — {exc}")
|
||
return None
|
||
|
||
|
||
def _calculate_looks(
|
||
master_sml: str,
|
||
slave_sml: str,
|
||
target_resolution: float,
|
||
) -> tuple:
|
||
"""Calculate range and azimuth looks from SML pixel spacing.
|
||
|
||
Returns (range_looks, azimuth_looks) as integers >= 1.
|
||
Mirrors the IDL logic in batch_dinsarworkflow_all.pro.
|
||
"""
|
||
m_rg = _read_sml_parameter(master_sml, "PixelSpacingRg")
|
||
m_az = _read_sml_parameter(master_sml, "PixelSpacingAz")
|
||
m_inc = _read_sml_parameter(master_sml, "IncidenceAngle")
|
||
s_rg = _read_sml_parameter(slave_sml, "PixelSpacingRg")
|
||
s_az = _read_sml_parameter(slave_sml, "PixelSpacingAz")
|
||
s_inc = _read_sml_parameter(slave_sml, "IncidenceAngle")
|
||
|
||
if not all([m_rg, m_az, m_inc, s_rg, s_az, s_inc]):
|
||
raise ValueError(
|
||
"Cannot read pixel spacing / incidence angle from SML files. "
|
||
f"master={master_sml} slave={slave_sml}"
|
||
)
|
||
|
||
m_rg_f, m_az_f, m_inc_f = float(m_rg), float(m_az), float(m_inc)
|
||
s_rg_f, s_az_f, s_inc_f = float(s_rg), float(s_az), float(s_inc)
|
||
|
||
avg_az = (m_az_f + s_az_f) / 2.0
|
||
azimuth_looks = max(1, int(target_resolution / avg_az))
|
||
|
||
m_ground_rg = m_rg_f / math.sin(math.radians(m_inc_f))
|
||
s_ground_rg = s_rg_f / math.sin(math.radians(s_inc_f))
|
||
avg_ground_rg = (m_ground_rg + s_ground_rg) / 2.0
|
||
range_looks = max(1, int(target_resolution / avg_ground_rg))
|
||
|
||
return range_looks, azimuth_looks
|
||
|
||
|
||
def _find_latest_sarscapedata(
|
||
directory: str,
|
||
pattern_fragment: str,
|
||
log_lines: Optional[List[str]] = None,
|
||
) -> Optional[Dict[str, Any]]:
|
||
"""Scan directory for the latest SARscape file matching a pattern.
|
||
|
||
Used as a fallback when envipyengine reports 'outputs not generated'
|
||
but SARscape actually wrote the file. ``pattern_fragment`` is inserted
|
||
into a glob like ``*{pattern_fragment}*.sml``.
|
||
Returns a SARSCAPEDATA dict or None if not found.
|
||
"""
|
||
pattern = os.path.join(directory, f"*{pattern_fragment}*.sml")
|
||
candidates = sorted(glob(pattern), key=os.path.getmtime, reverse=True)
|
||
if log_lines is not None:
|
||
log_lines.append(f"[scan] pattern={pattern} found={len(candidates)}")
|
||
if not candidates:
|
||
return None
|
||
sml_path = candidates[0]
|
||
base = sml_path[:-4] # strip .sml
|
||
if log_lines is not None:
|
||
log_lines.append(f"[scan] using: {os.path.basename(base)}")
|
||
return _build_sarscapedata(base)
|
||
|
||
|
||
# Stability check configuration
|
||
_STABILITY_INTERVAL = int(_read_env("ENVI_STABILITY_CHECK_INTERVAL", "15") or 15)
|
||
_STABILITY_ROUNDS = int(_read_env("ENVI_STABILITY_ROUNDS", "3") or 3)
|
||
_STABILITY_MAX_WAIT = int(_read_env("ENVI_STABILITY_MAX_WAIT", "3600") or 3600)
|
||
|
||
|
||
def _wait_files_stable(
|
||
directory: str,
|
||
log_lines: Optional[List[str]] = None,
|
||
) -> None:
|
||
"""Wait until all files in directory have stable sizes.
|
||
|
||
Checks every _STABILITY_INTERVAL seconds. Returns when file sizes
|
||
are unchanged for _STABILITY_ROUNDS consecutive checks, or after
|
||
_STABILITY_MAX_WAIT seconds (safety cap).
|
||
"""
|
||
if not directory or not os.path.isdir(directory):
|
||
return
|
||
|
||
def _snapshot() -> Dict[str, int]:
|
||
sizes: Dict[str, int] = {}
|
||
try:
|
||
for root, _dirs, files in os.walk(directory):
|
||
for f in files:
|
||
fp = os.path.join(root, f)
|
||
try:
|
||
sizes[fp] = os.path.getsize(fp)
|
||
except OSError as exc:
|
||
print(f"[WARN] _snapshot getsize: {exc}")
|
||
except Exception as exc:
|
||
print(f"[WARN] _snapshot walk: {exc}")
|
||
return sizes
|
||
|
||
stable_count = 0
|
||
prev = _snapshot()
|
||
wait_start = time.time()
|
||
|
||
while stable_count < _STABILITY_ROUNDS:
|
||
elapsed = time.time() - wait_start
|
||
if elapsed > _STABILITY_MAX_WAIT:
|
||
if log_lines is not None:
|
||
log_lines.append(
|
||
f"[stability] max wait {_STABILITY_MAX_WAIT}s reached, proceeding"
|
||
)
|
||
break
|
||
time.sleep(_STABILITY_INTERVAL)
|
||
cur = _snapshot()
|
||
if cur == prev:
|
||
stable_count += 1
|
||
else:
|
||
stable_count = 0
|
||
prev = cur
|
||
|
||
total_wait = round(time.time() - wait_start, 1)
|
||
if log_lines is not None:
|
||
log_lines.append(
|
||
f"[stability] files stable after {total_wait}s "
|
||
f"({stable_count}/{_STABILITY_ROUNDS} rounds, "
|
||
f"{len(prev)} files)"
|
||
)
|
||
|
||
|
||
def _wait_for_disp_stable(
|
||
directory: str,
|
||
log_lines: Optional[List[str]] = None,
|
||
) -> bool:
|
||
"""Wait for *_rsp_disp file to appear and stabilize.
|
||
|
||
1. Poll until a file matching *_rsp_disp (no extra extension) appears.
|
||
2. Then wait until that file's size is unchanged for consecutive checks.
|
||
Returns True if the file was found and stabilized, False on timeout.
|
||
"""
|
||
if not directory or not os.path.isdir(directory):
|
||
return False
|
||
|
||
wait_start = time.time()
|
||
|
||
# Phase 1: wait for the file to appear
|
||
disp_path = None
|
||
while (time.time() - wait_start) < _STABILITY_MAX_WAIT:
|
||
for f in os.listdir(directory):
|
||
# Match *_rsp_disp exactly (not _rsp_disp_cc_geo etc.)
|
||
if f.endswith("_rsp_disp") and not f.endswith(".hdr") and not f.endswith(".sml"):
|
||
disp_path = os.path.join(directory, f)
|
||
break
|
||
if disp_path:
|
||
break
|
||
if log_lines is not None and int(time.time() - wait_start) % 60 == 0:
|
||
log_lines.append(
|
||
f"[wait_disp] waiting for _rsp_disp file... "
|
||
f"({int(time.time() - wait_start)}s)"
|
||
)
|
||
time.sleep(_STABILITY_INTERVAL)
|
||
|
||
if not disp_path:
|
||
if log_lines is not None:
|
||
log_lines.append(
|
||
f"[wait_disp] _rsp_disp file not found after "
|
||
f"{int(time.time() - wait_start)}s"
|
||
)
|
||
return False
|
||
|
||
if log_lines is not None:
|
||
log_lines.append(
|
||
f"[wait_disp] found {os.path.basename(disp_path)} "
|
||
f"after {int(time.time() - wait_start)}s"
|
||
)
|
||
|
||
# Phase 2: wait for the file size to stabilize
|
||
stable_count = 0
|
||
prev_size = None # None = not yet read; -1 = read failed
|
||
while stable_count < _STABILITY_ROUNDS:
|
||
if (time.time() - wait_start) > _STABILITY_MAX_WAIT:
|
||
if log_lines is not None:
|
||
log_lines.append("[wait_disp] max wait reached, proceeding")
|
||
break
|
||
time.sleep(_STABILITY_INTERVAL)
|
||
try:
|
||
cur_size = os.path.getsize(disp_path)
|
||
except OSError:
|
||
cur_size = -1
|
||
# Only count as stable if we got a real size (>= 0) and it matches prev
|
||
if cur_size >= 0 and cur_size == prev_size:
|
||
stable_count += 1
|
||
else:
|
||
stable_count = 0
|
||
prev_size = cur_size
|
||
|
||
total_wait = round(time.time() - wait_start, 1)
|
||
if log_lines is not None:
|
||
log_lines.append(
|
||
f"[wait_disp] stable after {total_wait}s "
|
||
f"(size={prev_size} bytes)"
|
||
)
|
||
return True
|
||
|
||
|
||
def _generate_gcps(
|
||
coherence_file: str,
|
||
output_shp: str,
|
||
coh_threshold: float = 0.7,
|
||
num_points: int = 100,
|
||
log_lines: Optional[List[str]] = None,
|
||
) -> bool:
|
||
"""Generate GCP shapefile from coherence raster (Python rewrite of IDL logic).
