chore: sync repository with current workspace state

.env.example

@@ -177,9 +177,26 @@ PYINT_DEM_MODE=local_fabdem
 PYINT_FABDEM_ROOT=
 # When PYINT_DEM_MODE=prepared_file, point this to the same prepared WGS84 DEM.
 PYINT_PREPARED_DEM_PATH=
+# 0 means do not derive looks from a target output grid.
+PYINT_DEFAULT_TARGET_GRID_SIZE_M=0
+# Source DEM resolution recorded in PyINT/Gamma run metadata.
+PYINT_DEM_RESOLUTION_M=30.0
 PYINT_OPENTOPO_DEM_TYPE=SRTMGL1
 PYINT_OPENTOPO_API_KEY=
 PYINT_DEM_STRICT=true
+# Gamma unwrap support and quality support reporting are intentionally separate.
+PYINT_UNWRAP_COH_THRESHOLD=0.05
+PYINT_PRODUCT_COH_THRESHOLD=0.20
+PYINT_GAMMA_NODATA_VALUE=-9999.0
+PYINT_GEO_INTERP=1
+PYINT_ATMCOR_ENABLED=false
+PYINT_ATMCOR_USE_FOR_DISP=false
+PYINT_REFLATTEN_ENABLED=true
+PYINT_REFLATTEN_MODEL=plane
+PYINT_REFLATTEN_COH_THRESHOLD=0.70
+PYINT_REFLATTEN_FALLBACK_COH_THRESHOLD=0.20
+PYINT_REFLATTEN_RANGE_STEP=32
+PYINT_REFLATTEN_AZIMUTH_STEP=32
 PYINT_ORBIT_POLICY=require_txt
 PYINT_ORBIT_POOL_TXT=D:\orbit_pools\envi
 PYINT_RECORD_INPUT_ASSETS=true

backend/app/config.py

@@ -265,9 +265,26 @@ class Settings(BaseSettings):
     PYINT_DEM_MODE: str = "local_fabdem"
     PYINT_FABDEM_ROOT: str = ""
     PYINT_PREPARED_DEM_PATH: str = ""
+    PYINT_DEM_RESOLUTION_M: float = 30.0
     PYINT_OPENTOPO_DEM_TYPE: str = "SRTMGL1"
     PYINT_OPENTOPO_API_KEY: str = ""
     PYINT_DEM_STRICT: bool = True
+    PYINT_UNWRAP_COH_THRESHOLD: float = 0.05
+    PYINT_PRODUCT_COH_THRESHOLD: float = 0.20
+    PYINT_REFERENCE_MODE: str = "none"
+    PYINT_REFERENCE_COH_THRESHOLD: float = 0.30
+    PYINT_DERAMP_MODE: str = "none"
+    PYINT_DERAMP_COH_THRESHOLD: float = 0.30
+    PYINT_GAMMA_NODATA_VALUE: float = -9999.0
+    PYINT_GEO_INTERP: str = "1"
+    PYINT_ATMCOR_ENABLED: bool = False
+    PYINT_ATMCOR_USE_FOR_DISP: bool = False
+    PYINT_REFLATTEN_ENABLED: bool = True
+    PYINT_REFLATTEN_MODEL: str = "plane"
+    PYINT_REFLATTEN_COH_THRESHOLD: float = 0.70
+    PYINT_REFLATTEN_FALLBACK_COH_THRESHOLD: float = 0.20
+    PYINT_REFLATTEN_RANGE_STEP: int = 32
+    PYINT_REFLATTEN_AZIMUTH_STEP: int = 32
     PYINT_ORBIT_POLICY: str = "require_txt"
     PYINT_ORBIT_POOL_TXT: str = ""
     PYINT_RECORD_INPUT_ASSETS: bool = True
@@ -491,6 +508,70 @@ class Settings(BaseSettings):
         if pyint_dem_mode not in {"local_fabdem", "opentopo", "prepared_file"}:
             pyint_dem_mode = "local_fabdem"
         object.__setattr__(self, "PYINT_DEM_MODE", pyint_dem_mode)
+        object.__setattr__(self, "PYINT_DEM_RESOLUTION_M", max(0.1, float(self.PYINT_DEM_RESOLUTION_M or 30.0)))
+        object.__setattr__(
+            self,
+            "PYINT_UNWRAP_COH_THRESHOLD",
+            min(1.0, max(0.0, float(self.PYINT_UNWRAP_COH_THRESHOLD or 0.05))),
+        )
+        object.__setattr__(
+            self,
+            "PYINT_PRODUCT_COH_THRESHOLD",
+            min(1.0, max(0.0, float(self.PYINT_PRODUCT_COH_THRESHOLD or 0.20))),
+        )
+        pyint_reference_mode = str(self.PYINT_REFERENCE_MODE or "none").strip().lower() or "none"
+        if pyint_reference_mode not in {"none", "coh_median"}:
+            pyint_reference_mode = "none"
+        object.__setattr__(self, "PYINT_REFERENCE_MODE", pyint_reference_mode)
+        object.__setattr__(
+            self,
+            "PYINT_REFERENCE_COH_THRESHOLD",
+            min(1.0, max(0.0, float(self.PYINT_REFERENCE_COH_THRESHOLD or 0.30))),
+        )
+        pyint_deramp_mode = str(self.PYINT_DERAMP_MODE or "none").strip().lower() or "none"
+        if pyint_deramp_mode not in {"none", "plane"}:
+            pyint_deramp_mode = "none"
+        object.__setattr__(self, "PYINT_DERAMP_MODE", pyint_deramp_mode)
+        object.__setattr__(
+            self,
+            "PYINT_DERAMP_COH_THRESHOLD",
+            min(1.0, max(0.0, float(self.PYINT_DERAMP_COH_THRESHOLD or 0.30))),
+        )
+        object.__setattr__(
+            self,
+            "PYINT_GAMMA_NODATA_VALUE",
+            float(self.PYINT_GAMMA_NODATA_VALUE if self.PYINT_GAMMA_NODATA_VALUE is not None else -9999.0),
+        )
+        pyint_geo_interp = str(self.PYINT_GEO_INTERP or "0").strip()
+        if pyint_geo_interp not in {"0", "1"}:
+            pyint_geo_interp = "1"
+        object.__setattr__(self, "PYINT_GEO_INTERP", pyint_geo_interp)
+        pyint_reflatten_model = str(self.PYINT_REFLATTEN_MODEL or "plane").strip().lower() or "plane"
+        if pyint_reflatten_model in {"linear"}:
+            pyint_reflatten_model = "plane"
+        if pyint_reflatten_model not in {"plane", "quadratic"}:
+            pyint_reflatten_model = "plane"
+        object.__setattr__(self, "PYINT_REFLATTEN_MODEL", pyint_reflatten_model)
+        object.__setattr__(
+            self,
+            "PYINT_REFLATTEN_COH_THRESHOLD",
+            min(1.0, max(0.0, float(self.PYINT_REFLATTEN_COH_THRESHOLD or 0.70))),
+        )
+        object.__setattr__(
+            self,
+            "PYINT_REFLATTEN_FALLBACK_COH_THRESHOLD",
+            min(1.0, max(0.0, float(self.PYINT_REFLATTEN_FALLBACK_COH_THRESHOLD or 0.20))),
+        )
+        object.__setattr__(
+            self,
+            "PYINT_REFLATTEN_RANGE_STEP",
+            max(1, int(self.PYINT_REFLATTEN_RANGE_STEP or 32)),
+        )
+        object.__setattr__(
+            self,
+            "PYINT_REFLATTEN_AZIMUTH_STEP",
+            max(1, int(self.PYINT_REFLATTEN_AZIMUTH_STEP or 32)),
+        )
         if not self.PYINT_OPENTOPO_DEM_TYPE:
             object.__setattr__(self, "PYINT_OPENTOPO_DEM_TYPE", "SRTMGL1")
         pyint_orbit_policy = str(self.PYINT_ORBIT_POLICY or "require_txt").strip().lower() or "require_txt"

backend/app/dinsar_engines/pyint_engine.py

@@ -8,7 +8,9 @@ from pathlib import Path
 from typing import Any, Dict, List
 
 from ..config import get_env_text, read_bool_env, settings
+from ..services.dinsar_completion_files import repair_managed_completion_files
 from ..services.dinsar_naming import write_run_metadata
+from ..services.isce2_result_validator import validate_isce2_result_files
 from ..services.pyint_input_assets_service import (
     get_pyint_dem_summary,
     get_pyint_orbit_context,
@@ -17,11 +19,33 @@ from ..services.pyint_input_assets_service import (
 )
 from ..services.pyint_service import (
     DEFAULT_AZIMUTH_LOOKS,
+    DEFAULT_DEM_RESOLUTION_M,
+    DEFAULT_DERAMP_COH_THRESHOLD,
+    DEFAULT_DERAMP_MODE,
+    DEFAULT_ATMCOR_ENABLED,
+    DEFAULT_ATMCOR_USE_FOR_DISP,
+    DEFAULT_GEO_INTERP,
     DEFAULT_PARALLEL_WORKERS,
+    DEFAULT_PRODUCT_COH_THRESHOLD,
     DEFAULT_RANGE_LOOKS,
+    DEFAULT_REFLATTEN_AZIMUTH_STEP,
+    DEFAULT_REFLATTEN_COH_THRESHOLD,
+    DEFAULT_REFLATTEN_ENABLED,
+    DEFAULT_REFLATTEN_FALLBACK_COH_THRESHOLD,
+    DEFAULT_REFLATTEN_MODEL,
+    DEFAULT_REFLATTEN_RANGE_STEP,
+    DEFAULT_REFERENCE_COH_THRESHOLD,
+    DEFAULT_REFERENCE_MODE,
+    DEFAULT_TARGET_GRID_SIZE_M,
+    DEFAULT_UNWRAP_COH_THRESHOLD,
     MAX_LOOKS,
     MAX_PARALLEL_WORKERS,
+    REFLATTEN_MODEL_CHOICES,
+    TARGET_GRID_SIZE_MAX_M,
+    TARGET_GRID_SIZE_MIN_M,
     build_project_name,
+    calculate_dem_oversampling,
+    calculate_looks_from_task_dir,
     check_pyint_environment,
     infer_scene_date_from_archives,
     infer_task_identity,
@@ -31,10 +55,11 @@ from ..services.pyint_service import (
     to_wsl_path,
     validate_pyint_root_dir,
 )
-from ..services.wsl_service import run_wsl_command
+from ..services.wsl_service import run_wsl_command_stream
 from .base import DinsarEngine, EngineAvailability, EngineProfile, RunRequest, RunResult
 
 RERUN_MODE_UNFINISHED_ONLY = "unfinished_only"
+DEFAULT_COHERENCE_MASK_THRESHOLD = DEFAULT_PRODUCT_COH_THRESHOLD
 
 
 def _read_env(name: str, default: str = "") -> str:
@@ -121,6 +146,85 @@ class PyintEngine(DinsarEngine):
     def _dem_mode(self) -> str:
         return str(getattr(settings, "PYINT_DEM_MODE", "local_fabdem") or "local_fabdem").strip().lower()
 
+    @property
+    def _dem_resolution_m(self) -> float:
+        return max(0.1, float(getattr(settings, "PYINT_DEM_RESOLUTION_M", DEFAULT_DEM_RESOLUTION_M) or DEFAULT_DEM_RESOLUTION_M))
+
+    @property
+    def _default_unwrap_coh_threshold(self) -> float:
+        return float(getattr(settings, "PYINT_UNWRAP_COH_THRESHOLD", DEFAULT_UNWRAP_COH_THRESHOLD) or DEFAULT_UNWRAP_COH_THRESHOLD)
+
+    @property
+    def _default_product_coh_threshold(self) -> float:
+        return float(getattr(settings, "PYINT_PRODUCT_COH_THRESHOLD", DEFAULT_PRODUCT_COH_THRESHOLD) or DEFAULT_PRODUCT_COH_THRESHOLD)
+
+    @property
+    def _default_reference_mode(self) -> str:
+        return str(getattr(settings, "PYINT_REFERENCE_MODE", DEFAULT_REFERENCE_MODE) or DEFAULT_REFERENCE_MODE).strip().lower()
+
+    @property
+    def _default_reference_coh_threshold(self) -> float:
+        return float(getattr(settings, "PYINT_REFERENCE_COH_THRESHOLD", DEFAULT_REFERENCE_COH_THRESHOLD) or DEFAULT_REFERENCE_COH_THRESHOLD)
+
+    @property
+    def _default_deramp_mode(self) -> str:
+        return str(getattr(settings, "PYINT_DERAMP_MODE", DEFAULT_DERAMP_MODE) or DEFAULT_DERAMP_MODE).strip().lower()
+
+    @property
+    def _default_deramp_coh_threshold(self) -> float:
+        return float(getattr(settings, "PYINT_DERAMP_COH_THRESHOLD", DEFAULT_DERAMP_COH_THRESHOLD) or DEFAULT_DERAMP_COH_THRESHOLD)
+
+    @property
+    def _gamma_nodata_value(self) -> float:
+        return float(getattr(settings, "PYINT_GAMMA_NODATA_VALUE", -9999.0) if getattr(settings, "PYINT_GAMMA_NODATA_VALUE", None) is not None else -9999.0)
+
+    @property
+    def _geo_interp(self) -> str:
+        value = str(getattr(settings, "PYINT_GEO_INTERP", DEFAULT_GEO_INTERP) or DEFAULT_GEO_INTERP).strip()
+        return value if value in {"0", "1"} else DEFAULT_GEO_INTERP
+
+    @property
+    def _atmcor_enabled(self) -> bool:
+        return bool(getattr(settings, "PYINT_ATMCOR_ENABLED", DEFAULT_ATMCOR_ENABLED))
+
+    @property
+    def _atmcor_use_for_disp(self) -> bool:
+        return bool(getattr(settings, "PYINT_ATMCOR_USE_FOR_DISP", DEFAULT_ATMCOR_USE_FOR_DISP))
+
+    @property
+    def _reflatten_enabled(self) -> bool:
+        return bool(getattr(settings, "PYINT_REFLATTEN_ENABLED", DEFAULT_REFLATTEN_ENABLED))
+
+    @property
+    def _reflatten_model(self) -> str:
+        value = str(getattr(settings, "PYINT_REFLATTEN_MODEL", DEFAULT_REFLATTEN_MODEL) or DEFAULT_REFLATTEN_MODEL).strip().lower()
+        if value == "linear":
+            value = "plane"
+        return value if value in REFLATTEN_MODEL_CHOICES else DEFAULT_REFLATTEN_MODEL
+
+    @property
+    def _reflatten_coh_threshold(self) -> float:
+        return float(getattr(settings, "PYINT_REFLATTEN_COH_THRESHOLD", DEFAULT_REFLATTEN_COH_THRESHOLD) or DEFAULT_REFLATTEN_COH_THRESHOLD)
+
+    @property
+    def _reflatten_fallback_coh_threshold(self) -> float:
+        return float(
+            getattr(
+                settings,
+                "PYINT_REFLATTEN_FALLBACK_COH_THRESHOLD",
+                DEFAULT_REFLATTEN_FALLBACK_COH_THRESHOLD,
+            )
+            or DEFAULT_REFLATTEN_FALLBACK_COH_THRESHOLD
+        )
+
+    @property
+    def _reflatten_range_step(self) -> int:
+        return max(1, int(getattr(settings, "PYINT_REFLATTEN_RANGE_STEP", DEFAULT_REFLATTEN_RANGE_STEP) or DEFAULT_REFLATTEN_RANGE_STEP))
+
+    @property
+    def _reflatten_azimuth_step(self) -> int:
+        return max(1, int(getattr(settings, "PYINT_REFLATTEN_AZIMUTH_STEP", DEFAULT_REFLATTEN_AZIMUTH_STEP) or DEFAULT_REFLATTEN_AZIMUTH_STEP))
+
     @property
     def _fabdem_root(self) -> str:
         return _read_env("PYINT_FABDEM_ROOT", "")
@@ -197,25 +301,39 @@ class PyintEngine(DinsarEngine):
                         "label": "强制重跑",
                         "type": "boolean",
                         "default": False,
+                        "section": "Execution",
                         "description": "删除当前 run_key 对应的工作区后重跑。",
                     },
+                    "target_grid_size_m": {
+                        "label": "目标网格尺寸（米）",
+                        "type": "number",
+                        "default": DEFAULT_TARGET_GRID_SIZE_M,
+                        "step": 1,
+                        "min": TARGET_GRID_SIZE_MIN_M,
+                        "max": TARGET_GRID_SIZE_MAX_M,
+                        "section": "Advanced",
+                        "description": "可选。仅在未手动填写 looks 时用于估算多视数；不会重采样 DEM 或改写 Gamma 产品。",
+                        "recommendation": "保持 0 使用显式或默认的 Gamma/PyINT looks。",
+                    },
                     "range_looks": {
-                        "label": "距离向多视",
+                        "label": "距离向多视（手动覆盖）",
                         "type": "number",
                         "default": DEFAULT_RANGE_LOOKS,
                         "step": 1,
                         "min": 1,
                         "max": MAX_LOOKS,
-                        "description": "PyINT 模板中的 range_looks。",
+                        "section": "Execution",
+                        "description": "PyINT/Gamma 模板中的 range_looks。",
                     },
                     "azimuth_looks": {
-                        "label": "方位向多视",
+                        "label": "方位向多视（手动覆盖）",
                         "type": "number",
                         "default": DEFAULT_AZIMUTH_LOOKS,
                         "step": 1,
                         "min": 1,
                         "max": MAX_LOOKS,
-                        "description": "PyINT 模板中的 azimuth_looks。",
+                        "section": "Execution",
+                        "description": "PyINT/Gamma 模板中的 azimuth_looks。",
                     },
                     "parallel_workers": {
                         "label": "并行数",
@@ -224,18 +342,121 @@ class PyintEngine(DinsarEngine):
                         "step": 1,
                         "min": 1,
                         "max": MAX_PARALLEL_WORKERS,
+                        "section": "Execution",
                         "description": "同步控制 raw2slc/coreg/diff/unwrap/geocode 的并行数。",
                     },
+                    "coherence_mask_threshold": {
+                        "label": "Coherence quality",
+                        "type": "number",
+                        "default": self._default_product_coh_threshold,
+                        "step": 0.05,
+                        "min": 0.0,
+                        "max": 1.0,
+                        "section": "Delivery",
+                        "description": "Only used for quality support statistics. It is not applied as a Python product mask.",
+                        "recommendation": "Use 0.20 by default for LT-1 single-pair reporting; raise it for stricter review maps.",
+                    },
+                    "unwrap_coh_threshold": {
+                        "label": "Unwrap coherence",
+                        "type": "number",
+                        "default": self._default_unwrap_coh_threshold,
+                        "step": 0.05,
+                        "min": 0.0,
+                        "max": 1.0,
+                        "section": "Advanced",
+                        "description": "Minimum coherence used by Gamma rascc_mask/mcf during unwrapping.",
+                        "recommendation": "Use 0.05 for ENVI-like permissive LT-1 unwrapping; raise it only when low-coherence bridges cause unwrap artifacts.",
+                    },
+                    "geo_interp": {
+                        "label": "Geocode interpolation",
+                        "type": "select",
+                        "default": self._geo_interp,
+                        "enum": ["0", "1"],
+                        "section": "Advanced",
+                        "description": "Gamma geocode_back interpolation mode: 0 nearest, 1 bicubic spline.",
+                    },
+                    "atmcor": {
+                        "label": "Gamma atmcor",
+                        "type": "boolean",
+                        "default": self._atmcor_enabled,
+                        "section": "Advanced",
+                        "description": "Run PyINT/Gamma atm_correction stage using atm_mod_2d/atm_sim_2d/sub_phase.",
+                    },
+                    "atmcor_use_for_disp": {
+                        "label": "Use atmcor for disp",
+                        "type": "boolean",
+                        "default": self._atmcor_use_for_disp,
+                        "section": "Advanced",
+                        "description": "Use the Gamma atmospheric-corrected unwrapped phase as dispmap input when available.",
+                    },
+                    "reflatten": {
+                        "label": "Gamma residual reflatten",
+                        "type": "boolean",
+                        "default": self._reflatten_enabled,
+                        "section": "Gamma Refinement",
+                        "description": "After unwrapping, fit and remove residual long-wavelength phase ramps with Gamma rascc_mask/quad_fit/quad_sub.",
+                        "recommendation": "Keep enabled for LT-1 D-InSAR unless validating the raw PyINT/Gamma baseline.",
+                    },
+                    "reflatten_model": {
+                        "label": "Reflatten model",
+                        "type": "select",
+                        "default": self._reflatten_model,
+                        "enum": ["plane", "quadratic"],
+                        "section": "Gamma Refinement",
+                        "description": "Gamma quad_fit model used for residual phase trend removal.",
+                        "recommendation": "plane is safer for single-pair production; use quadratic only when a clear curved residual ramp remains.",
+                    },
+                    "reflatten_coh_threshold": {
+                        "label": "Reflatten coherence",
+                        "type": "number",
+                        "default": self._reflatten_coh_threshold,
+                        "step": 0.05,
+                        "min": 0.0,
+                        "max": 1.0,
+                        "section": "Gamma Refinement",
+                        "description": "Coherence threshold used to build the fit mask.",
+                        "recommendation": "Keep the primary fit conservative at 0.70; the backend can retry with a looser fallback.",
+                    },
+                    "reflatten_fallback_coh_threshold": {
+                        "label": "Reflatten fallback coherence",
+                        "type": "number",
+                        "default": self._reflatten_fallback_coh_threshold,
+                        "step": 0.05,
+                        "min": 0.0,
+                        "max": 1.0,
+                        "section": "Gamma Refinement",
+                        "description": "Fallback coherence threshold if the primary reflatten fit does not have enough usable samples.",
+                    },
+                    "reflatten_range_step": {
+                        "label": "Reflatten range step",
+                        "type": "number",
+                        "default": self._reflatten_range_step,
+                        "step": 1,
+                        "min": 1,
+                        "section": "Gamma Refinement",
+                        "description": "Sampling step in range pixels for Gamma quad_fit control points.",
+                    },
+                    "reflatten_azimuth_step": {
+                        "label": "Reflatten azimuth step",
+                        "type": "number",
+                        "default": self._reflatten_azimuth_step,
+                        "step": 1,
+                        "min": 1,
+                        "section": "Gamma Refinement",
+                        "description": "Sampling step in azimuth lines for Gamma quad_fit control points.",
+                    },
                     "unwrap": {
                         "label": "执行解缠",
                         "type": "boolean",
                         "default": True,
+                        "section": "Execution",
                         "description": "关闭后仅做到差分干涉图，不做解缠。",
                     },
                     "geocode": {
                         "label": "执行地理编码",
                         "type": "boolean",
                         "default": True,
+                        "section": "Execution",
                         "description": "关闭后不导出地理编码结果。",
                     },
                 },
@@ -257,10 +478,36 @@ class PyintEngine(DinsarEngine):
                 return False
             return bool(value)
 
-        for key in ("force", "unwrap", "geocode"):
+        for key in ("force", "unwrap", "geocode", "atmcor", "atmcor_use_for_disp", "reflatten"):
             if key in normalized:
                 normalized[key] = _coerce_bool(normalized[key])
 
+        if "geo_interp" in normalized and normalized["geo_interp"] is not None:
+            value = str(normalized["geo_interp"] or "").strip()
+            if not value:
+                normalized.pop("geo_interp", None)
+            elif value not in {"0", "1"}:
+                raise ValueError("geo_interp must be 0 or 1.")
+            else:
+                normalized["geo_interp"] = value
+
+        if "target_grid_size_m" in normalized and str(normalized["target_grid_size_m"] or "").strip() == "":
+            normalized.pop("target_grid_size_m", None)
+
+        if "target_grid_size_m" in normalized and normalized["target_grid_size_m"] is not None:
+            try:
+                grid_size = float(normalized["target_grid_size_m"])
+            except (TypeError, ValueError) as exc:
+                raise ValueError("目标网格尺寸必须为数字。") from exc
+            if int(grid_size) != grid_size:
+                raise ValueError("目标网格尺寸必须使用整数米。")
+            grid_size = int(grid_size)
+            if grid_size < TARGET_GRID_SIZE_MIN_M or grid_size > TARGET_GRID_SIZE_MAX_M:
+                raise ValueError(
+                    f"目标网格尺寸必须在 {TARGET_GRID_SIZE_MIN_M} 到 {TARGET_GRID_SIZE_MAX_M} 米之间。"
+                )
+            normalized["target_grid_size_m"] = grid_size
+
         for key, maximum, label in (
             ("range_looks", MAX_LOOKS, "距离向多视"),
             ("azimuth_looks", MAX_LOOKS, "方位向多视"),
@@ -268,6 +515,9 @@ class PyintEngine(DinsarEngine):
         ):
             if key not in normalized or normalized[key] is None:
                 continue
+            if str(normalized[key]).strip() == "":
+                normalized.pop(key, None)
+                continue
             try:
                 parsed = int(normalized[key])
             except (TypeError, ValueError) as exc:
@@ -276,6 +526,59 @@ class PyintEngine(DinsarEngine):
                 raise ValueError(f"{label}必须在 1 到 {maximum} 之间。")
             normalized[key] = parsed
 
+        for mode_key, choices in (
+            ("reference_mode", {"none", "coh_median"}),
+            ("deramp_mode", {"none", "plane"}),
+            ("reflatten_model", {"plane", "linear", "quadratic"}),
+        ):
+            if mode_key not in normalized or normalized[mode_key] is None:
+                continue
+            value = str(normalized[mode_key] or "").strip().lower()
+            if not value:
+                normalized.pop(mode_key, None)
+                continue
+            if mode_key == "reflatten_model" and value == "linear":
+                value = "plane"
+            if value not in choices:
+                supported = ", ".join(sorted(choices))
+                raise ValueError(f"{mode_key} must be one of: {supported}.")
+            normalized[mode_key] = value
+
+        for threshold_key in (
+            "coherence_mask_threshold",
+            "unwrap_coh_threshold",
+            "reference_coh_threshold",
+            "deramp_coh_threshold",
+            "reflatten_coh_threshold",
+            "reflatten_fallback_coh_threshold",
+        ):
+            if threshold_key not in normalized or normalized[threshold_key] is None:
+                continue
+            if str(normalized[threshold_key]).strip() == "":
+                normalized.pop(threshold_key, None)
+                continue
+            try:
+                parsed_threshold = float(normalized[threshold_key])
+            except (TypeError, ValueError) as exc:
+                raise ValueError(f"{threshold_key} must be a number.") from exc
+            if parsed_threshold < 0.0 or parsed_threshold > 1.0:
+                raise ValueError(f"{threshold_key} must be between 0.0 and 1.0.")
+            normalized[threshold_key] = parsed_threshold
+
+        for step_key in ("reflatten_range_step", "reflatten_azimuth_step"):
+            if step_key not in normalized or normalized[step_key] is None:
+                continue
+            if str(normalized[step_key]).strip() == "":
+                normalized.pop(step_key, None)
+                continue
+            try:
+                parsed_step = int(normalized[step_key])
+            except (TypeError, ValueError) as exc:
+                raise ValueError(f"{step_key} must be an integer.") from exc
+            if parsed_step < 1:
+                raise ValueError(f"{step_key} must be greater than or equal to 1.")
+            normalized[step_key] = parsed_step
+
         return normalized
 
     def _has_completed_task_result(self, task_dir: str, profile_code: str) -> bool:
@@ -413,7 +716,10 @@ class PyintEngine(DinsarEngine):
         total_tasks = len(task_dirs)
         run_started_at = datetime.utcnow()
         run_started_at_text = run_started_at.isoformat(timespec="seconds") + "Z"
-        run_key = f"run_{run_started_at.strftime('%Y%m%dT%H%M%SZ')}_{self.engine_code}_{request.profile}"
+        managed_run_key = str(extra.get("__managed_run_key") or "").strip()
+        run_key = managed_run_key or f"run_{run_started_at.strftime('%Y%m%dT%H%M%SZ')}_{self.engine_code}_{request.profile}"
+        managed_run_dir_override = str(extra.get("__managed_run_dir") or "").strip()
+        managed_native_output_dir_override = str(extra.get("__managed_native_output_dir") or "").strip()
         progress_callback = request.progress_callback
 
         def emit_progress(event_type: str, **payload: Any) -> None:
@@ -426,9 +732,44 @@ class PyintEngine(DinsarEngine):
 
         timeout = max(60, int(request.timeout_seconds or self.default_timeout_seconds))
         force = bool(extra.get("force"))
-        range_looks = int(extra.get("range_looks", DEFAULT_RANGE_LOOKS))
-        azimuth_looks = int(extra.get("azimuth_looks", DEFAULT_AZIMUTH_LOOKS))
+        target_grid_size_m = int(extra.get("target_grid_size_m") or 0)
+        manual_range_looks = extra.get("range_looks")
+        manual_azimuth_looks = extra.get("azimuth_looks")
         parallel_workers = int(extra.get("parallel_workers", DEFAULT_PARALLEL_WORKERS))
+        dem_resolution_m = self._dem_resolution_m
+        dem_oversampling = calculate_dem_oversampling(
+            dem_resolution_m=dem_resolution_m,
+            target_grid_size_m=target_grid_size_m,
+        )
+        dem_lat_ovr = float(dem_oversampling["oversampling"])
+        dem_lon_ovr = float(dem_oversampling["oversampling"])
+        unwrap_coh_threshold = float(extra.get("unwrap_coh_threshold", self._default_unwrap_coh_threshold))
+        coherence_mask_threshold = float(extra.get("coherence_mask_threshold", self._default_product_coh_threshold))
+        reference_mode = "none"
+        reference_coh_threshold = float(self._default_reference_coh_threshold)
+        deramp_mode = "none"
+        deramp_coh_threshold = float(self._default_deramp_coh_threshold)
+        gamma_nodata_value = self._gamma_nodata_value
+        geo_interp = str(extra.get("geo_interp", self._geo_interp) or self._geo_interp).strip()
+        if geo_interp not in {"0", "1"}:
+            geo_interp = DEFAULT_GEO_INTERP
+        atmcor = bool(extra.get("atmcor", self._atmcor_enabled))
+        atmcor_use_for_disp = bool(extra.get("atmcor_use_for_disp", self._atmcor_use_for_disp)) if atmcor else False
+        reflatten = bool(extra.get("reflatten", self._reflatten_enabled))
+        reflatten_model = str(extra.get("reflatten_model", self._reflatten_model) or self._reflatten_model).strip().lower()
+        if reflatten_model == "linear":
+            reflatten_model = "plane"
+        if reflatten_model not in {"plane", "quadratic"}:
+            reflatten_model = DEFAULT_REFLATTEN_MODEL
+        reflatten_coh_threshold = float(extra.get("reflatten_coh_threshold", self._reflatten_coh_threshold))
+        reflatten_fallback_coh_threshold = float(
+            extra.get(
+                "reflatten_fallback_coh_threshold",
+                self._reflatten_fallback_coh_threshold,
+            )
+        )
+        reflatten_range_step = int(extra.get("reflatten_range_step", self._reflatten_range_step))
+        reflatten_azimuth_step = int(extra.get("reflatten_azimuth_step", self._reflatten_azimuth_step))
         unwrap = bool(extra.get("unwrap", True))
         geocode = bool(extra.get("geocode", True))
 