|
||
|
||
Divides the raster into a grid, picks the highest-coherence pixel per cell
|
||
that exceeds coh_threshold, and writes a point shapefile with SARscape fields.
|
||
"""
|
||
try:
|
||
import numpy as np
|
||
import rasterio
|
||
import geopandas as gpd
|
||
from shapely.geometry import Point
|
||
except ImportError as exc:
|
||
raise RuntimeError(
|
||
"rasterio, geopandas, and shapely are required for GCP generation. "
|
||
f"Missing: {exc}"
|
||
) from exc
|
||
|
||
coh_path = _to_local_path(coherence_file)
|
||
# SARscape coherence files may not have an extension — try common variants
|
||
if not os.path.isfile(coh_path):
|
||
for ext in [".hdr", ""]:
|
||
candidate = coh_path + ext
|
||
if os.path.isfile(candidate):
|
||
coh_path = candidate
|
||
break
|
||
|
||
if not os.path.isfile(coh_path):
|
||
if log_lines is not None:
|
||
log_lines.append(f"[gcp] coherence file not found: {coh_path}")
|
||
return False
|
||
|
||
with rasterio.open(coh_path) as src:
|
||
data = src.read(1) # first band
|
||
ns, nl = src.width, src.height
|
||
|
||
grid_dim = math.ceil(math.sqrt(num_points))
|
||
x_step = nl // grid_dim # rows
|
||
y_step = ns // grid_dim # cols
|
||
|
||
points = []
|
||
for j in range(grid_dim):
|
||
for i in range(grid_dim):
|
||
x_start = i * y_step
|
||
y_start = j * x_step
|
||
x_end = min((i + 1) * y_step, ns)
|
||
y_end = min((j + 1) * x_step, nl)
|
||
if x_start >= ns or y_start >= nl:
|
||
continue
|
||
cell = data[y_start:y_end, x_start:x_end]
|
||
max_val = float(np.nanmax(cell)) if cell.size > 0 else 0.0
|
||
if max_val >= coh_threshold:
|
||
idx = int(np.nanargmax(cell))
|
||
cell_h, cell_w = cell.shape
|
||
max_row = idx // cell_w
|
||
max_col = idx % cell_w
|
||
px_col = x_start + max_col
|
||
px_row = y_start + max_row
|
||
points.append((px_col, px_row))
|
||
|
||
if not points:
|
||
if log_lines is not None:
|
||
log_lines.append(
|
||
f"[gcp] no points found above threshold {coh_threshold}"
|
||
)
|
||
return False
|
||
|
||
# Build GeoDataFrame with SARscape-compatible fields
|
||
records = []
|
||
for idx, (col, row) in enumerate(points):
|
||
records.append({
|
||
"SHP_ID": idx,
|
||
"GCP_LABEL": f"GCP_{idx + 1}",
|
||
"GCP_TYPE": "undefined",
|
||
"GCP_COLUMN": float(col),
|
||
"GCP_ROW": float(row),
|
||
"GCP_OTHER_": "",
|
||
"geometry": Point(float(col), float(row)),
|
||
})
|
||
|
||
gdf = gpd.GeoDataFrame(records)
|
||
out_path = _to_local_path(output_shp)
|
||
os.makedirs(os.path.dirname(out_path) or ".", exist_ok=True)
|
||
gdf.to_file(out_path, driver="ESRI Shapefile")
|
||
|
||
if log_lines is not None:
|
||
log_lines.append(f"[gcp] created {len(points)} GCPs -> {out_path}")
|
||
return True
|
||
|
||
|
||
def _run_dinsar_custom_single(
|
||
master_base: str,
|
||
slave_base: str,
|
||
dem_base: str,
|
||
output_root: str,
|
||
log_lines: List[str],
|
||
job_id: Optional[str] = None,
|
||
pair_index: int = 0,
|
||
total_pairs: int = 0,
|
||
pair_name: str = "",
|
||
) -> bool:
|
||
"""Execute the 6-step custom D-InSAR workflow for one pair.
|
||
|
||
Uses envipyengine individual tasks instead of the metatask.
|
||
Each step's output SARSCAPEDATA is chained as input to the next step.
|
||
"""
|
||
master_sml = master_base + ".sml"
|
||
slave_sml = slave_base + ".sml"
|
||
|
||
# Build SARSCAPEDATA hashes
|
||
master_sd = _build_sarscapedata(master_base)
|
||
slave_sd = _build_sarscapedata(slave_base)
|
||
dem_sd = _build_sarscapedata(dem_base)
|
||
out_dir = _normalize_path(os.path.dirname(output_root))
|
||
|
||
# --- Calculate looks ---
|
||
try:
|
||
range_looks, azimuth_looks = _calculate_looks(
|
||
master_sml, slave_sml, CUSTOM_TARGET_RESOLUTION_M
|
||
)
|
||
log_lines.append(
|
||
f"[custom] looks: range={range_looks} azimuth={azimuth_looks} "
|
||
f"(target_res={CUSTOM_TARGET_RESOLUTION_M}m)"
|
||
)
|
||
except Exception as exc:
|
||
log_lines.append(f"[custom] looks calculation failed: {exc}")
|
||
return False
|
||
|
||
# === STEP 1: Interferogram Generation ===
|
||
log_lines.append("[custom] step 1/6: Interferogram Generation")
|
||
_write_progress(job_id, 1, 6, "Interferogram Generation", out_dir, pair_index, total_pairs, pair_name)
|
||
start = time.time()
|
||
try:
|
||
r1 = execute_envi_task(
|
||
"SARsInSARInterferogramGeneration",
|
||
{
|
||
"REFERENCE_SARSCAPEDATA": master_sd,
|
||
"SECONDARY_SARSCAPEDATA": slave_sd,
|
||
"DEM_SARSCAPEDATA": dem_sd,
|
||
"ROOT_URI_FOR_OUTPUT": out_dir,
|
||
"RG_LOOKS_NBR": float(range_looks),
|
||
"AZ_LOOKS_NBR": float(azimuth_looks),
|
||
"COREGISTRATION_WITH_DEM": True,
|
||
},
|
||
)
|
||
log_lines.append(f"[custom] step 1 ok ({round(time.time() - start, 1)}s)")
|
||
except Exception as exc:
|
||
log_lines.append(
|
||
f"[custom] step 1 failed ({round(time.time() - start, 1)}s): {exc}"
|
||
)
|
||
return False
|
||
|
||
# Extract step 1 outputs for chaining
|
||
s1_dint = _unwrap_sarscapedata(r1.get("DINT_SARSCAPEDATA"))
|
||
s1_ref_pwr = _unwrap_sarscapedata(r1.get("REFERENCE_POWER_SARSCAPEDATA"))
|
||
s1_sec_pwr = _unwrap_sarscapedata(r1.get("SECONDARY_POWER_SARSCAPEDATA"))
|
||
s1_sint = _unwrap_sarscapedata(r1.get("SINT_SARSCAPEDATA"))
|
||
s1_srdem = _unwrap_sarscapedata(r1.get("SRDEM_SARSCAPEDATA"))
|
||
log_lines.append(
|
||
f"[custom] step 1 outputs: dint={bool(s1_dint)} ref_pwr={bool(s1_ref_pwr)} "
|
||
f"sec_pwr={bool(s1_sec_pwr)} sint={bool(s1_sint)} srdem={bool(s1_srdem)}"
|
||
)
|
||
|
||
# === STEP 2: Filtering and Coherence ===
|
||
log_lines.append("[custom] step 2/6: Filtering and Coherence")
|
||
_write_progress(job_id, 2, 6, "Filtering and Coherence", out_dir, pair_index, total_pairs, pair_name)
|
||
start = time.time()
|
||
try:
|
||
r2 = execute_envi_task(
|
||
"SARsInSARFilterAndCoherence",
|
||
{
|
||
"DINT_SARSCAPEDATA": s1_dint,
|
||
"REFERENCE_SARSCAPEDATA": s1_ref_pwr,
|
||
"SECONDARY_SARSCAPEDATA": s1_sec_pwr,
|
||
"ROOT_URI_FOR_OUTPUT": out_dir,
|
||
"FILTERING_METHOD": CUSTOM_FILTER_METHOD,
|
||
"COHERENCE": True,
|
||
"INTERF_FILT": True,
|
||
},
|
||
)
|
||
log_lines.append(f"[custom] step 2 ok ({round(time.time() - start, 1)}s)")
|
||
except Exception as exc:
|
||
log_lines.append(
|
||
f"[custom] step 2 failed ({round(time.time() - start, 1)}s): {exc}"
|
||
)
|
||
return False
|
||
|
||
s2_fint = _unwrap_sarscapedata(r2.get("FINT_SARSCAPEDATA"))
|
||
s2_cc = _unwrap_sarscapedata(r2.get("COHERENCE_SARSCAPEDATA"))
|
||
log_lines.append(
|
||
f"[custom] step 2 outputs: fint={bool(s2_fint)} cc={bool(s2_cc)}"
|
||
)
|
||
|
||
# === STEP 3: Remove Residual Phase Frequency ===
|
||
log_lines.append("[custom] step 3/6: Orbital Trend Removal")
|
||
_write_progress(job_id, 3, 6, "Orbital Trend Removal", out_dir, pair_index, total_pairs, pair_name)
|
||
start = time.time()
|
||
s3_rrpf = None
|
||
try:
|
||
r3 = execute_envi_task(
|
||
"SARsInSARRemoveResidualPhaseFrequency",
|
||
{
|
||
"INTERFEROGRAM_SARSCAPEDATA": s2_fint,
|
||
"COHERENCE_FILE_NAME": s2_cc,
|
||
"ROOT_URI_FOR_OUTPUT": out_dir,
|
||
},
|
||
)
|
||
s3_rrpf = _unwrap_sarscapedata(r3.get("RRPF_DINT_SARSCAPEDATA"))
|
||
log_lines.append(f"[custom] step 3 ok ({round(time.time() - start, 1)}s)")
|
||
except Exception as exc:
|
||
elapsed = round(time.time() - start, 1)
|
||
log_lines.append(f"[custom] step 3 engine error ({elapsed}s): {exc}")