@@ -443,6 +784,57 @@ class PyintEngine(DinsarEngine):
         wsl_prepared_dem_path = to_wsl_path(prepared_dem_path) if prepared_dem_path else ""
         shared_orbit_context = get_pyint_orbit_context()
 
+        def resolve_pair_looks(task_dir: str) -> Dict[str, Any]:
+            manual_range = int(manual_range_looks) if manual_range_looks is not None else None
+            manual_azimuth = int(manual_azimuth_looks) if manual_azimuth_looks is not None else None
+            calculation: Dict[str, Any] = {}
+            error_text = ""
+
+            if target_grid_size_m > 0 and (manual_range is None or manual_azimuth is None):
+                try:
+                    calculation = calculate_looks_from_task_dir(
+                        task_dir,
+                        target_grid_size_m,
+                    )
+                except Exception as exc:
+                    error_text = str(exc)
+                    calculation = {
+                        "mode": "fallback_default",
+                        "target_resolution_m": target_grid_size_m,
+                        "error": error_text,
+                    }
+            elif manual_range is None or manual_azimuth is None:
+                calculation = {
+                    "mode": "gamma_default_looks",
+                    "target_resolution_m": None,
+                }
+
+            range_looks = manual_range
+            if range_looks is None:
+                range_looks = int(calculation.get("range_looks") or DEFAULT_RANGE_LOOKS)
+
+            azimuth_looks = manual_azimuth
+            if azimuth_looks is None:
+                azimuth_looks = int(calculation.get("azimuth_looks") or DEFAULT_AZIMUTH_LOOKS)
+
+            if manual_range is not None or manual_azimuth is not None:
+                calculation = {
+                    **calculation,
+                    "mode": "manual_override" if calculation else "manual",
+                    "manual_range_looks": manual_range,
+                    "manual_azimuth_looks": manual_azimuth,
+                }
+
+            calculation["resolved_range_looks"] = int(range_looks)
+            calculation["resolved_azimuth_looks"] = int(azimuth_looks)
+            calculation["target_grid_size_m"] = int(target_grid_size_m)
+            return {
+                "range_looks": int(range_looks),
+                "azimuth_looks": int(azimuth_looks),
+                "calculation": calculation,
+                "error": error_text,
+            }
+
         task_results: List[Dict[str, Any]] = []
         output_dirs: List[str] = []
         pairs_processed = 0
@@ -458,11 +850,19 @@ class PyintEngine(DinsarEngine):
             slave_date = task_identity["slave_date"]
 
             work_run_root = os.path.normpath(os.path.join(self._work_root, pair_key, run_key))
-            output_dir = os.path.normpath(os.path.join(self._output_root, pair_key, "runs", run_key, "native"))
+            run_dir = os.path.normpath(managed_run_dir_override) if managed_run_dir_override else os.path.normpath(
+                os.path.join(self._output_root, pair_key, "runs", run_key)
+            )
+            output_dir = (
+                os.path.normpath(managed_native_output_dir_override)
+                if managed_native_output_dir_override
+                else os.path.join(run_dir, "native")
+            )
             template_root = os.path.normpath(os.path.join(self._template_root, pair_key, run_key))
             project_name = build_project_name(pair_key, run_key)
             project_dir = os.path.join(work_run_root, project_name)
-            input_assets_dir = os.path.join(work_run_root, "input_assets")
+            # Keep input assets outside the run root because the WSL pipeline may delete run_root on --force.
+            input_assets_dir = os.path.join(self._work_root, pair_key, "input_assets", run_key)
 
             wsl_task_dir = to_wsl_path(task_dir)
             wsl_project_dir = to_wsl_path(project_dir)
@@ -663,6 +1063,45 @@ class PyintEngine(DinsarEngine):
                 else ""
             )
 
+            look_resolution = resolve_pair_looks(task_dir)
+            range_looks = int(look_resolution["range_looks"])
+            azimuth_looks = int(look_resolution["azimuth_looks"])
+            look_calculation = dict(look_resolution.get("calculation") or {})
+            look_message = (
+                f"PyINT looks resolved for {task_alias}: "
+                f"range={range_looks}, azimuth={azimuth_looks}, "
+                f"target_grid={target_grid_size_m or 'not_set'}m, mode={look_calculation.get('mode', 'unknown')}"
+            )
+            if look_resolution.get("error"):
+                look_message += f", fallback_reason={look_resolution['error']}"
+            emit_progress(
+                "log",
+                pair_index=pair_index,
+                pair_total=total_tasks,
+                task_name=task_name,
+                task_alias=task_alias,
+                pair_key=pair_key,
+                level="WARNING" if look_resolution.get("error") else "INFO",
+                source="looks",
+                message=look_message,
+            )
+            emit_progress(
+                "log",
+                pair_index=pair_index,
+                pair_total=total_tasks,
+                task_name=task_name,
+                task_alias=task_alias,
+                pair_key=pair_key,
+                level="INFO",
+                source="dem",
+                message=(
+                    f"PyINT DEM oversampling for {task_alias}: "
+                    f"dem_resolution={dem_resolution_m:g}m, target_grid={target_grid_size_m or 'not_set'}m, "
+                    f"dem_lat_ovr={dem_lat_ovr:g}, dem_lon_ovr={dem_lon_ovr:g}, "
+                    f"actual_grid={float(dem_oversampling.get('actual_grid_size_m') or 0.0):g}m"
+                ),
+            )
+
             cmd_parts = [
                 f"{quote_shell(self._python)} {quote_shell(self._pipeline_script)} {quote_shell(wsl_task_dir)}",
                 f"--project-dir {quote_shell(wsl_project_dir)}",
@@ -679,10 +1118,24 @@ class PyintEngine(DinsarEngine):
                 f"--orbit-policy {quote_shell(self._orbit_policy)}",
                 f"--range-looks {range_looks}",
                 f"--azimuth-looks {azimuth_looks}",
+                f"--dem-resolution-m {dem_resolution_m}",
+                f"--dem-lat-ovr {dem_lat_ovr}",
+                f"--dem-lon-ovr {dem_lon_ovr}",
                 f"--parallel-workers {parallel_workers}",
                 f"--master-date {quote_shell(master_date)}" if master_date else "",
                 f"--slave-date {quote_shell(slave_date)}" if slave_date else "",
                 f"--time-baseline-days {time_baseline_days}",
+                f"--target-grid-size-m {target_grid_size_m}",
+                f"--unwrap-coh-threshold {unwrap_coh_threshold}",
+                f"--coherence-mask-threshold {coherence_mask_threshold}",
+                f"--geo-interp {quote_shell(geo_interp)}",
+                f"--gamma-nodata-value {gamma_nodata_value}",
+                "--reflatten" if reflatten else "--no-reflatten",
+                f"--reflatten-model {quote_shell(reflatten_model)}",
+                f"--reflatten-coh-threshold {reflatten_coh_threshold}",
+                f"--reflatten-fallback-coh-threshold {reflatten_fallback_coh_threshold}",
+                f"--reflatten-range-step {reflatten_range_step}",
+                f"--reflatten-azimuth-step {reflatten_azimuth_step}",
                 f"--input-assets-dir {quote_shell(wsl_input_assets_dir)}" if wsl_input_assets_dir else "",
                 f"--input-assets-json {quote_shell(wsl_input_assets_json)}" if wsl_input_assets_json else "",
                 f"--lt1-precise-orbit-enabled {'true' if self._lt1_precise_orbit_enabled else 'false'}",
@@ -695,6 +1148,8 @@ class PyintEngine(DinsarEngine):
                 f"--lt1-precise-orbit-backup {'true' if self._lt1_precise_orbit_backup else 'false'}",
                 f"--lt1-precise-orbit-orb-filt-degree {self._lt1_precise_orbit_orb_filt_degree}",
                 "--unwrap" if unwrap else "--no-unwrap",
+                "--atmcor" if atmcor else "--no-atmcor",
+                "--atmcor-use-for-disp" if atmcor_use_for_disp else "--no-atmcor-use-for-disp",
                 "--geocode" if geocode else "--no-geocode",
             ]
             if self._dem_mode == "local_fabdem" and wsl_fabdem_root:
@@ -712,19 +1167,61 @@ class PyintEngine(DinsarEngine):
                 cmd_parts.append("--force")
 
             cmd = " ".join(part for part in cmd_parts if part)
-            rc, stdout, stderr = run_wsl_command(
+            def _emit_stream_log(level: str, source: str, text: str) -> None:
+                line = str(text or "").strip()
+                if not line:
+                    return
+                max_len = 2000
+                if len(line) > max_len:
+                    line = line[:max_len] + "...<truncated>"
+                emit_progress(
+                    "log",
+                    pair_index=pair_index,
+                    pair_total=total_tasks,
+                    task_name=task_name,
+                    task_alias=task_alias,
+                    pair_key=pair_key,
+                    level=level,
+                    source=source,
+                    message=line,
+                )
+
+            rc, stdout, stderr = run_wsl_command_stream(
                 cmd,
                 distro=self._distro,
                 timeout=timeout,
+                stdout_callback=lambda line: _emit_stream_log("INFO", "stdout", line),
+                stderr_callback=lambda line: _emit_stream_log("WARNING", "stderr", line),
             )
 
             success = rc == 0
+            error_text = stderr.strip() if stderr else ""
+            validation_result: Dict[str, Any] = {}
+            completion_files_result: Dict[str, Any] = {}
+            primary_file = ""
+            source_files: List[str] = []
             if success:
-                pairs_processed += 1
+                try:
                     os.makedirs(output_dir, exist_ok=True)
-                write_run_metadata(
-                    output_dir,
-                    {
+                    os.makedirs(run_dir, exist_ok=True)
+                    standard_disp_path = os.path.join(run_dir, "assets", "disp", "disp.tif")
+                    standard_coh_path = os.path.join(run_dir, "assets", "coh", "coh.tif")
+                    if geocode:
+                        validation_sources = [standard_disp_path]
+                        if os.path.isfile(standard_coh_path):
+                            validation_sources.append(standard_coh_path)
+                        validation_result = validate_isce2_result_files(
+                            standard_disp_path,
+                            validation_sources,
+                        )
+                        if not bool(validation_result.get("accepted")):
+                            issues = validation_result.get("issues") or []
+                            issue_text = "; ".join(str(item) for item in issues[:3]) or "unknown validation error"
+                            raise RuntimeError(f"PyINT standard GeoTIFF validation failed: {issue_text}")
+                        primary_file = str(validation_result.get("primary_file") or standard_disp_path)
+                        source_files = list(validation_result.get("source_files") or validation_sources)
+
+                    run_metadata = {
                         "run_key": run_key,
                         "pair_key": pair_key,
                         "task_name": task_name,
@@ -734,15 +1231,50 @@ class PyintEngine(DinsarEngine):
                         "source_root": os.path.normpath(request.root_dir),
                         "task_dir": os.path.normpath(task_dir),
                         "work_dir": work_run_root,
-                        "output_dir": output_dir,
+                        "output_dir": run_dir,
+                        "native_output_dir": output_dir,
                         "project_dir": project_dir,
+                        "runtime_id": settings.PYINT_RUNTIME_ID,
                         "started_at": run_started_at_text,
                         "finished_at": datetime.utcnow().isoformat(timespec="seconds") + "Z",
+                        "primary_file": primary_file,
+                        "source_files": source_files,
+                        "acceptance": validation_result,
                         "params": {
                             "force": force,
+                            "target_grid_size_m": target_grid_size_m,
+                            "dem_resolution_m": dem_resolution_m,
+                            "dem_oversampling": dem_oversampling,
+                            "dem_lat_ovr": dem_lat_ovr,
+                            "dem_lon_ovr": dem_lon_ovr,
                             "range_looks": range_looks,
                             "azimuth_looks": azimuth_looks,
+                            "manual_range_looks": manual_range_looks,
+                            "manual_azimuth_looks": manual_azimuth_looks,
+                            "look_calculation": look_calculation,
                             "parallel_workers": parallel_workers,
+                            "unwrap_coh_threshold": unwrap_coh_threshold,
+                            "coherence_quality_threshold": coherence_mask_threshold,
+                            "reference_mode": reference_mode,
+                            "reference_coh_threshold": reference_coh_threshold,
+                            "deramp_mode": deramp_mode,
+                            "deramp_coh_threshold": deramp_coh_threshold,
+                            "gamma_nodata_value": gamma_nodata_value,
+                            "geo_interp": geo_interp,
+                            "atmcor": atmcor,
+                            "atmcor_use_for_disp": atmcor_use_for_disp,
+                            "reflatten": reflatten,
+                            "reflatten_model": reflatten_model,
+                            "reflatten_coh_threshold": reflatten_coh_threshold,
+                            "reflatten_fallback_coh_threshold": reflatten_fallback_coh_threshold,
+                            "reflatten_range_step": reflatten_range_step,
+                            "reflatten_azimuth_step": reflatten_azimuth_step,
+                            "gamma_native_export": {
+                                "python_data_processing_applied": False,
+                                "coherence_mask_applied": False,
+                                "reference_applied": False,
+                                "deramp_applied": False,
+                            },
                             "unwrap": unwrap,
                             "geocode": geocode,
                         },
@@ -765,10 +1297,24 @@ class PyintEngine(DinsarEngine):
                         "policy_version": pair_meta.get("policy_version"),
                         "selection_strategy": pair_meta.get("selection_strategy"),
                         "input_assets": input_assets_summary,
-                    },
+                    }
+                    write_run_metadata(run_dir, run_metadata)
+                    write_run_metadata(output_dir, run_metadata)
+                    if geocode and primary_file:
+                        completion_files_result = repair_managed_completion_files(
+                            run_dir,
+                            primary_file=primary_file,
+                            source_files=source_files,
+                            run_meta=run_metadata,
                         )
-                output_dirs.append(output_dir)
-            else:
+                    output_dirs.append(run_dir)
+                    pairs_processed += 1
+                except Exception as exc:
+                    success = False
+                    error_text = str(exc)
+                    stderr = (stderr.rstrip() + "\n" + error_text) if stderr else error_text
+
+            if not success:
                 pairs_failed += 1
 
             emit_progress(
@@ -780,7 +1326,7 @@ class PyintEngine(DinsarEngine):
                 pair_key=pair_key,
                 success=success,
                 returncode=rc,
-                error=stderr.strip() if stderr else "",
+                error=error_text,
             )
             task_results.append(
                 {
@@ -791,13 +1337,45 @@ class PyintEngine(DinsarEngine):
                     "task_dir": task_dir,
                     "work_dir": work_run_root,
                     "project_dir": project_dir,
-                    "output_dir": output_dir,
+                    "run_dir": run_dir,
+                    "output_dir": run_dir,
+                    "native_output_dir": output_dir,
+                    "primary_file": primary_file,
+                    "source_files": source_files,
+                    "acceptance": validation_result,
+                    "completion_files": completion_files_result,
+                    "target_grid_size_m": target_grid_size_m,
+                    "dem_resolution_m": dem_resolution_m,
+                    "dem_oversampling": dem_oversampling,
+                    "dem_lat_ovr": dem_lat_ovr,
+                    "dem_lon_ovr": dem_lon_ovr,
+                    "range_looks": range_looks,
+                    "azimuth_looks": azimuth_looks,
+                    "manual_range_looks": manual_range_looks,
+                    "manual_azimuth_looks": manual_azimuth_looks,
+                    "look_calculation": look_calculation,
+                    "unwrap_coh_threshold": unwrap_coh_threshold,
+                    "coherence_quality_threshold": coherence_mask_threshold,
+                    "reference_mode": reference_mode,
+                    "reference_coh_threshold": reference_coh_threshold,
+                    "deramp_mode": deramp_mode,
+                    "deramp_coh_threshold": deramp_coh_threshold,
+                    "gamma_nodata_value": gamma_nodata_value,
+                    "geo_interp": geo_interp,
+                    "atmcor": atmcor,
+                    "atmcor_use_for_disp": atmcor_use_for_disp,
+                    "gamma_native_export": {
+                        "python_data_processing_applied": False,
+                        "coherence_mask_applied": False,
+                        "reference_applied": False,
+                        "deramp_applied": False,
+                    },
                     "command": cmd,
                     "success": success,
                     "returncode": rc,
                     "stdout_tail": stdout[-3000:] if stdout else "",
                     "stderr_tail": stderr[-3000:] if stderr else "",
-                    "error": stderr.strip() if stderr else "",
+                    "error": error_text,
                     "wsl_task_dir": wsl_task_dir,
                     "wsl_project_dir": wsl_project_dir,
                     "wsl_output_dir": wsl_output_dir,
@@ -849,9 +1427,32 @@ class PyintEngine(DinsarEngine):
                 "started_at": run_started_at_text,
                 "force": force,
                 "timeout_seconds": timeout,
-                "range_looks": range_looks,
-                "azimuth_looks": azimuth_looks,
+                "target_grid_size_m": target_grid_size_m,
+                "dem_resolution_m": dem_resolution_m,
+                "dem_oversampling": dem_oversampling,
+                "dem_lat_ovr": dem_lat_ovr,
+                "dem_lon_ovr": dem_lon_ovr,
+                "range_looks": last_task_result.get("range_looks"),
+                "azimuth_looks": last_task_result.get("azimuth_looks"),
+                "manual_range_looks": manual_range_looks,
+                "manual_azimuth_looks": manual_azimuth_looks,
                 "parallel_workers": parallel_workers,
+                "unwrap_coh_threshold": unwrap_coh_threshold,
+                "coherence_quality_threshold": coherence_mask_threshold,
+                "reference_mode": reference_mode,
+                "reference_coh_threshold": reference_coh_threshold,
+                "deramp_mode": deramp_mode,
+                "deramp_coh_threshold": deramp_coh_threshold,
+                "gamma_nodata_value": gamma_nodata_value,
+                "geo_interp": geo_interp,
+                "atmcor": atmcor,
+                "atmcor_use_for_disp": atmcor_use_for_disp,
+                "gamma_native_export": {
+                    "python_data_processing_applied": False,
+                    "coherence_mask_applied": False,
+                    "reference_applied": False,
+                    "deramp_applied": False,
+                },
                 "unwrap": unwrap,
                 "geocode": geocode,
                 "command": last_task_result.get("command", ""),

backend/app/routers/dinsar_production.py

@@ -268,6 +268,7 @@ async def submit_run(
         else:
             job_type = JOB_TYPE_PYINT_RUN
             max_attempts = PYINT_PRODUCTION_JOB_MAX_ATTEMPTS
+            create_managed_run = True
         if validation_summary is not None:
             validated_task_count = validation_summary.get("task_count", 0)
             payload["extra"].update(

backend/app/services/dinsar_production_service.py

@@ -27,6 +27,7 @@ from .workflow_service import workflow_service
 
 TASK_TYPE_DINSAR_PRODUCTION = "IDL_RUN_DINSAR"
 TASK_TYPE_ISCE2_DINSAR_PRODUCTION = "ISCE2_RUN"
+TASK_TYPE_PYINT_DINSAR_PRODUCTION = "PYINT_RUN"
 RUN_STATUS_PENDING = "PENDING"
 RUN_STATUS_RUNNING = "RUNNING"
 RUN_STATUS_COMPLETED = "COMPLETED"
@@ -75,6 +76,8 @@ def _task_type_for_engine(engine_code: str) -> str:
         return TASK_TYPE_DINSAR_PRODUCTION
     if normalized == "isce2":
         return TASK_TYPE_ISCE2_DINSAR_PRODUCTION
+    if normalized in {"pyint", "gamma"}:
+        return TASK_TYPE_PYINT_DINSAR_PRODUCTION
     raise ValueError(f"Unsupported engine for D-InSAR production run: {engine_code}")
 
 
@@ -84,6 +87,8 @@ def _workflow_name_for_engine(engine_code: str) -> str:
         return "dinsar_sarscape_production"
     if normalized == "isce2":
         return "dinsar_isce2_production"
+    if normalized in {"pyint", "gamma"}:
+        return "dinsar_pyint_gamma_production"
     raise ValueError(f"Unsupported engine for D-InSAR production run: {engine_code}")
 
 
@@ -93,6 +98,8 @@ def _workflow_step_name_for_engine(engine_code: str) -> str:
         return RUNS_STEP_NAME
     if normalized == "isce2":
         return "Execute ISCE2 D-InSAR items"
+    if normalized in {"pyint", "gamma"}:
+        return "Execute PyINT/Gamma D-InSAR items"
     raise ValueError(f"Unsupported engine for D-InSAR production run: {engine_code}")
 
 
@@ -329,6 +336,82 @@ def _execution_dir(item: DinsarProductionRunItemORM, run_key: str) -> str:
     return os.path.join(item.results_root_dir, "runs", run_key)
 
 
+def _first_text(*values: Any) -> str:
+    for value in values:
+        text = str(value or "").strip()
+        if text:
+            return text
+    return ""
+
+
+def _read_json_if_exists(path: str) -> Dict[str, Any]:
+    text = str(path or "").strip()
+    if not text or not os.path.isfile(text):
+        return {}
+    try:
+        with open(text, "r", encoding="utf-8") as fp:
+            payload = json.load(fp)
+        return payload if isinstance(payload, dict) else {}
+    except Exception:
+        return {}
+
+
+def _maybe_join(base: str, *parts: str) -> str:
+    text = str(base or "").strip()
+    if not text:
+        return ""
+    return os.path.normpath(os.path.join(text, *parts))
+
+
+def _build_output_paths(
+    *,
+    engine_code: str,
+    item: DinsarProductionRunItemORM,
+    run_key: str,
+    output_dir: str,
+    manifest_path: Optional[str] = None,
+) -> Dict[str, Any]:
+    run_dir = os.path.normpath(str(output_dir or _execution_dir(item, run_key)))
+    native_dir = _maybe_join(run_dir, "native")
+    paths: Dict[str, Any] = {
+        "run_dir": run_dir,
+        "native_dir": native_dir,
+        "assets_dir": _maybe_join(run_dir, "assets"),
+        "quality_dir": _maybe_join(run_dir, "quality"),
+        "manifest_path": str(manifest_path or "").strip(),
+    }
+
+    if str(engine_code or "").strip().lower() in {"pyint", "gamma"}:
+        pair_key = _first_text(item.pair_key, os.path.basename(os.path.dirname(os.path.dirname(run_dir))))
+        project_name = f"{pair_key}_{run_key}" if pair_key and run_key else ""
+        work_root = _maybe_join(settings.PYINT_WORK_ROOT, pair_key, run_key)
+        project_dir = _maybe_join(work_root, project_name) if project_name else ""
+
+        summary_payload = _read_json_if_exists(_maybe_join(native_dir, "pyint_run_summary.json"))
+        summary_project_dir = _first_text(summary_payload.get("project_dir"))
+        project_dir = summary_project_dir or project_dir
+
+        master_date = _first_text(summary_payload.get("master_date"))
+        slave_date = _first_text(summary_payload.get("slave_date"))
+        pair_name = f"{master_date}-{slave_date}" if master_date and slave_date else ""
+        ifgrams_dir = _maybe_join(project_dir, "ifgrams", pair_name) if pair_name else _maybe_join(project_dir, "ifgrams")
+
+        paths.update(
+            {
+                "work_dir": work_root,
+                "project_dir": project_dir,
+                "ifgrams_dir": ifgrams_dir,
+                "reflatten_dir": _maybe_join(run_dir, "gamma_reflatten"),
+                "native_reflatten_dir": _maybe_join(native_dir, "reflatten"),
+                "pyint_summary_path": _maybe_join(native_dir, "pyint_run_summary.json"),
+                "stdout_log": _maybe_join(work_root, "pyint.stdout.log"),
+                "stderr_log": _maybe_join(work_root, "pyint.stderr.log"),
+            }
+        )
+
+    return paths
+
+
 def _sanitize_pointer_fragment(value: str, default: str) -> str:
     text = _SAFE_POINTER_RE.sub("_", str(value or "").strip()).strip("._")
     return text or default
@@ -616,6 +699,7 @@ class DinsarProductionService:
         )
         result = await db.execute(stmt)
         runs = result.scalars().all()
+        run_ids = [run.run_id for run in runs if run.run_id]
         pending_reconcile = [
             run
             for run in runs
@@ -636,6 +720,15 @@ class DinsarProductionService:
                 ) or changed
             if changed:
                 await db.commit()
+        items_by_run_id: Dict[str, List[DinsarProductionRunItemORM]] = {}
+        if run_ids:
+            items_result = await db.execute(
+                select(DinsarProductionRunItemORM)
+                .where(DinsarProductionRunItemORM.run_id.in_(run_ids))
+                .order_by(DinsarProductionRunItemORM.order_index.asc(), DinsarProductionRunItemORM.id.asc())
+            )
+            for item in items_result.scalars().all():
+                items_by_run_id.setdefault(item.run_id, []).append(item)
         return {
             "runs": [
                 {
@@ -656,6 +749,29 @@ class DinsarProductionService:
                     "completed_items": run.completed_items,
                     "failed_items": run.failed_items,
                     "skipped_items": run.skipped_items,
+                    "items": [
+                        {
+                            "task_name": item.task_name,
+                            "task_alias": item.task_alias,
+                            "pair_key": item.pair_key,
+                            "status": item.status,
+                            "current_step": item.current_step,
+                            "latest_run_key": item.latest_run_key,
+                            "latest_output_dir": item.latest_output_dir,
+                            "latest_manifest_path": item.latest_manifest_path,
+                            "last_error": item.last_error,
+                            "paths": _build_output_paths(
+                                engine_code=run.engine_code,
+                                item=item,
+                                run_key=str(item.latest_run_key or ""),
+                                output_dir=str(item.latest_output_dir or _execution_dir(item, str(item.latest_run_key or ""))),
+                                manifest_path=item.latest_manifest_path,
+                            )
+                            if item.latest_run_key
+                            else {},
+                        }
+                        for item in items_by_run_id.get(run.run_id, [])[:5]
+                    ],
                 }
                 for run in runs
             ],

backend/app/services/job_handlers.py

@@ -2058,6 +2058,25 @@ async def _handle_queued_engine_run(
             pair_index = max(0, int(event.get("pair_index") or 0))
             task_label = str(event.get("task_alias") or event.get("task_name") or "").strip()
 