|
||
# envipyengine may report "outputs not generated" even though
|
||
# SARscape DID write the file. Scan the directory for it.
|
||
log_lines.append("[custom] step 3 scanning for generated RRPF file...")
|
||
s3_rrpf = _find_latest_sarscapedata(
|
||
_to_local_path(out_dir), "ISARRRPF", log_lines
|
||
)
|
||
|
||
if not s3_rrpf:
|
||
log_lines.append("[custom] step 3 failed: no RRPF output found")
|
||
return False
|
||
log_lines.append(f"[custom] step 3 output: {s3_rrpf.get('url', '?')}")
|
||
|
||
# === STEP 4: Phase Unwrapping ===
|
||
log_lines.append("[custom] step 4/6: Phase Unwrapping")
|
||
_write_progress(job_id, 4, 6, "Phase Unwrapping", out_dir, pair_index, total_pairs, pair_name)
|
||
start = time.time()
|
||
s4_upha = None
|
||
try:
|
||
r4 = execute_envi_task(
|
||
"SARsInSARPhaseUnwrapping",
|
||
{
|
||
"INFILE_NAME": s3_rrpf,
|
||
"COHERENCEFILE_NAME": s2_cc,
|
||
"ROOT_URI_FOR_OUTPUT": out_dir,
|
||
"UPHA_COH_THRESHOLD": CUSTOM_UNWRAP_COH_THRESHOLD,
|
||
},
|
||
)
|
||
s4_upha = _unwrap_sarscapedata(r4.get("OUTFILE_NAME"))
|
||
log_lines.append(f"[custom] step 4 ok ({round(time.time() - start, 1)}s)")
|
||
except Exception as exc:
|
||
elapsed = round(time.time() - start, 1)
|
||
log_lines.append(f"[custom] step 4 engine error ({elapsed}s): {exc}")
|
||
log_lines.append("[custom] step 4 scanning for generated UPHA file...")
|
||
s4_upha = _find_latest_sarscapedata(
|
||
_to_local_path(out_dir), "ISARPU", log_lines
|
||
)
|
||
|
||
if not s4_upha:
|
||
log_lines.append("[custom] step 4 failed: no UPHA output found")
|
||
return False
|
||
log_lines.append(f"[custom] step 4 output: {s4_upha.get('url', '?')}")
|
||
|
||
# === STEP 5: Refinement and Reflattening (with auto GCP) ===
|
||
# 5a: Generate GCPs from coherence
|
||
log_lines.append("[custom] step 5a/6: GCP Generation")
|
||
_write_progress(job_id, 5, 6, "GCP Generation + Refinement", out_dir, pair_index, total_pairs, pair_name)
|
||
# Extract coherence base path from SARSCAPEDATA for rasterio
|
||
cc_url = s2_cc.get("url", "") if isinstance(s2_cc, dict) else str(s2_cc)
|
||
cc_local = _to_local_path(cc_url)
|
||
auto_gcp_shp = os.path.join(os.path.dirname(cc_local) or out_dir, "auto_gcp.shp")
|
||
gcp_ok = _generate_gcps(
|
||
coherence_file=cc_local,
|
||
output_shp=auto_gcp_shp,
|
||
coh_threshold=CUSTOM_GCP_COH_THRESHOLD,
|
||
num_points=CUSTOM_GCP_NUMBER,
|
||
log_lines=log_lines,
|
||
)
|
||
if not gcp_ok:
|
||
log_lines.append("[custom] step 5a failed: GCP generation returned no points")
|
||
return False
|
||
|
||
# 5b: Refinement and Reflattening
|
||
log_lines.append("[custom] step 5b/6: Refinement and Reflattening")
|
||
start = time.time()
|
||
s5_upha = None
|
||
try:
|
||
r5 = execute_envi_task(
|
||
"SARsInSARRefinementAndReflattening",
|
||
{
|
||
"INPUT_UPHA_FILE_NAME": s4_upha,
|
||
"REFERENCE_SARSCAPEDATA": s1_ref_pwr,
|
||
"SECONDARY_SARSCAPEDATA": s1_sec_pwr,
|
||
"SLANT_RANGE_DEM_FILE_NAME": s1_srdem,
|
||
"SYNTHETIC_FILE_NAME": s1_sint,
|
||
"COHERENCE_FILE_NAME": s2_cc,
|
||
"DEM_SARSCAPEDATA": dem_sd,
|
||
"ROOT_URI_FOR_OUTPUT": out_dir,
|
||
"REFINEMENT_GCP_FILE_NAME": _normalize_path(auto_gcp_shp),
|
||
},
|
||
)
|
||
s5_upha = _unwrap_sarscapedata(r5.get("UPHA_REFLAT_SARSCAPEDATA"))
|
||
log_lines.append(f"[custom] step 5b ok ({round(time.time() - start, 1)}s)")
|
||
except Exception as exc:
|
||
elapsed = round(time.time() - start, 1)
|
||
log_lines.append(f"[custom] step 5b engine error ({elapsed}s): {exc}")
|
||
log_lines.append("[custom] step 5b scanning for generated REFLAT UPHA file...")
|
||
s5_upha = _find_latest_sarscapedata(
|
||
_to_local_path(out_dir), "ISARRF", log_lines
|
||
)
|
||
# Refinement produces multiple outputs; pick the _upha one
|
||
if not s5_upha:
|
||
s5_upha = _find_latest_sarscapedata(
|
||
_to_local_path(out_dir), "_reflat_upha", log_lines
|
||
)
|
||
|
||
if not s5_upha:
|
||
log_lines.append("[custom] step 5b failed: no REFLAT UPHA output found")
|
||
return False
|
||
log_lines.append(f"[custom] step 5b output: {s5_upha.get('url', '?')}")
|
||
|
||
# === STEP 6: Phase to Displacement and Geocoding ===
|
||
log_lines.append("[custom] step 6/6: Phase to Displacement + Geocoding")
|
||
_write_progress(job_id, 6, 6, "Phase to Displacement + Geocoding", out_dir, pair_index, total_pairs, pair_name)
|
||
start = time.time()
|
||
try:
|
||
r6 = execute_envi_task(
|
||
"SARsInSARPhaseToDisplacement",
|
||
{
|
||
"INPUT_SARSCAPEDATA": s5_upha,
|
||
"COHERNCE_SARSCAPEDATA": s2_cc,
|
||
"DEM_SARSCAPEDATA": dem_sd,
|
||
"ROOT_URI_FOR_OUTPUT": out_dir,
|
||
"COHERENCE_THRESHOLD": CUSTOM_GEOCODING_COH_THRESHOLD,
|
||
"GEOCODE_RG_GRID_SIZE": CUSTOM_GEOCODING_PIXEL_SIZE_M,
|
||
"GEOCODE_AZ_GRID_SIZE": CUSTOM_GEOCODING_PIXEL_SIZE_M,
|
||
},
|
||
)
|
||
log_lines.append(f"[custom] step 6 ok ({round(time.time() - start, 1)}s)")
|
||
except Exception as exc:
|
||
elapsed = round(time.time() - start, 1)
|
||
log_lines.append(f"[custom] step 6 engine error ({elapsed}s): {exc}")
|
||
|
||
# envipyengine may return (success or error) before ENVI finishes writing.
|
||
# Always wait for the _rsp_disp file to appear and stabilize.
|
||
log_lines.append("[custom] step 6: waiting for _rsp_disp file...")