+            if event_type == "log":
+                level = str(event.get("level") or "INFO").strip().upper()
+                if level not in {"DEBUG", "INFO", "WARNING", "ERROR"}:
+                    level = "INFO"
+                source = str(event.get("source") or "").strip()
+                message = str(event.get("message") or "").strip()
+                if not message:
+                    continue
+                label = task_label or str(progress_state.get("pair_label") or "").strip() or "pair"
+                prefix = f"{engine_title} {pair_index}/{pair_total} {label}"
+                if source:
+                    prefix = f"{prefix} {source}"
+                await task_service.add_log(
+                    job.task_id,
+                    level,
+                    f"{prefix}: {message}",
+                )
+                continue
+
             if event_type == "pair_started":
                 progress = min(
                     90,
@@ -2496,7 +2515,22 @@ async def _run_wsl_dinsar_production_controller(
                         if event is None:
                             return
                         event_type = str(event.get("event") or "").strip().lower()
-                        if event_type == "pair_started":
+                        if event_type == "log":
+                            level = str(event.get("level") or "INFO").strip().upper()
+                            if level not in {"DEBUG", "INFO", "WARNING", "ERROR"}:
+                                level = "INFO"
+                            source = str(event.get("source") or "").strip()
+                            message = str(event.get("message") or "").strip()
+                            if message:
+                                prefix = f"[{item_index}/{total_items}] {engine_title} {item_label}"
+                                if source:
+                                    prefix = f"{prefix} {source}"
+                                await task_service.add_log(
+                                    job.task_id,
+                                    level,
+                                    f"{prefix}: {message}",
+                                )
+                        elif event_type == "pair_started":
                             progress_state["message"] = (
                                 f"[{engine_code}/{run.profile_code}] Running "
                                 f"{item_index}/{total_items}: {item_label}"
@@ -2892,6 +2926,52 @@ async def _handle_isce2_run(job: SystemJobORM) -> None:
 
 
 async def _handle_pyint_run(job: SystemJobORM) -> None:
+    production_run_id = str((job.payload or {}).get("production_run_id") or "").strip()
+    if production_run_id:
+        try:
+            await _run_wsl_dinsar_production_controller(
+                job,
+                engine_code="pyint",
+                engine_title="PyINT/Gamma",
+                fallback_timeout_seconds=settings.PYINT_DEFAULT_TIMEOUT_SECONDS,
+            )
+        except Exception as exc:
+            latest_message = f"PyINT/Gamma D-InSAR production controller failed: {exc}"
+            try:
+                async with AsyncSessionLocal() as db:
+                    run = await dinsar_production_service.get_run(production_run_id, db)
+                    if run is not None and str(run.status or "").strip().upper() not in {"COMPLETED", "FAILED", "CANCELLED"}:
+                        summary_payload = dict(run.summary_json or {})
+                        summary_payload["controller_error"] = str(exc)
+                        await dinsar_production_service.finalize_run(
+                            run,
+                            db=db,
+                            status="FAILED",
+                            summary_payload=summary_payload,
+                            latest_message=latest_message,
+                        )
+                        dinsar_production_service.append_run_log(
+                            run.run_id,
+                            f"[controller-failed] {exc}",
+                        )
+            except Exception:
+                pass
+
+            try:
+                current_task = await task_service.get_task(job.task_id)
+                if current_task and current_task.status not in {"COMPLETED", "FAILED", "CANCELLED"}:
+                    await task_service.add_log(job.task_id, "ERROR", latest_message)
+                    await task_service.update_task(
+                        job.task_id,
+                        status="FAILED",
+                        progress=100,
+                        message=latest_message,
+                    )
+            except Exception:
+                pass
+            raise
+        return
+
     await _handle_queued_engine_run(
         job,
         engine_title="PyINT",

backend/app/services/pyint_input_assets_service.py

@@ -316,6 +316,7 @@ def get_pyint_dem_summary() -> Dict[str, Any]:
             "hdr_exists": bool(prepared_dem_info.get("hdr_exists")),
             "vrt_exists": bool(prepared_dem_info.get("vrt_exists")),
         },
+        "configured_resolution_m": float(getattr(settings, "PYINT_DEM_RESOLUTION_M", 30.0) or 30.0),
         "opentopo_dem_type": opentopo_dem_type,
         "opentopo_api_key_configured": bool(opentopo_api_key),
         "status": status,

backend/app/services/pyint_service.py

@@ -4,6 +4,8 @@ from __future__ import annotations
 import os
 import re
 import shlex
+import math
+import defusedxml.ElementTree as ET
 from dataclasses import dataclass, field
 from datetime import datetime
 from pathlib import Path
@@ -11,12 +13,83 @@ from typing import Any, Dict, Iterable, List, Optional
 
 from ..config import get_env_text, read_bool_env, settings
 from .dinsar_naming import PAIR_META_FILENAME, build_fallback_pair_key, find_json_sidecar
-from .wsl_service import run_wsl_command
+from .wsl_service import run_wsl_exec
 
 
 LT1_INPUT_GLOBS = ("LT1*.tar.gz", "LT1*.tiff")
 DEFAULT_RANGE_LOOKS = 2
 DEFAULT_AZIMUTH_LOOKS = 2
+DEFAULT_DEM_RESOLUTION_M = 30.0
+DEFAULT_UNWRAP_COH_THRESHOLD = 0.05
+DEFAULT_PRODUCT_COH_THRESHOLD = 0.20
+DEFAULT_REFERENCE_MODE = "none"
+DEFAULT_REFERENCE_COH_THRESHOLD = 0.30
+DEFAULT_DERAMP_MODE = "none"
+DEFAULT_DERAMP_COH_THRESHOLD = 0.30
+DEFAULT_GEO_INTERP = "1"
+DEFAULT_ATMCOR_ENABLED = False
+DEFAULT_ATMCOR_USE_FOR_DISP = False
+DEFAULT_REFLATTEN_ENABLED = True
+DEFAULT_REFLATTEN_MODEL = "plane"
+DEFAULT_REFLATTEN_COH_THRESHOLD = 0.70
+DEFAULT_REFLATTEN_FALLBACK_COH_THRESHOLD = 0.20
+DEFAULT_REFLATTEN_RANGE_STEP = 32
+DEFAULT_REFLATTEN_AZIMUTH_STEP = 32
+DEM_OVERSAMPLING_MIN = 0.25
+DEM_OVERSAMPLING_MAX = 16.0
+REFERENCE_MODE_CHOICES = {"none", "coh_median"}
+DERAMP_MODE_CHOICES = {"none", "plane"}
+REFLATTEN_MODEL_CHOICES = {"plane", "linear", "quadratic"}
+
+
+def _read_default_target_grid_size_m() -> int:
+    for name in ("PYINT_DEFAULT_TARGET_GRID_SIZE_M",):
+        text = str(get_env_text(name, "") or "").strip()
+        if not text:
+            continue
+        try:
+            value = float(text)
+        except (TypeError, ValueError):
+            continue
+        if value > 0:
+            return int(value)
+    return 0
+
+
+def _read_float_env(names: Iterable[str], default: float) -> float:
+    for name in names:
+        text = str(get_env_text(name, "") or "").strip()
+        if not text:
+            continue
+        try:
+            value = float(text)
+        except (TypeError, ValueError):
+            continue
+        if math.isfinite(value):
+            return value
+    return float(default)
+
+
+DEFAULT_TARGET_GRID_SIZE_M = _read_default_target_grid_size_m()
+TARGET_GRID_SIZE_MIN_M = 0
+TARGET_GRID_SIZE_MAX_M = 100
+DEFAULT_DEM_RESOLUTION_M = _read_float_env(("PYINT_DEM_RESOLUTION_M",), DEFAULT_DEM_RESOLUTION_M)
+DEFAULT_UNWRAP_COH_THRESHOLD = _read_float_env(
+    ("PYINT_UNWRAP_COH_THRESHOLD",),
+    DEFAULT_UNWRAP_COH_THRESHOLD,
+)
+DEFAULT_PRODUCT_COH_THRESHOLD = _read_float_env(
+    ("PYINT_PRODUCT_COH_THRESHOLD", "PYINT_COHERENCE_MASK_THRESHOLD"),
+    DEFAULT_PRODUCT_COH_THRESHOLD,
+)
+DEFAULT_REFERENCE_COH_THRESHOLD = _read_float_env(
+    ("PYINT_REFERENCE_COH_THRESHOLD",),
+    DEFAULT_REFERENCE_COH_THRESHOLD,
+)
+DEFAULT_DERAMP_COH_THRESHOLD = _read_float_env(
+    ("PYINT_DERAMP_COH_THRESHOLD",),
+    DEFAULT_DERAMP_COH_THRESHOLD,
+)
 DEFAULT_PARALLEL_WORKERS = 1
 MAX_LOOKS = 32
 MAX_PARALLEL_WORKERS = 16
@@ -76,6 +149,180 @@ def normalize_date_text(value: Any) -> str:
     return ""
 
 
+def _local_xml_tag_name(tag: Any) -> str:
+    text = str(tag or "")
+    return text.split("}")[-1] if "}" in text else text
+
+
+def _read_xml_first_parameter(xml_file: str, names: Iterable[str]) -> Optional[str]:
+    path = os.path.normpath(str(xml_file or "").strip())
+    if not path or not os.path.isfile(path):
+        return None
+    wanted = {str(name or "").strip().lower() for name in names if str(name or "").strip()}
+    if not wanted:
+        return None
+    try:
+        tree = ET.parse(path)
+        root = tree.getroot()
+    except Exception:
+        return None
+    for elem in root.iter():
+        local_name = _local_xml_tag_name(elem.tag).lower()
+        if local_name in wanted and elem.text and str(elem.text).strip():
+            return str(elem.text).strip()
+    return None
+
+
+def _read_scene_geometry_metadata(metadata_path: str) -> Dict[str, Any]:
+    source = os.path.normpath(str(metadata_path or "").strip())
+    range_spacing = _read_xml_first_parameter(
+        source,
+        ("PixelSpacingRg", "columnSpacing", "slantRange", "range_pixel_spacing"),
+    )
+    azimuth_spacing = _read_xml_first_parameter(
+        source,
+        ("PixelSpacingAz", "rowSpacing", "projectedSpacingAzimuth", "azimuth_pixel_spacing"),
+    )
+    incidence_angle = _read_xml_first_parameter(
+        source,
+        ("IncidenceAngle", "incidence_angle"),
+    )
+    if not all((range_spacing, azimuth_spacing, incidence_angle)):
+        raise ValueError(f"Cannot read range/azimuth spacing and incidence angle from: {source}")
+    return {
+        "source": source,
+        "range_pixel_spacing_m": float(range_spacing),
+        "azimuth_pixel_spacing_m": float(azimuth_spacing),
+        "incidence_angle_deg": float(incidence_angle),
+    }
+
+
+def _scene_geometry_metadata_candidates(directory: str, patterns: Iterable[str]) -> List[str]:
+    root = os.path.normpath(str(directory or "").strip())
+    if not root or not os.path.isdir(root):
+        return []
+    candidates: List[str] = []
+    for pattern in patterns:
+        candidates.extend(str(path) for path in Path(root).glob(pattern) if path.is_file())
+    return [
+        os.path.normpath(path)
+        for path in sorted(
+            set(candidates),
+            key=lambda item: (0 if item.lower().endswith(".sml") else 1, item.lower()),
+        )
+    ]
+
+
+def resolve_scene_geometry_metadata_files(scene_dir: str) -> List[str]:
+    return _scene_geometry_metadata_candidates(
+        scene_dir,
+        (
+            "*.sml",
+            "*.SML",
+            "*.meta.xml",
+            "*.META.XML",
+        ),
+    )
+
+
+def resolve_scene_geometry_metadata_file(scene_dir: str) -> str:
+    candidates = resolve_scene_geometry_metadata_files(scene_dir)
+    return candidates[0] if candidates else ""
+
+
+def calculate_looks_from_scene_metadata(
+    *,
+    master_metadata: str,
+    slave_metadata: str,
+    target_resolution_m: float,
+) -> Dict[str, Any]:
+    target_resolution = float(target_resolution_m)
+    if target_resolution <= 0:
+        raise ValueError("target_resolution_m must be greater than 0")
+
+    master = _read_scene_geometry_metadata(master_metadata)
+    slave = _read_scene_geometry_metadata(slave_metadata)
+
+    avg_azimuth = (
+        float(master["azimuth_pixel_spacing_m"]) + float(slave["azimuth_pixel_spacing_m"])
+    ) / 2.0
+    master_ground_range = float(master["range_pixel_spacing_m"]) / math.sin(
+        math.radians(float(master["incidence_angle_deg"]))
+    )
+    slave_ground_range = float(slave["range_pixel_spacing_m"]) / math.sin(
+        math.radians(float(slave["incidence_angle_deg"]))
+    )
+    avg_ground_range = (master_ground_range + slave_ground_range) / 2.0
+
+    range_ratio = target_resolution / avg_ground_range
+    azimuth_ratio = target_resolution / avg_azimuth
+    range_looks = max(1, int(math.floor(range_ratio + 0.5)))
+    azimuth_looks = max(1, int(math.floor(azimuth_ratio + 0.5)))
+
+    return {
+        "mode": "target_grid_size",
+        "target_resolution_m": target_resolution,
+        "range_looks": range_looks,
+        "azimuth_looks": azimuth_looks,
+        "avg_ground_range_spacing_m": avg_ground_range,
+        "avg_azimuth_spacing_m": avg_azimuth,
+        "range_look_ratio": range_ratio,
+        "azimuth_look_ratio": azimuth_ratio,
+        "resolved_ground_range_spacing_m": avg_ground_range * range_looks,
+        "resolved_azimuth_spacing_m": avg_azimuth * azimuth_looks,
+        "master": master,
+        "slave": slave,
+    }
+
+
+def calculate_looks_from_task_dir(task_dir: str, target_resolution_m: float) -> Dict[str, Any]:
+    task_root = os.path.normpath(str(task_dir or "").strip())
+    master_candidates = resolve_scene_geometry_metadata_files(os.path.join(task_root, "master"))
+    slave_candidates = resolve_scene_geometry_metadata_files(os.path.join(task_root, "slave"))
+    if not master_candidates or not slave_candidates:
+        raise ValueError(f"Cannot find SML/meta XML metadata under task: {task_root}")
+    errors: List[str] = []
+    for master_metadata in master_candidates:
+        for slave_metadata in slave_candidates:
+            try:
+                return calculate_looks_from_scene_metadata(
+                    master_metadata=master_metadata,
+                    slave_metadata=slave_metadata,
+                    target_resolution_m=target_resolution_m,
+                )
+            except Exception as exc:
+                errors.append(f"{os.path.basename(master_metadata)} + {os.path.basename(slave_metadata)}: {exc}")
+    detail = "; ".join(errors[:3]) if errors else "unknown metadata parsing error"
+    raise ValueError(f"Cannot calculate looks from task metadata under {task_root}: {detail}")
+
+
+def calculate_dem_oversampling(
+    *,
+    dem_resolution_m: float,
+    target_grid_size_m: float,
+) -> Dict[str, Any]:
+    dem_resolution = float(dem_resolution_m or 0.0)
+    target_grid = float(target_grid_size_m or 0.0)
+    if not math.isfinite(dem_resolution) or dem_resolution <= 0:
+        dem_resolution = DEFAULT_DEM_RESOLUTION_M
+
+    raw_factor = dem_resolution / target_grid if math.isfinite(target_grid) and target_grid > 0 else None
+    oversampling = 1.0
+    actual_grid = dem_resolution / oversampling if oversampling > 0 else dem_resolution
+    mismatch_ratio = abs(actual_grid - target_grid) / target_grid if target_grid > 0 else None
+    return {
+        "mode": "gamma_dem_oversampling",
+        "dem_resolution_m": dem_resolution,
+        "target_grid_size_m": target_grid,
+        "raw_oversampling": raw_factor,
+        "oversampling": oversampling,
+        "actual_grid_size_m": actual_grid,
+        "mismatch_ratio": mismatch_ratio,
+        "min_oversampling": DEM_OVERSAMPLING_MIN,
+        "max_oversampling": DEM_OVERSAMPLING_MAX,
+    }
+
+
 def slugify_text(value: Any, *, default: str = "item", max_len: int = 96) -> str:
     text = _SAFE_TEXT_RE.sub("_", str(value or "").strip()).strip("._")
     if not text:
@@ -278,7 +525,14 @@ def _gamma_prefix(gamma_env_script_wsl: str) -> str:
     script = str(gamma_env_script_wsl or "").strip()
     if not script:
         return ""
-    return f". {quote_shell(script)} >/dev/null 2>&1 && "
+    return f". {quote_shell(script)} >/dev/null 2>&1 || exit 1; "
+
+
+def _pyint_path_prefix(pyint_home_wsl: str) -> str:
+    home = str(pyint_home_wsl or "").strip().rstrip("/")
+    if not home:
+        return ""
+    return f"export PATH={quote_shell(home + '/pyint')}:\"$PATH\" && "
 
 
 def check_pyint_environment(
@@ -320,7 +574,10 @@ def check_pyint_environment(
     def add(name: str, ok: bool, detail: str = "", skipped: bool = False) -> None:
         checks.append(PyintCheck(name=name, ok=ok, detail=detail, skipped=skipped))
 