|
||
disp_ok = _wait_for_disp_stable(_to_local_path(out_dir), log_lines)
|
||
if not disp_ok:
|
||
log_lines.append("[custom] step 6 failed: _rsp_disp never appeared")
|
||
return False
|
||
|
||
# Final stability wait: ensure ALL output files are fully written
|
||
log_lines.append("[custom] final stability check on output directory...")
|
||
_wait_files_stable(_to_local_path(out_dir), log_lines)
|
||
|
||
_write_progress(job_id, 6, 6, "Completed", out_dir, pair_index, total_pairs, pair_name)
|
||
return True
|
||
|
||
|
||
# ---------------------------------------------------------------------------
|
||
# Custom D-InSAR batch workflow
|
||
# ---------------------------------------------------------------------------
|
||
|
||
def run_dinsar_custom_workflow(
|
||
root_dir: str,
|
||
num_to_process: int = 0,
|
||
timeout: int = DEFAULT_TIMEOUT,
|
||
job_id: Optional[str] = None,
|
||
timeout_seconds: Optional[int] = None,
|
||
run_key: Optional[str] = None,
|
||
profile_code: str = "custom6",
|
||
started_at: Optional[datetime] = None,
|
||
) -> Dict[str, Any]:
|
||
"""Run custom 6-step D-InSAR on Task_* folders.
|
||
|
||
Same smart-chaining as metatask version (auto-import if needed),
|
||
but uses individual SARscape tasks with user-defined parameters.
|
||
"""
|
||
timeout = min(timeout_seconds or timeout or DEFAULT_TIMEOUT, MAX_TIMEOUT)
|
||
root_dir = _to_local_path(root_dir)
|
||
run_started_at = started_at or datetime.utcnow()
|
||
run_started_at_text = run_started_at.isoformat(timespec="seconds") + "Z"
|
||
resolved_run_key = run_key or build_run_key("sarscape", profile_code, started_at=run_started_at)
|
||
dem_base_file = DEM_BASE_FILE
|
||
if not root_dir or not os.path.isdir(root_dir):
|
||
raise ValueError(f"D-InSAR root directory does not exist: {root_dir}")
|
||
if not dem_base_file:
|
||
raise ValueError(
|
||
"DEM path not configured. Set IDL_DINSAR_DEM_BASE_FILE in .env"
|
||
)
|
||
|
||
task_folders = _collect_task_folders(root_dir)
|
||
log_lines: List[str] = [
|
||
f"[envi] dinsar custom (6-step)",
|
||
f"[envi] root_dir={root_dir}",
|
||
f"[envi] dem={dem_base_file}",
|
||
f"[envi] target_resolution={CUSTOM_TARGET_RESOLUTION_M}m",
|
||
f"[envi] filter={CUSTOM_FILTER_METHOD}",
|
||
f"[envi] unwrap_coh={CUSTOM_UNWRAP_COH_THRESHOLD}",
|
||
f"[envi] gcp_coh={CUSTOM_GCP_COH_THRESHOLD} gcp_n={CUSTOM_GCP_NUMBER}",
|
||
f"[envi] geocode_coh={CUSTOM_GEOCODING_COH_THRESHOLD} "
|
||
f"geocode_px={CUSTOM_GEOCODING_PIXEL_SIZE_M}m",
|
||
f"[envi] Task_* folders={len(task_folders)}",
|
||
]
|
||
if not task_folders:
|
||
return {
|
||
"summary": {
|
||
"task_folders": 0,
|
||
"processed": 0,
|
||
"failed": 0,
|
||
"skipped": 0,
|
||
"auto_imported": 0,
|
||
},
|
||
"log_lines": log_lines,
|
||
"task_results": [],
|
||
"output_dirs": [],
|
||
"run_key": resolved_run_key,
|
||
"profile_code": profile_code,
|
||
}
|
||
|
||
processed = 0
|
||
failed = 0
|
||
skipped = 0
|
||
auto_imported = 0
|
||
task_results: List[Dict[str, Any]] = []
|
||
output_dirs: List[str] = []
|
||
effective_total = len(task_folders) if num_to_process <= 0 else min(num_to_process, len(task_folders))
|
||
pair_counter = 0
|
||
|
||
for folder in task_folders:
|
||
if num_to_process > 0 and processed >= num_to_process:
|
||
log_lines.append(f"[envi] reached limit={num_to_process}")
|
||
break
|
||
task_name = os.path.basename(folder)
|
||
task_alias, pair_key, pair_meta = _resolve_dinsar_pair_identity(folder, task_name)
|
||
master_dir = os.path.join(folder, "master")
|
||
slave_dir = os.path.join(folder, "slave")
|
||
|
||
if not os.path.isdir(master_dir) or not os.path.isdir(slave_dir):
|
||
skipped += 1
|
||
log_lines.append(f"[skip] {task_name}: master/slave dir missing")
|
||
task_results.append(
|
||
{
|
||
"task_name": task_name,
|
||
"task_alias": task_alias,
|
||
"pair_key": pair_key,
|
||
"run_key": resolved_run_key,
|
||
"task_dir": folder,
|
||
"success": False,
|
||
"status": "skipped",
|
||
"error": "master/slave dir missing",
|
||
}
|
||
)
|
||
continue
|
||
|
||
# --- Smart chaining: auto-import if .sml missing ---
|
||
for side, side_dir in [("master", master_dir), ("slave", slave_dir)]:
|
||
if not _has_sml(side_dir):
|
||
meta_files = _find_meta_files(side_dir)
|
||
if not meta_files:
|
||
log_lines.append(
|
||
f"[warn] {task_name}/{side}: no .sml and no .meta.xml"
|
||
)
|
||
continue
|
||
log_lines.append(
|
||
f"[auto-import] {task_name}/{side}: "
|
||
f"importing {len(meta_files)} file(s)"
|
||
)
|
||
for mf in meta_files:
|
||
imp_start = time.time()
|
||
try:
|
||
execute_envi_task(
|
||
"SARsImportLuTan1",
|
||
{
|
||
"INPUT_FILE_LIST": [mf],
|
||
"ROOT_URI_FOR_OUTPUT": side_dir,
|
||
},
|
||
)
|
||
elapsed = round(time.time() - imp_start, 1)
|
||
auto_imported += 1
|
||
log_lines.append(
|
||
f"[auto-import ok] {task_name}/{side}: "
|
||
f"{os.path.basename(mf)} ({elapsed}s)"
|
||
)
|
||
except Exception as exc:
|
||
elapsed = round(time.time() - imp_start, 1)
|
||
log_lines.append(
|
||
f"[auto-import err] {task_name}/{side}: "
|
||
f"{os.path.basename(mf)} ({elapsed}s): {exc}"
|
||
)
|
||
|
||
# After auto-import, check .sml again
|
||
master_base = _first_sml_base(master_dir)
|
||
slave_base = _first_sml_base(slave_dir)
|
||
if not master_base or not slave_base:
|
||
skipped += 1
|
||
log_lines.append(
|
||
f"[skip] {task_name}: still missing .sml after import "
|
||
f"(master={'yes' if master_base else 'no'} "
|
||
f"slave={'yes' if slave_base else 'no'})"
|
||
)
|
||
task_results.append(
|
||
{
|
||
"task_name": task_name,
|
||