-    rc, out, err = run_wsl_command("echo pyint_alive", distro=distro_value, timeout=15)
+    def run_check(command: str, timeout: int = 30):
+        return run_wsl_exec(["bash", "-lc", command], distro=distro_value, timeout=timeout)
+
+    rc, out, err = run_check("echo pyint_alive", timeout=15)
     wsl_ok = rc == 0 and "pyint_alive" in out
     add("WSL distro", wsl_ok, out or err or distro_value)
 
@@ -331,17 +588,15 @@ def check_pyint_environment(
             message=f"WSL distro is unavailable: {distro_value}",
         )
 
-    rc, out, err = run_wsl_command(
+    rc, out, err = run_check(
         f"{quote_shell(python_value)} --version",
-        distro=distro_value,
         timeout=15,
     )
     add("WSL Python", rc == 0, out or err or python_value)
 
     if pyint_home_wsl:
-        rc, out, err = run_wsl_command(
+        rc, out, err = run_check(
             f"test -d {quote_shell(pyint_home_wsl)} && echo ok",
-            distro=distro_value,
             timeout=10,
         )
         add("PYINT_HOME", rc == 0 and "ok" in out, pyint_home_wsl or err)
@@ -349,9 +604,8 @@ def check_pyint_environment(
         add("PYINT_HOME", False, "PYINT_HOME is empty")
 
     if pyint_app_wsl:
-        rc, out, err = run_wsl_command(
+        rc, out, err = run_check(
             f"test -f {quote_shell(pyint_app_wsl)} && echo ok",
-            distro=distro_value,
             timeout=10,
         )
         add("pyintApp.py", rc == 0 and "ok" in out, pyint_app_wsl or err)
@@ -367,17 +621,15 @@ def check_pyint_environment(
         if not path_text:
             add(name, False, f"{name} is empty")
             continue
-        rc, out, err = run_wsl_command(
+        rc, out, err = run_check(
             f"test -d {quote_shell(path_text)} && test -w {quote_shell(path_text)} && echo ok",
-            distro=distro_value,
             timeout=10,
         )
         add(name, rc == 0 and "ok" in out, path_text or err)
 
     if gamma_env_wsl:
-        rc, out, err = run_wsl_command(
+        rc, out, err = run_check(
             f"test -f {quote_shell(gamma_env_wsl)} && echo ok",
-            distro=distro_value,
             timeout=10,
         )
         add("GAMMA env script", rc == 0 and "ok" in out, gamma_env_wsl or err)
@@ -385,16 +637,16 @@ def check_pyint_environment(
         add("GAMMA env script", True, "Not configured; using current PATH", skipped=True)
 
     gamma_prefix = _gamma_prefix(gamma_env_wsl)
+    pyint_prefix = _pyint_path_prefix(pyint_home_wsl)
     for name, command_name in (
         ("GAMMA LT1 import", "LT1_import_SLC_from_zipfiles1"),
         ("GAMMA geocode_back", "geocode_back"),
     ):
-        rc, out, err = run_wsl_command(
-            gamma_prefix + f"command -v {quote_shell(command_name)}",
-            distro=distro_value,
+        rc, out, err = run_check(
+            gamma_prefix + pyint_prefix + f"command -v {quote_shell(command_name)} >/dev/null 2>&1 && echo ok",
             timeout=10,
         )
-        add(name, rc == 0 and bool(out.strip()), out or err or command_name)
+        add(name, rc == 0 and "ok" in out, out or err or command_name)
 
     helper_path = (
         Path(__file__).resolve().parent.parent
@@ -412,7 +664,7 @@ def check_pyint_environment(
             + gamma_prefix
             + f"{quote_shell(python_value)} {quote_shell(pyint_app_wsl)} -h >/dev/null"
         )
-        rc, out, err = run_wsl_command(smoke_cmd, distro=distro_value, timeout=60)
+        rc, out, err = run_check(smoke_cmd, timeout=60)
         add("PyINT smoke test", rc == 0, out or err or "pyintApp.py -h")
     else:
         add("PyINT smoke test", True, "Skipped", skipped=True)

backend/app/services/wsl_service.py

@@ -11,8 +11,10 @@ from __future__ import annotations
 import os
 import shutil
 import subprocess
+import threading
+import time
 from dataclasses import dataclass, field
-from typing import Any, Dict, List, Optional, Sequence, Tuple
+from typing import Any, Callable, Dict, List, Optional, Sequence, Tuple
 
 
 # ---------------------------------------------------------------------------
@@ -101,6 +103,79 @@ def _run_windows_command(
     )
 
 
+def _run_windows_command_stream(
+    args: List[str],
+    timeout: int = 30,
+    env: Optional[Dict[str, str]] = None,
+    stdout_callback: Optional[Callable[[str], None]] = None,
+    stderr_callback: Optional[Callable[[str], None]] = None,
+) -> Tuple[int, str, str]:
+    proc_env = os.environ.copy()
+    if env:
+        proc_env.update(env)
+
+    stdout_parts: List[str] = []
+    stderr_parts: List[str] = []
+    try:
+        proc = subprocess.Popen(
+            args,
+            stdout=subprocess.PIPE,
+            stderr=subprocess.PIPE,
+            text=False,
+            env=proc_env,
+        )
+    except FileNotFoundError:
+        return -2, "", "wsl.exe not found"
+    except Exception as exc:
+        return -3, "", str(exc)
+
+    def _drain(stream: Any, parts: List[str], callback: Optional[Callable[[str], None]]) -> None:
+        for raw_line in iter(stream.readline, b""):
+            text = _decode_subprocess_output(raw_line)
+            if not text:
+                continue
+            parts.append(text)
+            if callback:
+                try:
+                    callback(text)
+                except Exception:
+                    pass
+
+    threads = [
+        threading.Thread(target=_drain, args=(proc.stdout, stdout_parts, stdout_callback), daemon=True),
+        threading.Thread(target=_drain, args=(proc.stderr, stderr_parts, stderr_callback), daemon=True),
+    ]
+    for thread in threads:
+        thread.start()
+
+    timed_out = False
+    deadline = time.monotonic() + max(1, int(timeout or 30))
+    while proc.poll() is None:
+        if time.monotonic() >= deadline:
+            timed_out = True
+            try:
+                proc.kill()
+            except Exception:
+                pass
+            break
+        time.sleep(0.2)
+
+    try:
+        returncode = proc.wait(timeout=10)
+    except subprocess.TimeoutExpired:
+        returncode = -1
+    for thread in threads:
+        thread.join(timeout=5)
+
+    stdout = "\n".join(stdout_parts)
+    stderr = "\n".join(stderr_parts)
+    if timed_out:
+        timeout_text = f"command timed out ({timeout}s)"
+        stderr = f"{stderr}\n{timeout_text}".strip()
+        return -1, stdout, stderr
+    return returncode, stdout, stderr
+
+
 def run_wsl_command(
     cmd: str,
     distro: Optional[str] = None,
@@ -127,6 +202,33 @@ def run_wsl_command(
         return -3, "", str(exc)
 
 
+def run_wsl_command_stream(
+    cmd: str,
+    distro: Optional[str] = None,
+    timeout: int = 30,
+    env: Optional[Dict[str, str]] = None,
+    stdout_callback: Optional[Callable[[str], None]] = None,
+    stderr_callback: Optional[Callable[[str], None]] = None,
+) -> Tuple[int, str, str]:
+    """Run a WSL bash command and stream decoded stdout/stderr lines to callbacks."""
+    wsl_exe = _find_wsl_executable()
+    if not wsl_exe:
+        return -2, "", "wsl.exe not found"
+
+    wsl_args = [wsl_exe]
+    if distro:
+        wsl_args += ["-d", distro]
+    wsl_args += ["bash", "-lc", cmd]
+
+    return _run_windows_command_stream(
+        wsl_args,
+        timeout=timeout,
+        env=env,
+        stdout_callback=stdout_callback,
+        stderr_callback=stderr_callback,
+    )
+
+
 def run_wsl_exec(
     argv: Sequence[str],
     distro: Optional[str] = None,

deploy/wsl/profiles/gamma_env.sh

@@ -60,7 +60,7 @@ for _gamma_dir in \
   _gamma_profile_prepend_path "${_gamma_dir}"
 done
 
-_gamma_profile_repo_root="$(cd "$(dirname "${BASH_SOURCE[0]}")/../.." && pwd)"
+_gamma_profile_repo_root="$(cd "$(dirname "${BASH_SOURCE[0]}")/../../.." && pwd)"
 _gamma_profile_pyint_dir="${_gamma_profile_repo_root}/third_party/PyINT/pyint"
 _gamma_profile_prepend_path "${_gamma_profile_pyint_dir}"
 

experiments/isce2_sbas_timeseries/README.md

@@ -1,181 +0,0 @@
-# ISCE2 SBAS Time-Series Experiments
-
-This folder is the isolated sandbox for validating the SBAS/time-series route before wiring it into production code.
-
-## Purpose
-
-- verify LT-1 stack compatibility with ISCE2 stack tooling
-- validate MintPy input and output expectations
-- record runnable command templates
-- collect conclusions that should later be promoted into `docs/` or backend services
-- maintain the current SBAS product contract before backend embedding
-
-## Structure
-
-- `notes/`
-  - experiment notes, pitfalls, conclusions
-- `configs/`
-  - sample templates, parameter files, manifest drafts
-- `scripts/`
-  - throwaway or semi-stable experiment scripts
-- `scratch/`
-  - local temporary workspace placeholder only
-
-## Rules
-
-- do not commit raw SAR scenes
-- do not commit large DEM or orbit datasets
-- do not commit large intermediate outputs
-- keep production code changes out of this folder unless the goal is to prototype file layout or commands
-- when an experiment becomes stable, move the result back into the formal backend or `docs/`
-
-## Suggested first experiments
-
-1. Check whether LT-1/LUTAN1 scenes can be ingested by official ISCE2 stack tooling.
-2. Determine whether MintPy can consume the generated stack layout without extra conversion.
-3. Record the minimal command chain needed for one small AOI smoke test.
-4. Draft the first `psinsar` manifest and product directory convention.
-
-## Current scripts
-
-- `backend/app/isce2_pipeline/lt1_input_resolver.py`
-  - shared LT-1 input helper reused by D-InSAR and stack experiments
-  - centralizes DEM resolution, orbit-pool resolution, and LT-1 precise-orbit XML generation
-- `scripts/scan_lt1_stack_candidates.py`
-  - scan LT-1 single-scene folders and build a stack candidate manifest
-- `scripts/build_lt1_stack_prep.py`
-  - consume a selected stack manifest
-  - resolve orbit pool and DEM
-  - generate a dry-run `scratch/...` workspace for `stripmapStack --nofocus`
-  - write the current adapter contract and a preflight run script
-- `scripts/materialize_lt1_stack_scenes.py`
-  - consume `scratch/.../stack_input_manifest.json`
-  - materialize one or more LT-1 acquisitions into `SLC/YYYYMMDD/`
-  - write `YYYYMMDD.slc`, `YYYYMMDD.slc.xml`, and `data`
-- `scripts/install_isce2_stack_runtime_ubuntu2404.sh`
-  - install known WSL `isce2` runtime dependencies
-  - default pip mirror is Tsinghua
-- `scripts/install_mintpy_runtime_ubuntu2404.sh`
-  - create or update a dedicated WSL `mintpy` conda environment
-  - default conda channels use Tsinghua mirror URLs
-- `scripts/install_mintpy_into_cloned_isce2_env_ubuntu2404.sh`
-  - clone the working WSL `isce2` env into a dedicated unified-env target such as `isce2_mintpy`
-  - install MintPy into that clone with Tsinghua mirror channels
-- `scripts/run_mintpy_unified_env_ubuntu2404.sh`
-  - run MintPy commands directly inside the cloned unified env
-- `scripts/run_mintpy_sbas_unified_env_smoketest_ubuntu2404.sh`
-  - run the current LT-1 SBAS smoke test in the cloned unified env
-  - reuses the same strict-mask and patched-launcher helpers as the bridge route
-- `scripts/run_mintpy_with_isce_ubuntu2404.sh`
-  - run MintPy commands in the dedicated `mintpy` env
-  - bridge only the top-level WSL `isce` package into the `mintpy` env
-  - avoids pulling conflicting `h5py` / numeric packages from the `isce2` env
-- `scripts/create_mintpy_all_ifgram_mask.py`
-  - build a strict `maskAllValid.h5` from `inputs/ifgramStack.h5`
-  - keep only pixels valid in all interferograms before SBAS inversion
-- `scripts/run_smallbaselineApp_patched.py`
-  - repo-local launcher for MintPy `smallbaselineApp`
-  - applies a local workaround for the MintPy `1.6.2` single-pixel partial-network inversion bug
-- `scripts/run_mintpy_sbas_smoketest_ubuntu2404.sh`
-  - run the current LT-1 SBAS smoke test in three steps:
-    - `load_data`
-    - strict-mask generation
-    - `modify_network -> velocity`
-- `scripts/export_mintpy_publish_products_ubuntu2404.sh`
-  - geocode MintPy outputs into latitude/longitude grids
-  - convert selected outputs into GeoTIFF
-  - build a publish-style bundle with `manifest.json`, `assets/`, `preview/`, and `metadata/`
-  - defaults to the bridge runner but now also supports `MINTPY_RUNNER=...` override
-- `scripts/export_mintpy_publish_products_unified_env_ubuntu2404.sh`
-  - run the same publish export logic through the cloned unified env runner
-- `scripts/export_conda_env_snapshot_ubuntu2404.sh`
-  - export one WSL conda environment into reproducible snapshot files
-  - writes `no_builds.yml`, `explicit.txt`, `conda_list.txt`, and `runtime_versions.txt`
-- `scripts/export_phase4_env_snapshots_ubuntu2404.sh`
-  - export both `isce2` and `isce2_mintpy_v1` snapshots for the current phase-4 record
-- `scripts/build_mintpy_publish_bundle.py`
-  - generate `preview/velocity_preview.png`
-  - summarize quality masks
-  - write the publish-style `manifest.json`
-- `scripts/prepare_lt1_stack_dem.py`
-  - clip a stack-local DEM window from the source DEM
-  - store it under `scratch/.../inputs/dem/`
-  - avoid global-DEM bbox problems during `createWaterMask`
-- `scripts/run_generated_stack_runfile_ubuntu2404.sh`
-  - execute one generated `run_XX_*` file under `Ubuntu-24.04`
-  - standardize `PATH`, `PYTHONPATH`, and log output
-- `scripts/create_synthetic_watermask.py`
-  - create a local all-land `geom_reference/waterMask.rdr`
-  - used only when `run_01_reference` cannot download `SWBD` from Earthdata
-
-## Reproducible Flow
-
-1. Generate or refresh the sample stack workspace with `build_lt1_stack_prep.py`.
-2. Materialize the LT-1 acquisitions with `materialize_lt1_stack_scenes.py`.
-3. Clip a stack-local DEM window with `prepare_lt1_stack_dem.py`.
-4. In `Ubuntu-24.04`, run `scripts/install_isce2_stack_runtime_ubuntu2404.sh`.
-5. Regenerate the stack workspace so it picks the local DEM.
-6. Run the generated wrapper through the validated chain:
-   - `scripts/run_generated_stack_runfile_ubuntu2404.sh <scratch_root_wsl> run_01_reference`
-   - `scripts/run_generated_stack_runfile_ubuntu2404.sh <scratch_root_wsl> run_02_focus_split`
-   - `scripts/run_generated_stack_runfile_ubuntu2404.sh <scratch_root_wsl> run_03_geo2rdr_coarseResamp`
-   - `scripts/run_generated_stack_runfile_ubuntu2404.sh <scratch_root_wsl> run_04_refineSecondaryTiming`
-   - `scripts/run_generated_stack_runfile_ubuntu2404.sh <scratch_root_wsl> run_05_invertMisreg`
-   - `scripts/run_generated_stack_runfile_ubuntu2404.sh <scratch_root_wsl> run_06_fineResamp`
-   - `scripts/run_generated_stack_runfile_ubuntu2404.sh <scratch_root_wsl> run_07_grid_baseline`
-   - if Earthdata credentials are missing, the wrapper now auto-generates a synthetic all-land `waterMask.rdr` from `shadowMask.rdr` and treats `run_01_reference` as recovered
-7. In `Ubuntu-24.04`, run `scripts/install_mintpy_runtime_ubuntu2404.sh` before the first MintPy validation.
-8. In `Ubuntu-24.04`, run `scripts/run_mintpy_with_isce_ubuntu2404.sh prep_isce.py ...` for the first MintPy metadata preparation on stripmapStack outputs.
-9. In `Ubuntu-24.04`, run:
-   - `scripts/run_mintpy_sbas_smoketest_ubuntu2404.sh <cfg_wsl> <mintpy_work_dir_wsl>`
-10. Review:
-   - `notes/PHASE2_MINTPY_SBAS_SMOKETEST.md`
-11. In `Ubuntu-24.04`, run:
-   - `scripts/export_mintpy_publish_products_ubuntu2404.sh <mintpy_work_dir_wsl> <publish_dir_wsl>`
-12. Review:
-   - `notes/PHASE3_PUBLISH_EXPORT_SMOKETEST.md`
-13. Record findings under `notes/` before promoting anything into backend code.
-
-## Product Contract
-
-Formal product guidance now lives in:
-
-- `docs/ISCE2_SBAS_PRODUCT_SPEC.md`
-
-Current practical rule:
-
-- runtime success is proven by radar-coordinate `timeseries.h5` and `velocity.h5`
-- publish success is proven by a geocoded bundle under `publish/.../`
-- system embedding should treat `manifest.json` as the publish entrypoint
-- true time-series capability should be judged against `assets/geo_timeseries.h5`, not only `assets/velocity.tif`
-
-## Unified-Environment Track
-
-The bridge route remains the validated baseline.
-
-A separate unified-environment experiment is now staged in:
-
-- `notes/PHASE4_UNIFIED_ENV_EXPERIMENT.md`
-- `notes/PHASE4_UNIFIED_ENV_DECISION.md`
-
-Current practical rule:
-
-- the unified env has now completed the same SBAS smoke test chain and publish export in experiment scope
-- the unified env is now the preferred SBAS experiment runtime
-- do not replace or mutate the current `isce2` env used by D-InSAR production
-- do not replace the bridge route as the default fallback until the comparison note is fully written
-- current successful unified env:
-  - `/home/administrator/miniconda3/envs/isce2_mintpy_v1`
-- current successful unified SBAS work dir:
-  - `scratch/lt1a_strip1_hh_descending_e123p3_n46p1/stack_work/mintpy_sbas_unified_v1`
-- current successful unified publish dir:
-  - `scratch/lt1a_strip1_hh_descending_e123p3_n46p1/publish/mintpy_sbas_unified_v1`
-
-## Current Offline Assumption
-
-- the LT-1 sample experiment already has local SAR scenes, local orbit XML, and a local DEM
-- the remaining optional online dependency is the `SWBD` water mask normally fetched by `createWaterMask.py`
-- for this experiment track, do not download `SWBD`
-- continue with the local synthetic all-land `waterMask.rdr` fallback until the stack route is otherwise stable
-- current validated MintPy boundary is radar-coordinate `timeseries.h5` plus `velocity.h5`
-- current validated publish boundary is a geocoded experiment bundle under `publish/.../`

experiments/isce2_sbas_timeseries/configs/.gitkeep

@@ -1 +0,0 @@
-

experiments/isce2_sbas_timeseries/configs/env_snapshots/20260406/isce2.conda_list.txt

@@ -1,227 +0,0 @@
-# packages in environment at /home/administrator/miniconda3/envs/isce2:
-#
-# Name                              Version          Build                    Channel
-_openmp_mutex                       4.5              20_gnu                   conda-forge
-aom                                 3.9.1            hac33072_0               conda-forge
-attr                                2.5.2            h39aace5_0               conda-forge
-aws-c-auth                          0.9.3            hef928c7_0               conda-forge
-aws-c-cal                           0.9.13           h2c9d079_1               conda-forge
-aws-c-common                        0.12.6           hb03c661_0               conda-forge
-aws-c-compression                   0.3.1            h8b1a151_9               conda-forge
-aws-c-event-stream                  0.5.7            h28f887f_1               conda-forge
-aws-c-http                          0.10.7           ha8fc4e3_5               conda-forge
-aws-c-io                            0.23.3           hdaf4b65_5               conda-forge
-aws-c-mqtt                          0.13.3           hc63082f_11              conda-forge
-aws-c-s3                            0.11.3           h06ab39a_1               conda-forge
-aws-c-sdkutils                      0.2.4            h8b1a151_4               conda-forge
-aws-checksums                       0.2.7            h8b1a151_5               conda-forge
-aws-crt-cpp                         0.35.2           h8824e59_6               conda-forge
-aws-sdk-cpp                         1.11.606         hf38915e_9               conda-forge
-azure-core-cpp                      1.16.1           h3a458e0_0               conda-forge
-azure-identity-cpp                  1.13.2           h3a5f585_1               conda-forge
-azure-storage-blobs-cpp             12.15.0          h2a74896_1               conda-forge
-azure-storage-common-cpp            12.11.0          h3d7a050_1               conda-forge
-azure-storage-files-datalake-cpp    12.13.0          hf38f1be_1               conda-forge
-backports.zstd                      1.3.0            py311h6b1f9c4_0          conda-forge
-blosc                               1.21.6           he440d0b_1               conda-forge
-brotli-python                       1.2.0            py311h66f275b_1          conda-forge
-brunsli                             0.1              hd1e3526_2               conda-forge
-bzip2                               1.0.8            hda65f42_9               conda-forge
-c-ares                              1.34.6           hb03c661_0               conda-forge
-c-blosc2                            2.23.1           hc31b594_0               conda-forge
-ca-certificates                     2026.2.25        hbd8a1cb_0               conda-forge
-cached-property                     1.5.2            hd8ed1ab_1               conda-forge
-cached_property                     1.5.2            pyha770c72_1             conda-forge
-cairo                               1.18.4           he90730b_1               conda-forge
-capnproto                           1.2.0            hfc315d8_0               conda-forge
-certifi                             2026.2.25        pyhd8ed1ab_0             conda-forge
-cfitsio                             4.6.3            ha0b56bc_0               conda-forge
-charls                              2.4.3            hecca717_0               conda-forge
-charset-normalizer                  3.4.5            pyhd8ed1ab_0             conda-forge
-contourpy                           1.3.3            pypi_0                   pypi
-cycler                              0.12.1           pypi_0                   pypi
-cyrus-sasl                          2.1.28           hac629b4_1               conda-forge
-dav1d                               1.2.1            hd590300_0               conda-forge
-fftw                                3.3.10           nompi_h3b011a4_112       conda-forge
-fmt                                 12.0.0           h2b0788b_0               conda-forge
-font-ttf-dejavu-sans-mono           2.37             hab24e00_0               conda-forge
-font-ttf-inconsolata                3.000            h77eed37_0               conda-forge
-font-ttf-source-code-pro            2.038            h77eed37_0               conda-forge
-font-ttf-ubuntu                     0.83             h77eed37_3               conda-forge
-fontconfig                          2.17.1           h27c8c51_0               conda-forge
-fonts-conda-ecosystem               1                0                        conda-forge
-fonts-conda-forge                   1                hc364b38_1               conda-forge
-fonttools                           4.62.1           pypi_0                   pypi
-freetype                            2.14.2           ha770c72_0               conda-forge
-freexl                              2.0.0            h9dce30a_2               conda-forge
-gdal                                3.10.3           py311h34ccccb_27         conda-forge
-geos                                3.14.1           h480dda7_0               conda-forge
-geotiff                             1.7.4            h1000f5c_4               conda-forge
-giflib                              5.2.2            hd590300_0               conda-forge
-h2                                  4.3.0            pyhcf101f3_0             conda-forge
-h5py                                3.15.1           nompi_py311h0b2f468_101  conda-forge
-hdf4                                4.2.15           h2a13503_7               conda-forge
-hdf5                                1.14.6           nompi_h19486de_106       conda-forge
-hpack                               4.1.0            pyhd8ed1ab_0             conda-forge
-hyperframe                          6.1.0            pyhd8ed1ab_0             conda-forge
-icu                                 78.2             h33c6efd_0               conda-forge
-idna                                3.11             pyhd8ed1ab_0             conda-forge
-imagecodecs                         2026.3.6         py311h9837d23_1          conda-forge
-imageio                             2.37.0           pyhfb79c49_0             conda-forge
-isce2                               2.6.4            py311h916084f_2          conda-forge
-json-c                              0.18             h6688a6e_0               conda-forge
-jxrlib                              1.1              hd590300_3               conda-forge
-kealib                              1.6.2            hb2f3951_2               conda-forge
-keyutils                            1.6.3            hb9d3cd8_0               conda-forge
-kiwisolver                          1.5.0            pypi_0                   pypi
-krb5                                1.22.2           ha1258a1_0               conda-forge
-lazy-loader                         0.5              pyhd8ed1ab_0             conda-forge
-lcms2                               2.18             h0c24ade_0               conda-forge
-ld_impl_linux-64                    2.45.1           default_hbd61a6d_101     conda-forge
-lerc                                4.1.0            hdb68285_0               conda-forge
-libabseil                           20250512.1       cxx17_hba17884_0         conda-forge
-libacl                              2.3.2            h0f662aa_0               conda-forge
-libaec                              1.1.5            h088129d_0               conda-forge
-libarchive                          3.8.5            gpl_hc2c16d8_100         conda-forge
-libavif16                           1.4.0            hcfa2d63_0               conda-forge
-libblas                             3.11.0           5_h4a7cf45_openblas      conda-forge
-libbrotlicommon                     1.2.0            hb03c661_1               conda-forge
-libbrotlidec                        1.2.0            hb03c661_1               conda-forge
-libbrotlienc                        1.2.0            hb03c661_1               conda-forge
-libcblas                            3.11.0           5_h0358290_openblas      conda-forge
-libcrc32c                           1.1.2            h9c3ff4c_0               conda-forge
-libcurl                             8.18.0           hcf29cc6_1               conda-forge
-libdeflate                          1.25             h17f619e_0               conda-forge
-libedit                             3.1.20250104     pl5321h7949ede_0         conda-forge
-libev                               4.33             hd590300_2               conda-forge
-libexpat                            2.7.4            hecca717_0               conda-forge
-libffi                              3.5.2            h3435931_0               conda-forge
-libfreetype                         2.14.2           ha770c72_0               conda-forge
-libfreetype6                        2.14.2           h73754d4_0               conda-forge
-libgcc                              15.2.0           he0feb66_18              conda-forge
-libgcc-ng                           15.2.0           h69a702a_18              conda-forge
-libgdal                             3.10.3           h3b705f5_27              conda-forge
-libgdal-core                        3.10.3           h1f481a6_27              conda-forge
-libgdal-fits                        3.10.3           hec9d828_27              conda-forge
-libgdal-grib                        3.10.3           hb20eef8_27              conda-forge
-libgdal-hdf4                        3.10.3           ha810028_27              conda-forge
-libgdal-hdf5                        3.10.3           h966a9c2_27              conda-forge
-libgdal-jp2openjpeg                 3.10.3           hdd07572_27              conda-forge
-libgdal-kea                         3.10.3           h2bf108d_27              conda-forge
-libgdal-netcdf                      3.10.3           ha526aae_27              conda-forge
-libgdal-pdf                         3.10.3           h20efda7_27              conda-forge
-libgdal-pg                          3.10.3           h55c2262_27              conda-forge
-libgdal-postgisraster               3.10.3           h55c2262_27              conda-forge
-libgdal-tiledb                      3.10.3           h6c35068_27              conda-forge
-libgdal-xls                         3.10.3           hdee084c_27              conda-forge
-libgfortran                         15.2.0           h69a702a_18              conda-forge
-libgfortran5                        15.2.0           h68bc16d_18              conda-forge
-libgl                               1.7.0            ha4b6fd6_2               conda-forge
-libglib                             2.86.4           h6548e54_1               conda-forge
-libglvnd                            1.7.0            ha4b6fd6_2               conda-forge
-libglx                              1.7.0            ha4b6fd6_2               conda-forge
-libgomp                             15.2.0           he0feb66_18              conda-forge
-libgoogle-cloud                     2.39.0           hdb79228_0               conda-forge
-libgoogle-cloud-storage             2.39.0           hdbdcf42_0               conda-forge
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-libhwy                              1.3.0            h4c17acf_1               conda-forge
-libiconv                            1.18             h3b78370_2               conda-forge
-libjpeg-turbo                       3.1.2            hb03c661_0               conda-forge
-libjxl                              0.11.2           ha09017c_0               conda-forge
-libkml                              1.3.0            haa4a5bd_1022            conda-forge
-liblapack                           3.11.0           5_h47877c9_openblas      conda-forge
-liblzma                             5.8.2            hb03c661_0               conda-forge
-libnetcdf                           4.9.3            nompi_hbf2fc22_104       conda-forge
-libnghttp2                          1.67.0           had1ee68_0               conda-forge
-libnsl                              2.0.1            hb9d3cd8_1               conda-forge
-libntlm                             1.8              hb9d3cd8_0               conda-forge
-libopenblas                         0.3.30           pthreads_h94d23a6_4      conda-forge
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-libprotobuf                         6.31.1           h49aed37_4               conda-forge
-libre2-11                           2025.11.05       h7b12aa8_0               conda-forge
-librttopo                           1.1.0            h46dd2a8_20              conda-forge
-libspatialite                       5.1.0            gpl_h2abfd87_119         conda-forge
-libsqlite                           3.52.0           hf4e2dac_0               conda-forge
-libssh2                             1.11.1           hcf80075_0               conda-forge
-libstdcxx                           15.2.0           h934c35e_18              conda-forge
-libstdcxx-ng                        15.2.0           hdf11a46_18              conda-forge
-libtiff                             4.7.1            h9d88235_1               conda-forge
-liburing                            2.14             hb700be7_0               conda-forge
-libuuid                             2.41.3           h5347b49_0               conda-forge
-libwebp-base                        1.6.0            hd42ef1d_0               conda-forge
-libxcb                              1.17.0           h8a09558_0               conda-forge
-libxcrypt                           4.4.36           hd590300_1               conda-forge
-libxml2                             2.15.2           he237659_0               conda-forge
-libxml2-16                          2.15.2           hca6bf5a_0               conda-forge
-libxml2-devel                       2.15.2           he237659_0               conda-forge
-libxslt                             1.1.43           h711ed8c_1               conda-forge
-libzip                              1.11.2           h6991a6a_0               conda-forge
-libzlib                             1.3.1            hb9d3cd8_2               conda-forge
-libzopfli                           1.0.3            h9c3ff4c_0               conda-forge
-lz4-c                               1.10.0           h5888daf_1               conda-forge
-lzo                                 2.10             h280c20c_1002            conda-forge
-matplotlib                          3.10.8           pypi_0                   pypi
-minizip                             4.0.10           h05a5f5f_0               conda-forge
-ncurses                             6.5              h2d0b736_3               conda-forge
-networkx                            3.6.1            pyhcf101f3_0             conda-forge
-nspr                                4.38             h29cc59b_0               conda-forge
-nss                                 3.118            h445c969_0               conda-forge
-numpy                               1.26.4           py311h64a7726_0          conda-forge
-openjpeg                            2.5.4            h55fea9a_0               conda-forge
-openjph                             0.26.3           h8d634f6_0               conda-forge
-openldap                            2.6.10           hbde042b_1               conda-forge
-openmotif                           2.3.8            hf55c2fc_5               conda-forge
-openssl                             3.6.1            h35e630c_1               conda-forge
-packaging                           26.0             pyhcf101f3_0             conda-forge
-pcre2                               10.47            haa7fec5_0               conda-forge
-pillow                              12.1.1           py311hf88fc01_0          conda-forge
-pip                                 26.0.1           pyh8b19718_0             conda-forge
-pixman                              0.46.4           h54a6638_1               conda-forge
-poppler                             25.07.0          h13eef12_1               conda-forge
-poppler-data                        0.4.12           hd8ed1ab_0               conda-forge
-postgresql                          18.3             h9d31465_0               conda-forge
-proj                                9.7.1            he0df7b0_3               conda-forge
-pthread-stubs                       0.4              hb9d3cd8_1002            conda-forge
-pyparsing                           3.3.2            pypi_0                   pypi
-pysocks                             1.7.1            pyha55dd90_7             conda-forge
-python                              3.11.15          hd63d673_0_cpython       conda-forge
-python-dateutil                     2.9.0.post0      pypi_0                   pypi
-python_abi                          3.11             8_cp311                  conda-forge
-rav1e                               0.8.1            h1fbca29_0               conda-forge
-re2                                 2025.11.05       h5301d42_0               conda-forge
-readline                            8.3              h853b02a_0               conda-forge
-requests                            2.32.5           pyhcf101f3_1             conda-forge
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-six                                 1.17.0           pypi_0                   pypi
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-tk                                  8.6.13           noxft_h366c992_103       conda-forge
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-zstd                                1.5.7            hb78ec9c_6               conda-forge