"task_alias": task_alias,
|
||
"pair_key": pair_key,
|
||
"run_key": resolved_run_key,
|
||
"task_dir": folder,
|
||
"success": False,
|
||
"status": "skipped",
|
||
"error": "missing .sml after import",
|
||
}
|
||
)
|
||
continue
|
||
|
||
output_dir = os.path.join(folder, "dinsar_results")
|
||
os.makedirs(output_dir, exist_ok=True)
|
||
output_root = os.path.join(output_dir, "workflow")
|
||
|
||
pair_start = time.time()
|
||
pair_counter += 1
|
||
log_lines.append(f"[custom] === {task_name} start ({pair_counter}/{effective_total}) ===")
|
||
try:
|
||
success = _run_dinsar_custom_single(
|
||
master_base, slave_base, dem_base_file, output_root, log_lines,
|
||
job_id=job_id,
|
||
pair_index=pair_counter,
|
||
total_pairs=effective_total,
|
||
pair_name=task_name,
|
||
)
|
||
except Exception as exc:
|
||
success = False
|
||
log_lines.append(f"[custom] {task_name} crashed: {exc}")
|
||
elapsed = round(time.time() - pair_start, 1)
|
||
|
||
if success:
|
||
processed += 1
|
||
log_lines.append(f"[ok] custom dinsar {task_name} ({elapsed}s)")
|
||
_write_envi_run_sidecar(
|
||
output_dir,
|
||
engine_code="sarscape",
|
||
profile_code=profile_code,
|
||
root_dir=root_dir,
|
||
task_dir=folder,
|
||
task_name=task_name,
|
||
task_alias=task_alias,
|
||
pair_key=pair_key,
|
||
run_key=resolved_run_key,
|
||
pair_meta=pair_meta,
|
||
started_at=run_started_at_text,
|
||
params={
|
||
"timeout_seconds": timeout,
|
||
"workflow": "custom6",
|
||
"dem_base_file": dem_base_file,
|
||
"target_resolution_m": CUSTOM_TARGET_RESOLUTION_M,
|
||
"filter_method": CUSTOM_FILTER_METHOD,
|
||
"unwrap_coh_threshold": CUSTOM_UNWRAP_COH_THRESHOLD,
|
||
"gcp_coh_threshold": CUSTOM_GCP_COH_THRESHOLD,
|
||
"gcp_number": CUSTOM_GCP_NUMBER,
|
||
"geocoding_coh_threshold": CUSTOM_GEOCODING_COH_THRESHOLD,
|
||
"geocoding_pixel_size_m": CUSTOM_GEOCODING_PIXEL_SIZE_M,
|
||
},
|
||
metrics={
|
||
"elapsed_seconds": elapsed,
|
||
},
|
||
)
|
||
output_dirs.append(output_dir)
|
||
task_results.append(
|
||
{
|
||
"task_name": task_name,
|
||
"task_alias": task_alias,
|
||
"pair_key": pair_key,
|
||
"run_key": resolved_run_key,
|
||
"task_dir": folder,
|
||
"output_dir": output_dir,
|
||
"success": True,
|
||
"status": "ok",
|
||
"elapsed_seconds": elapsed,
|
||
}
|
||
)
|
||
else:
|
||
failed += 1
|
||
log_lines.append(f"[err] custom dinsar {task_name} failed ({elapsed}s)")
|
||
task_results.append(
|
||
{
|
||
"task_name": task_name,
|
||
"task_alias": task_alias,
|
||
"pair_key": pair_key,
|
||
"run_key": resolved_run_key,
|
||
"task_dir": folder,
|
||
"output_dir": output_dir,
|
||
"success": False,
|
||
"status": "failed",
|
||
"elapsed_seconds": elapsed,
|
||
}
|
||
)
|
||
|
||
# Flush intermediate log so progress is preserved if process crashes
|
||
try:
|
||
os.makedirs(RUNTIME_DIR, exist_ok=True)
|
||
_interim_log = os.path.join(RUNTIME_DIR, "dinsar_custom_progress.log")
|
||
with open(_interim_log, "w", encoding="utf-8") as _fp:
|
||
_fp.write("\n".join(log_lines))
|
||
except Exception as exc:
|
||
print(f"[WARN] dinsar_workflow log: {exc}")
|
||
|
||
if failed > 0 and processed == 0 and len(task_folders) > 0:
|
||
detail = "\n".join(log_lines[-20:])
|
||
raise RuntimeError(
|
||
f"All custom D-InSAR tasks failed. failed={failed}, "
|
||
f"skipped={skipped}.\n{detail}"
|
||
)
|
||
|
||
return {
|
||
"summary": {
|
||
"task_folders": len(task_folders),
|
||
"processed": processed,
|
||
"failed": failed,
|
||
"skipped": skipped,
|
||
"auto_imported": auto_imported,
|
||
},
|
||
"log_lines": log_lines,
|
||
"task_results": task_results,
|
||
"output_dirs": output_dirs,
|
||
"run_key": resolved_run_key,
|
||
"profile_code": profile_code,
|
||
}
|
||
|
||
|
||
# ---------------------------------------------------------------------------
|
||
# Single-task D-InSAR workflow entrypoints
|
||
# ---------------------------------------------------------------------------
|
||
|
||
def run_single_task_workflow(
|
||
workflow: str,
|
||
task_dir: str,
|
||
output_dir: str,
|
||
*,
|
||
source_root: Optional[str] = None,
|
||
timeout: int = DEFAULT_TIMEOUT,
|
||
timeout_seconds: Optional[int] = None,
|
||
job_id: Optional[str] = None,
|
||
run_key: Optional[str] = None,
|
||
profile_code: Optional[str] = None,
|
||
started_at: Optional[datetime] = None,
|
||
) -> Dict[str, Any]:
|
||
"""Run one Task_* directory into an isolated output directory."""
|
||
normalized_workflow = str(workflow or "").strip().lower()
|
||
if normalized_workflow not in {"dinsar", "dinsar_custom"}:
|
||
raise ValueError(f"Unsupported single-task workflow: {workflow}")
|
||
|
||
timeout = min(timeout_seconds or timeout or DEFAULT_TIMEOUT, MAX_TIMEOUT)
|
||
task_dir = _to_local_path(task_dir)
|
||
output_dir = _to_local_path(output_dir)
|
||
source_root = _to_local_path(source_root or os.path.dirname(task_dir))
|
||
run_started_at = started_at or datetime.utcnow()
|
||
run_started_at_text = run_started_at.isoformat(timespec="seconds") + "Z"
|
||
resolved_profile_code = profile_code or ("custom6" if normalized_workflow == "dinsar_custom" else "metatask")
|
||
resolved_run_key = run_key or build_run_key("sarscape", resolved_profile_code, started_at=run_started_at)
|
||
task_name = os.path.basename(os.path.normpath(task_dir))
|
||
task_alias, pair_key, pair_meta = _resolve_dinsar_pair_identity(task_dir, task_name)
|
||
|
||
if not task_dir or not os.path.isdir(task_dir):
|
||
raise ValueError(f"D-InSAR task directory does not exist: {task_dir}")
|
||
if not output_dir:
|
||
raise ValueError("output_dir must not be empty.")
|
||
if not DEM_BASE_FILE:
|
||
raise ValueError("DEM path not configured. Set IDL_DINSAR_DEM_BASE_FILE in .env")
|
||
|
||
native_output_dir = get_run_native_output_dir(output_dir)
|
||
master_dir = os.path.join(task_dir, "master")
|
||
slave_dir = os.path.join(task_dir, "slave")
|
||
if not os.path.isdir(master_dir) or not os.path.isdir(slave_dir):
|
||
raise RuntimeError(f"{task_name}: master/slave dir missing")
|
||
|
||
os.makedirs(output_dir, exist_ok=True)
|
||
os.makedirs(native_output_dir, exist_ok=True)
|
||
log_lines: List[str] = [
|
||
f"[envi] single task workflow={normalized_workflow}",
|
||
f"[envi] source_root={source_root}",
|
||
f"[envi] task_dir={task_dir}",
|
||
f"[envi] output_dir={output_dir}",
|
||
f"[envi] native_output_dir={native_output_dir}",
|
||
f"[envi] dem={DEM_BASE_FILE}",
|
||
]
|
||
auto_imported = 0
|
||
|
||
for side, side_dir in [("master", master_dir), ("slave", slave_dir)]:
|
||
if _has_sml(side_dir):
|
||
continue
|
||
meta_files = _find_meta_files(side_dir)
|
||
if not meta_files:
|
||
log_lines.append(f"[warn] {task_name}/{side}: no .sml and no .meta.xml")
|
||
continue
|
||
log_lines.append(f"[auto-import] {task_name}/{side}: importing {len(meta_files)} file(s)")
|
||
for meta_file in meta_files:
|
||
start = time.time()
|
||
try:
|
||
execute_envi_task(
|
||
"SARsImportLuTan1",
|
||
{
|
||
"INPUT_FILE_LIST": [meta_file],
|
||
"ROOT_URI_FOR_OUTPUT": side_dir,
|
||
},
|
||
)
|
||
elapsed = round(time.time() - start, 1)
|
||
auto_imported += 1
|
||
log_lines.append(f"[auto-import ok] {task_name}/{side}: {os.path.basename(meta_file)} ({elapsed}s)")
|
||
except Exception as exc:
|
||
elapsed = round(time.time() - start, 1)
|
||
log_lines.append(f"[auto-import err] {task_name}/{side}: {os.path.basename(meta_file)} ({elapsed}s): {exc}")
|
||
|
||
master_base = _first_sml_base(master_dir)
|
||
slave_base = _first_sml_base(slave_dir)
|
||
if not master_base or not slave_base:
|
||
raise RuntimeError(
|
||
f"{task_name}: missing .sml after import "
|
||
f"(master={'yes' if master_base else 'no'} slave={'yes' if slave_base else 'no'})"
|
||
)
|
||
|
||
start = time.time()
|
||
if normalized_workflow == "dinsar":
|
||
_write_progress(job_id, 1, 1, "Metatask D-InSAR", output_dir, 1, 1, task_name)
|
||
execute_envi_task(
|
||
"SARsMetataskInSARDisplacementGeneration",
|
||
{
|
||
"REFERENCE_SARSCAPEDATA": _build_sarscapedata(master_base),
|
||
"SECONDARY_SARSCAPEDATA": _build_sarscapedata(slave_base),
|
||
"DEM_SARSCAPEDATA": _build_sarscapedata(DEM_BASE_FILE),
|
||
"OUTPUT_FOLDER": _normalize_path(native_output_dir),
|
||
},
|
||
)
|
||
_write_progress(job_id, 1, 1, "Completed", output_dir, 1, 1, task_name)
|
||
else:
|
||
success = _run_dinsar_custom_single(
|
||
master_base,
|
||
slave_base,
|
||
DEM_BASE_FILE,
|
||
os.path.join(native_output_dir, "workflow"),
|
||
log_lines,
|
||
job_id=job_id,
|
||
pair_index=1,
|
||
total_pairs=1,
|
||
pair_name=task_name,
|
||
)
|
||
if not success:
|
||
detail = "\n".join(log_lines[-20:])
|
||
raise RuntimeError(f"{task_name}: custom D-InSAR workflow failed.\n{detail}")
|
||
|
||
elapsed = round(time.time() - start, 1)
|
||
log_lines.append(f"[ok] {normalized_workflow} {task_name} ({elapsed}s)")
|
||
_write_envi_run_sidecar(
|
||
output_dir,
|
||
engine_code="sarscape",
|
||
profile_code=resolved_profile_code,
|
||
root_dir=source_root,
|
||
task_dir=task_dir,
|
||
task_name=task_name,
|
||
task_alias=task_alias,
|
||
pair_key=pair_key,
|
||
run_key=resolved_run_key,
|
||
pair_meta=pair_meta,
|
||
started_at=run_started_at_text,
|
||
params=(
|
||
{
|
||
"timeout_seconds": timeout,
|
||
"workflow": "custom6",
|
||
"dem_base_file": DEM_BASE_FILE,
|
||
"target_resolution_m": CUSTOM_TARGET_RESOLUTION_M,
|
||
"filter_method": CUSTOM_FILTER_METHOD,
|
||
"unwrap_coh_threshold": CUSTOM_UNWRAP_COH_THRESHOLD,
|
||
"gcp_coh_threshold": CUSTOM_GCP_COH_THRESHOLD,
|
||
"gcp_number": CUSTOM_GCP_NUMBER,
|
||
"geocoding_coh_threshold": CUSTOM_GEOCODING_COH_THRESHOLD,
|
||
"geocoding_pixel_size_m": CUSTOM_GEOCODING_PIXEL_SIZE_M,
|
||
}
|
||
if normalized_workflow == "dinsar_custom"
|
||
else {
|
||
"timeout_seconds": timeout,
|
||
"workflow": "metatask",
|
||
"dem_base_file": DEM_BASE_FILE,
|
||
}
|
||
),
|
||
metrics={
|
||
"elapsed_seconds": elapsed,
|
||
},
|
||
native_output_dir=native_output_dir,
|
||
)
|
||
return {
|
||
"summary": {
|
||
"task_folders": 1,
|
||
"processed": 1,
|
||
"failed": 0,
|
||
"skipped": 0,
|
||
"auto_imported": auto_imported,
|
||
},
|
||
"log_lines": log_lines,
|
||
"task_results": [
|
||
{
|
||
"task_name": task_name,
|
||
"task_alias": task_alias,
|
||
"pair_key": pair_key,
|
||
"run_key": resolved_run_key,
|
||
"task_dir": task_dir,
|
||
"output_dir": output_dir,
|
||
"native_output_dir": native_output_dir,
|
||
"success": True,
|
||
"status": "ok",
|
||
"elapsed_seconds": elapsed,
|
||
}
|
||
],
|
||
"output_dirs": [output_dir],
|
||
"run_key": resolved_run_key,
|
||
"profile_code": resolved_profile_code,
|
||
}
|
||
|
||
|
||
# ---------------------------------------------------------------------------
|
||
# Inspect (pre-check) functions
|
||
# ---------------------------------------------------------------------------
|
||
|
||
def inspect_import(root_dir: str) -> Dict[str, Any]:
|
||
"""Pre-check Import readiness for a root directory."""
|
||
root_dir = _to_local_path(root_dir)
|
||
result: Dict[str, Any] = {
|
||
"workflow": "import",
|
||
"root_dir": root_dir,
|
||
"exists": bool(root_dir and os.path.isdir(root_dir)),
|
||
"ready": False,
|
||
"summary": {},
|
||
"warnings": [],
|
||
}
|
||
if not result["exists"]:
|
||
result["warnings"].append("root_dir does not exist.")
|
||
return result
|
||
|
||
task_folders = _collect_task_folders(root_dir)
|
||
scan_mode = "task_folder"
|
||
scan_targets = task_folders
|
||
if not task_folders:
|
||
scan_mode = "flat_folder"
|
||
scan_targets = sorted(
|
||
p for p in glob(os.path.join(root_dir, "*")) if os.path.isdir(p)
|
||
)
|
||
|
||
meta_count = 0
|
||
sml_count = 0
|
||
candidate_count = 0
|
||
for folder in scan_targets:
|
||
if scan_mode == "flat_folder":
|
||
candidates = [folder]
|
||
else:
|
||
candidates = [
|
||
os.path.join(folder, "master"),
|
||
os.path.join(folder, "slave"),
|
||
]
|
||
for candidate in candidates:
|
||
if not os.path.isdir(candidate):
|
||
continue
|
||
metas = glob(os.path.join(candidate, "*.meta.xml"))
|
||
smls = glob(os.path.join(candidate, "*.sml"))
|
||
meta_count += len(metas)
|
||
sml_count += len(smls)
|
||
if metas and not smls:
|
||
candidate_count += len(metas)
|
||
|
||
result["summary"] = {
|
||
"scan_mode": scan_mode,
|
||
"folder_count": len(scan_targets),
|
||
"meta_file_count": meta_count,
|
||
"existing_sml_count": sml_count,
|
||
"import_candidate_count": candidate_count,
|
||
}
|
||
result["ready"] = candidate_count > 0
|
||
if candidate_count == 0:
|
||
result["warnings"].append(
|
||
"No import candidates (*.meta.xml without *.sml)."
|
||
)
|
||
return result
|
||
|
||
|
||
def inspect_dinsar(root_dir: str) -> Dict[str, Any]:
|
||
"""Pre-check D-InSAR readiness. Includes Import status detection."""
|
||
root_dir = _to_local_path(root_dir)
|
||
dem_base_file = DEM_BASE_FILE
|
||
dem_ok = bool(
|
||
dem_base_file
|
||
and (os.path.isfile(dem_base_file) or os.path.isdir(dem_base_file))
|
||
)
|
||
|
||
result: Dict[str, Any] = {
|
||
"workflow": "dinsar",
|
||
"root_dir": root_dir,
|
||
"exists": bool(root_dir and os.path.isdir(root_dir)),
|
||
"ready": False,
|
||
"summary": {},
|
||
"warnings": [],
|
||
}
|
||
if not result["exists"]:
|
||
result["warnings"].append("root_dir does not exist.")
|
||
return result
|
||
|
||
task_folders = _collect_task_folders(root_dir)
|
||
ready_count = 0
|
||
need_import_count = 0
|
||
missing_structure = 0
|
||
|
||
for folder in task_folders:
|
||
master_dir = os.path.join(folder, "master")
|
||
slave_dir = os.path.join(folder, "slave")
|
||
if not os.path.isdir(master_dir) or not os.path.isdir(slave_dir):
|
||
missing_structure += 1
|
||
continue
|
||
master_has_sml = _has_sml(master_dir)
|
||
slave_has_sml = _has_sml(slave_dir)
|
||
if master_has_sml and slave_has_sml:
|
||
ready_count += 1
|
||
else:
|
||
master_has_meta = bool(_find_meta_files(master_dir))
|
||
slave_has_meta = bool(_find_meta_files(slave_dir))
|
||
if (master_has_sml or master_has_meta) and (
|
||
slave_has_sml or slave_has_meta
|
||
):
|
||
need_import_count += 1
|
||
else:
|
||
missing_structure += 1
|
||
|
||
result["summary"] = {
|
||
"task_folder_count": len(task_folders),
|
||
"ready_for_dinsar": ready_count,
|
||
"need_import_first": need_import_count,
|
||
"missing_structure": missing_structure,
|
||
"dem_base_file": dem_base_file or "(not configured)",
|
||
"dem_exists": dem_ok,
|
||
}
|
||
result["ready"] = (ready_count + need_import_count) > 0 and dem_ok
|
||
if not dem_ok:
|
||
result["warnings"].append(
|
||
"DEM path not configured or does not exist. "
|
||
"Set IDL_DINSAR_DEM_BASE_FILE in .env"
|
||
)
|
||
if len(task_folders) == 0:
|
||
result["warnings"].append("No Task_* folders found.")
|
||
if need_import_count > 0:
|
||
result["warnings"].append(
|
||
f"{need_import_count} folder(s) need Import first "
|
||
f"(will be auto-imported during D-InSAR)."
|
||
)
|
||
return result
|
||
|
||
|
||
# ---------------------------------------------------------------------------
|
||
# System status
|
||
# ---------------------------------------------------------------------------
|
||
|
||
def get_status() -> Dict[str, Any]:
|
||
"""Return ENVI/IDL system status and DEM configuration."""
|
||
idl_installed = bool(IDL_EXECUTABLE and os.path.isfile(IDL_EXECUTABLE))
|
||
is_running = is_any_process_running(["idl.exe", "idlde.exe", "taskengine.exe"])
|
||
runner_status = probe_envi_runner()
|
||
|
||
dem_ok = bool(
|
||
DEM_BASE_FILE
|
||
and (os.path.isfile(DEM_BASE_FILE) or os.path.isdir(DEM_BASE_FILE))
|
||
)
|
||
|
||
return {
|
||
"engine": "envipyengine",
|
||
"idl_installed": idl_installed,
|
||
"idl_executable": IDL_EXECUTABLE,
|
||
"idl_running": is_running,
|
||
"dem_base_file": DEM_BASE_FILE or "(not configured)",
|
||
"dem_exists": dem_ok,
|
||
"runner_python": runner_status.get("python_path", ""),
|
||
"runner_cwd": runner_status.get("cwd", ""),
|
||
"runner_ready": bool(runner_status.get("ready")),
|
||
"runner_returncode": runner_status.get("returncode"),
|
||
"runner_message": runner_status.get("message", ""),
|
||
}
|
||
|
||
|
||
# ---------------------------------------------------------------------------
|
||
# Run history (stored as JSON files in runtime dir)
|
||
# ---------------------------------------------------------------------------
|
||
|
||
_RUNS_DIR = os.path.join(RUNTIME_DIR, "runs")
|
||
|
||
|
||
def _save_run_record(record: Dict[str, Any]) -> None:
|
||
os.makedirs(_RUNS_DIR, exist_ok=True)
|
||
run_id = record.get("run_id", "unknown")
|
||
path = os.path.join(_RUNS_DIR, f"{run_id}.json")
|
||
with open(path, "w", encoding="utf-8") as fp:
|
||
json.dump(record, fp, ensure_ascii=False, indent=2)
|
||
|
||
|
||
def list_recent_runs(limit: int = 20) -> List[Dict[str, Any]]:
|
||
"""Return recent run records, newest first."""
|
||
if not os.path.isdir(_RUNS_DIR):
|
||
return []
|
||
files = sorted(
|
||
glob(os.path.join(_RUNS_DIR, "*.json")), reverse=True
|
||
)
|
||
runs: List[Dict[str, Any]] = []
|
||
for f in files[:limit]:
|
||
try:
|
||
with open(f, "r", encoding="utf-8") as fp:
|
||
runs.append(json.load(fp))
|
||
except Exception as exc:
|
||
print(f"[WARN] get_run_history: {exc}")
|
||
continue
|
||
return runs
|
||
|
||
|
||
# ---------------------------------------------------------------------------
|
||
# Top-level workflow runner (called by envi_runner_cli.py)
|
||
# ---------------------------------------------------------------------------
|
||
|
||
def run_workflow(
|
||
workflow: str,
|
||
root_dir: str,
|
||
num_to_process: int = 0,
|
||
timeout: int = DEFAULT_TIMEOUT,
|
||
job_id: Optional[str] = None,
|
||
) -> Dict[str, Any]:
|
||
"""Execute a complete workflow and persist the run record."""
|
||
timeout = min(timeout or DEFAULT_TIMEOUT, MAX_TIMEOUT)
|
||
run_started_at = datetime.utcnow()
|
||
run_id = run_started_at.strftime("%Y%m%d_%H%M%S") + f"_{workflow}"
|
||
started_at = run_started_at.isoformat(timespec="seconds") + "Z"
|
||
started = time.time()
|
||
profile_code = None
|
||
run_key = None
|
||
|
||
try:
|
||
if workflow == "import":
|
||
result = run_import_workflow(root_dir, num_to_process, timeout)
|
||
elif workflow == "dinsar":
|
||
profile_code = "metatask"
|
||
run_key = build_run_key("sarscape", profile_code, started_at=run_started_at)
|
||
result = run_dinsar_workflow(
|
||
root_dir,
|
||
num_to_process,
|
||
timeout,
|
||
job_id=job_id,
|
||
run_key=run_key,
|
||
profile_code=profile_code,
|
||
started_at=run_started_at,
|
||
)
|
||
elif workflow == "dinsar_custom":
|
||
profile_code = "custom6"
|
||
run_key = build_run_key("sarscape", profile_code, started_at=run_started_at)
|
||
result = run_dinsar_custom_workflow(
|
||
root_dir,
|
||
num_to_process,
|
||
timeout,
|
||
job_id=job_id,
|
||
run_key=run_key,
|
||
profile_code=profile_code,
|
||
started_at=run_started_at,
|
||
)
|
||
else:
|
||
raise ValueError(f"Unknown workflow: {workflow}")
|
||
status = "success"
|
||
error = None
|
||
except Exception as exc:
|
||
result = {"summary": {}, "log_lines": [str(exc)]}
|
||
status = "failed"
|
||
error = str(exc)
|
||
|
||
elapsed = round(time.time() - started, 1)
|
||
finished_at = datetime.utcnow().isoformat(timespec="seconds") + "Z"
|
||
|
||
# Write log file
|
||
os.makedirs(RUNTIME_DIR, exist_ok=True)
|
||
log_path = os.path.join(RUNTIME_DIR, f"{run_id}.log")
|
||
with open(log_path, "w", encoding="utf-8") as fp:
|
||
fp.write("\n".join(result.get("log_lines", [])))
|
||
|
||
record = {
|
||
"run_id": run_id,
|
||
"workflow": workflow,
|
||
"status": status,
|
||
"started_at": started_at,
|
||
"finished_at": finished_at,
|
||
"duration_seconds": elapsed,
|
||
"root_dir": root_dir,
|
||
"summary": result.get("summary", {}),
|
||
"task_results": result.get("task_results", []),
|
||
"output_dirs": result.get("output_dirs", []),
|
||
"run_key": result.get("run_key") or run_key,
|
||
"profile_code": result.get("profile_code") or profile_code,
|
||
"log_path": log_path,
|
||
"error": error,
|
||
}
|
||
_save_run_record(record)
|
||
|
||
# Clean up progress file
|
||
if job_id:
|
||
try:
|
||
pf = _progress_file_path(job_id)
|
||
if os.path.isfile(pf):
|
||
os.remove(pf)
|
||
except Exception as exc:
|
||
print(f"[WARN] run_workflow cleanup: {exc}")
|
||
|
||
if error:
|
||
raise RuntimeError(error)
|
||
return record
|
||
|
||
|
||
# ---------------------------------------------------------------------------
|
||
# Disp result extraction
|
||
# ---------------------------------------------------------------------------
|
||
|
||
import re as _re
|
||
import shutil as _shutil
|
||
|
||
|
||
def _get_dinsar_target_dir() -> str:
|
||
raw = _read_env("MONITOR_DINSAR_DIRS", "")
|
||
dirs = [p.strip() for p in raw.replace(";", ",").split(",") if p.strip()]
|
||
if not dirs:
|
||
raise ValueError("MONITOR_DINSAR_DIRS 未在 .env 中配置")
|
||
return dirs[0]
|
||
|
||
|
||
def extract_disp_results(root_dir: str, dest_dir: Optional[str] = None) -> Dict[str, Any]:
|
||
from .envi_extract import extract_disp_results as _extract_disp_results
|
||
|
||
return _extract_disp_results(root_dir, dest_dir)
|
||
"""将 Task_*/dinsar_results/ 下最新的 disp 文件复制到目标目录并重命名。
|
||
|
||
Args:
|
||
root_dir: 生产根目录（包含 Task_* 文件夹）
|
||
dest_dir: 目标目录（可选，默认使用 MONITOR_DINSAR_DIRS[0]）
|
||
"""
|
||
if dest_dir:
|
||
target_dir = _to_local_path(dest_dir)
|
||
if not os.path.isdir(target_dir):
|
||
raise ValueError(f"目标目录不存在: {dest_dir}")
|
||
else:
|
||
target_dir = _get_dinsar_target_dir()
|
||
os.makedirs(target_dir, exist_ok=True)
|
||
|
||
_pattern = _re.compile(r"out_ISARPTD_(\d{14})_rsp_disp$")
|
||
_extensions = ["", ".hdr", ".sml"]
|
||
|
||
processed = 0
|
||
copied = 0
|
||
skipped = 0
|
||
overwritten = 0
|
||
failed = 0
|
||
details: List[Dict[str, Any]] = []
|
||
|
||
task_dirs = sorted(
|
||
d for d in os.listdir(root_dir)
|
||
if d.startswith("Task_") and os.path.isdir(os.path.join(root_dir, d))
|
||
)
|
||
|
||
for task_name in task_dirs:
|
||
dinsar_results_dir = os.path.join(root_dir, task_name, "dinsar_results")
|
||
if not os.path.isdir(dinsar_results_dir):
|
||
continue
|
||
|
||
# Find all no-extension files matching the pattern
|
||
candidates = []
|
||
try:
|
||
for fname in os.listdir(dinsar_results_dir):
|
||
m = _pattern.match(fname)
|
||
if m and os.path.isfile(os.path.join(dinsar_results_dir, fname)):
|
||
candidates.append((m.group(1), fname))
|
||
except OSError:
|
||
continue
|
||
|
||
if not candidates:
|
||
continue
|
||
|
||
# Pick the one with the largest timestamp
|
||
candidates.sort(key=lambda x: x[0], reverse=True)
|
||
_, best_fname = candidates[0]
|
||
base_src = os.path.join(dinsar_results_dir, best_fname)
|
||
target_base = os.path.join(target_dir, f"{task_name}_geo_disp")
|
||
|
||
task_status = "ok"
|
||
task_copied = 0
|
||
task_skipped = 0
|
||
task_overwritten = 0
|
||
task_failed = 0
|
||
|
||
for ext in _extensions:
|
||
src = base_src + ext
|
||
dst = target_base + ext
|
||
if not os.path.isfile(src):
|
||
task_failed += 1
|
||
continue
|
||
if os.path.isfile(dst):
|
||
if os.path.getsize(src) == os.path.getsize(dst):
|
||
task_skipped += 1
|
||
skipped += 1
|
||
continue
|
||
else:
|
||
try:
|
||
_shutil.copy2(src, dst)
|
||
task_overwritten += 1
|
||
overwritten += 1
|
||
except OSError as e:
|
||
task_failed += 1
|
||
task_status = f"error: {e}"
|
||
else:
|
||
try:
|
||
_shutil.copy2(src, dst)
|
||
task_copied += 1
|
||
copied += 1
|
||
except OSError as e:
|
||
task_failed += 1
|
||
task_status = f"error: {e}"
|
||
|
||
failed += task_failed
|
||
processed += 1
|
||
details.append({
|
||
"task": task_name,
|
||
"target_name": f"{task_name}_geo_disp",
|
||
"status": task_status,
|
||
"copied": task_copied,
|
||
"skipped": task_skipped,
|
||
"overwritten": task_overwritten,
|
||
"failed": task_failed,
|
||
})
|
||
|
||
return {
|
||
"processed": processed,
|
||
"copied": copied,
|
||
"skipped": skipped,
|
||
"overwritten": overwritten,
|
||
"failed": failed,
|
||
"target_dir": target_dir,
|
||
"details": details,
|
||
}
|
||
|
||
|
||
def get_task_overview(root_dir: str) -> Dict[str, Any]:
|
||
from .envi_extract import get_task_overview as _get_task_overview
|
||
|
||
return _get_task_overview(root_dir)
|
||
"""扫描 root_dir 下所有 Task_* 文件夹，返回每个 Task 的处理状态。"""
|
||
try:
|
||
target_dir = _get_dinsar_target_dir()
|
||
except ValueError:
|
||
target_dir = None
|
||
|
||
if not os.path.isdir(root_dir):
|
||
raise ValueError(f"目录不存在: {root_dir}")
|
||
|
||
task_dirs = sorted(
|
||
d for d in os.listdir(root_dir)
|
||
if d.startswith("Task_") and os.path.isdir(os.path.join(root_dir, d))
|
||
)
|
||
|
||
tasks = []
|
||
summary = {"total": 0, "imported": 0, "dinsar_done": 0, "extracted": 0}
|
||
|
||
for task_name in task_dirs:
|
||
task_path = os.path.join(root_dir, task_name)
|
||
|
||
has_master = os.path.isdir(os.path.join(task_path, "master"))
|
||
has_slave = os.path.isdir(os.path.join(task_path, "slave"))
|
||
has_structure = has_master and has_slave
|
||
|
||
imported = False
|
||
for sub in ("master", "slave"):
|
||
sub_path = os.path.join(task_path, sub)
|
||
if os.path.isdir(sub_path):
|
||
if any(f.endswith(".sml") for f in os.listdir(sub_path)):
|
||
imported = True
|
||
break
|
||
|
||
dinsar_results_dir = os.path.join(task_path, "dinsar_results")
|
||
dinsar_done = False
|
||
if os.path.isdir(dinsar_results_dir):
|
||
dinsar_done = any(
|
||
_re.search(r"ISARPTD.*_rsp_disp$", f)
|
||
for f in os.listdir(dinsar_results_dir)
|
||
if os.path.isfile(os.path.join(dinsar_results_dir, f))
|
||
)
|
||
|
||
extracted = False
|
||
if target_dir:
|
||
extracted = os.path.isfile(os.path.join(target_dir, f"{task_name}_geo_disp"))
|
||
|
||
try:
|
||
mtime = os.path.getmtime(task_path)
|
||
last_modified = datetime.utcfromtimestamp(mtime).strftime("%Y-%m-%d %H:%M")
|
||
except OSError:
|
||
last_modified = "-"
|
||
|
||
tasks.append({
|
||
"task_name": task_name,
|
||
"has_structure": has_structure,
|
||
"imported": imported,
|
||
"dinsar_done": dinsar_done,
|
||
"extracted": extracted,
|
||
"last_modified": last_modified,
|
||
})
|
||
|
||
summary["total"] += 1
|
||
if imported:
|
||
summary["imported"] += 1
|
||
if dinsar_done:
|
||
summary["dinsar_done"] += 1
|
||
if extracted:
|
||
summary["extracted"] += 1
|
||
|
||
return {"tasks": tasks, "summary": summary, "target_dir": target_dir or ""}
|
||
|
||
|
||
# ---------------------------------------------------------------------------
|
||
# Backward-compatible re-exports from split modules
|
||
# These lazy imports avoid circular-import issues at module load time.
|
||
# Callers that import run_import_workflow etc. directly from envi_service
|
||
# will still work without any changes.
|
||
# ---------------------------------------------------------------------------
|
||
|
||
def __getattr__(name: str): # noqa: N807
|
||
_split_map = {
|
||
"run_import_workflow": ("envi_import", "run_import_workflow"),
|
||
"inspect_import": ("envi_import", "inspect_import"),
|
||
"run_dinsar_workflow": ("envi_dinsar", "run_dinsar_workflow"),
|
||
"run_dinsar_custom_workflow": ("envi_dinsar", "run_dinsar_custom_workflow"),
|
||
"inspect_dinsar": ("envi_dinsar", "inspect_dinsar"),
|
||
"extract_disp_results": ("envi_extract", "extract_disp_results"),
|
||
"get_task_overview": ("envi_extract", "get_task_overview"),
|
||
}
|
||
if name in _split_map:
|
||
mod_name, attr = _split_map[name]
|
||
import importlib
|
||
mod = importlib.import_module(f".{mod_name}", package=__name__.rsplit(".", 1)[0])
|
||
return getattr(mod, attr)
|
||
raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
|