experiments/isce2_sbas_timeseries/configs/env_snapshots/20260406/isce2.explicit.txt

@@ -1,221 +0,0 @@
-# This file may be used to create an environment using:
-# $ conda create --name <env> --file <this file>
-# platform: linux-64
-# created-by: conda 26.1.1
-@EXPLICIT
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-https://conda.anaconda.org/conda-forge/noarch/font-ttf-source-code-pro-2.038-h77eed37_0.tar.bz2
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-https://conda.anaconda.org/conda-forge/noarch/fonts-conda-ecosystem-1-0.tar.bz2
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experiments/isce2_sbas_timeseries/configs/env_snapshots/20260406/isce2.no_builds.yml

@@ -1,231 +0,0 @@
-name: isce2
-channels:
-  - conda-forge
-  - defaults
-dependencies:
-  - _openmp_mutex=4.5
-  - aom=3.9.1
-  - attr=2.5.2
-  - aws-c-auth=0.9.3
-  - aws-c-cal=0.9.13
-  - aws-c-common=0.12.6
-  - aws-c-compression=0.3.1
-  - aws-c-event-stream=0.5.7
-  - aws-c-http=0.10.7
-  - aws-c-io=0.23.3
-  - aws-c-mqtt=0.13.3
-  - aws-c-s3=0.11.3
-  - aws-c-sdkutils=0.2.4
-  - aws-checksums=0.2.7
-  - aws-crt-cpp=0.35.2
-  - aws-sdk-cpp=1.11.606
-  - azure-core-cpp=1.16.1
-  - azure-identity-cpp=1.13.2
-  - azure-storage-blobs-cpp=12.15.0
-  - azure-storage-common-cpp=12.11.0
-  - azure-storage-files-datalake-cpp=12.13.0
-  - backports.zstd=1.3.0
-  - blosc=1.21.6
-  - brotli-python=1.2.0
-  - brunsli=0.1
-  - bzip2=1.0.8
-  - c-ares=1.34.6
-  - c-blosc2=2.23.1
-  - ca-certificates=2026.2.25
-  - cached-property=1.5.2
-  - cached_property=1.5.2
-  - cairo=1.18.4
-  - capnproto=1.2.0
-  - certifi=2026.2.25
-  - cfitsio=4.6.3
-  - charls=2.4.3
-  - charset-normalizer=3.4.5
-  - cyrus-sasl=2.1.28
-  - dav1d=1.2.1
-  - fftw=3.3.10
-  - fmt=12.0.0
-  - font-ttf-dejavu-sans-mono=2.37
-  - font-ttf-inconsolata=3.000
-  - font-ttf-source-code-pro=2.038
-  - font-ttf-ubuntu=0.83
-  - fontconfig=2.17.1
-  - fonts-conda-ecosystem=1
-  - fonts-conda-forge=1
-  - freetype=2.14.2
-  - freexl=2.0.0
-  - gdal=3.10.3
-  - geos=3.14.1
-  - geotiff=1.7.4
-  - giflib=5.2.2
-  - h2=4.3.0
-  - h5py=3.15.1
-  - hdf4=4.2.15
-  - hdf5=1.14.6
-  - hpack=4.1.0
-  - hyperframe=6.1.0
-  - icu=78.2
-  - idna=3.11
-  - imagecodecs=2026.3.6
-  - imageio=2.37.0
-  - isce2=2.6.4
-  - json-c=0.18
-  - jxrlib=1.1
-  - kealib=1.6.2
-  - keyutils=1.6.3
-  - krb5=1.22.2
-  - lazy-loader=0.5
-  - lcms2=2.18
-  - ld_impl_linux-64=2.45.1
-  - lerc=4.1.0
-  - libabseil=20250512.1
-  - libacl=2.3.2
-  - libaec=1.1.5
-  - libarchive=3.8.5
-  - libavif16=1.4.0
-  - libblas=3.11.0
-  - libbrotlicommon=1.2.0
-  - libbrotlidec=1.2.0
-  - libbrotlienc=1.2.0
-  - libcblas=3.11.0
-  - libcrc32c=1.1.2
-  - libcurl=8.18.0
-  - libdeflate=1.25
-  - libedit=3.1.20250104
-  - libev=4.33
-  - libexpat=2.7.4
-  - libffi=3.5.2
-  - libfreetype=2.14.2
-  - libfreetype6=2.14.2
-  - libgcc=15.2.0
-  - libgcc-ng=15.2.0
-  - libgdal=3.10.3
-  - libgdal-core=3.10.3
-  - libgdal-fits=3.10.3
-  - libgdal-grib=3.10.3
-  - libgdal-hdf4=3.10.3
-  - libgdal-hdf5=3.10.3
-  - libgdal-jp2openjpeg=3.10.3
-  - libgdal-kea=3.10.3
-  - libgdal-netcdf=3.10.3
-  - libgdal-pdf=3.10.3
-  - libgdal-pg=3.10.3
-  - libgdal-postgisraster=3.10.3
-  - libgdal-tiledb=3.10.3
-  - libgdal-xls=3.10.3
-  - libgfortran=15.2.0
-  - libgfortran5=15.2.0
-  - libgl=1.7.0
-  - libglib=2.86.4
-  - libglvnd=1.7.0
-  - libglx=1.7.0
-  - libgomp=15.2.0
-  - libgoogle-cloud=2.39.0
-  - libgoogle-cloud-storage=2.39.0
-  - libgrpc=1.73.1
-  - libhwy=1.3.0
-  - libiconv=1.18
-  - libjpeg-turbo=3.1.2
-  - libjxl=0.11.2
-  - libkml=1.3.0
-  - liblapack=3.11.0
-  - liblzma=5.8.2
-  - libnetcdf=4.9.3
-  - libnghttp2=1.67.0
-  - libnsl=2.0.1
-  - libntlm=1.8
-  - libopenblas=0.3.30
-  - libpng=1.6.55
-  - libpq=18.3
-  - libprotobuf=6.31.1
-  - libre2-11=2025.11.05
-  - librttopo=1.1.0
-  - libspatialite=5.1.0
-  - libsqlite=3.52.0
-  - libssh2=1.11.1
-  - libstdcxx=15.2.0
-  - libstdcxx-ng=15.2.0
-  - libtiff=4.7.1
-  - liburing=2.14
-  - libuuid=2.41.3
-  - libwebp-base=1.6.0
-  - libxcb=1.17.0
-  - libxcrypt=4.4.36
-  - libxml2=2.15.2
-  - libxml2-16=2.15.2
-  - libxml2-devel=2.15.2
-  - libxslt=1.1.43
-  - libzip=1.11.2
-  - libzlib=1.3.1
-  - libzopfli=1.0.3
-  - lz4-c=1.10.0
-  - lzo=2.10
-  - minizip=4.0.10
-  - ncurses=6.5
-  - networkx=3.6.1
-  - nspr=4.38
-  - nss=3.118
-  - numpy=1.26.4
-  - openjpeg=2.5.4
-  - openjph=0.26.3
-  - openldap=2.6.10
-  - openmotif=2.3.8
-  - openssl=3.6.1
-  - packaging=26.0
-  - pcre2=10.47
-  - pillow=12.1.1
-  - pip=26.0.1
-  - pixman=0.46.4
-  - poppler=25.07.0
-  - poppler-data=0.4.12
-  - postgresql=18.3
-  - proj=9.7.1
-  - pthread-stubs=0.4
-  - pysocks=1.7.1
-  - python=3.11.15
-  - python_abi=3.11
-  - rav1e=0.8.1
-  - re2=2025.11.05
-  - readline=8.3
-  - requests=2.32.5
-  - s2n=1.6.2
-  - scikit-image=0.26.0
-  - scipy=1.17.1
-  - setuptools=82.0.1
-  - snappy=1.2.2
-  - spdlog=1.16.0
-  - sqlite=3.52.0
-  - svt-av1=4.0.1
-  - tifffile=2026.3.3
-  - tiledb=2.29.2
-  - tk=8.6.13
-  - tzcode=2026a
-  - tzdata=2025c
-  - uriparser=0.9.8
-  - urllib3=2.6.3
-  - wheel=0.46.3
-  - xerces-c=3.3.0
-  - xorg-libice=1.1.2
-  - xorg-libsm=1.2.6
-  - xorg-libx11=1.8.13
-  - xorg-libxau=1.0.12
-  - xorg-libxdmcp=1.1.5
-  - xorg-libxext=1.3.7
-  - xorg-libxft=2.3.9
-  - xorg-libxmu=1.3.1
-  - xorg-libxp=1.0.4
-  - xorg-libxrender=0.9.12
-  - xorg-libxt=1.3.1
-  - zfp=1.0.1
-  - zlib=1.3.1
-  - zlib-ng=2.3.3
-  - zstd=1.5.7
-  - pip:
-      - contourpy==1.3.3
-      - cycler==0.12.1
-      - fonttools==4.62.1
-      - kiwisolver==1.5.0
-      - matplotlib==3.10.8
-      - pyparsing==3.3.2
-      - python-dateutil==2.9.0.post0
-      - six==1.17.0
-prefix: /home/administrator/miniconda3/envs/isce2

experiments/isce2_sbas_timeseries/configs/env_snapshots/20260406/isce2.runtime_versions.txt

@@ -1,12 +0,0 @@
-python_executable=/home/administrator/miniconda3/envs/isce2/bin/python
-python_version=3.11.15
-isce_present=True
-mintpy_present=False
-h5py_present=True
-isce_file=/home/administrator/miniconda3/envs/isce2/lib/python3.11/site-packages/isce/__init__.py
-isce_version=2.6.3
-2026-04-06 15:31:15,137 - h5py._conv - DEBUG - Creating converter from 7 to 5
-2026-04-06 15:31:15,138 - h5py._conv - DEBUG - Creating converter from 5 to 7
-2026-04-06 15:31:15,138 - h5py._conv - DEBUG - Creating converter from 7 to 5
-2026-04-06 15:31:15,139 - h5py._conv - DEBUG - Creating converter from 5 to 7
-h5py_version=3.15.1

experiments/isce2_sbas_timeseries/configs/env_snapshots/20260406/isce2_mintpy_v1.conda_list.txt

@@ -1,350 +0,0 @@
-# packages in environment at /home/administrator/miniconda3/envs/isce2_mintpy_v1:
-#
-# Name                              Version          Build                    Channel
-_openmp_mutex                       4.5              20_gnu                   https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-_x86_64-microarch-level             3                3_skylake                https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-aom                                 3.9.1            hac33072_0               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-argcomplete                         3.6.3            pyhd8ed1ab_0             https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-attr                                2.5.2            hb03c661_1               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-attrs                               26.1.0           pyhcf101f3_0             https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-aws-c-auth                          0.9.3            hef928c7_0               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-aws-c-cal                           0.9.13           h2c9d079_1               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-aws-c-common                        0.12.6           hb03c661_0               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-aws-c-compression                   0.3.1            h8b1a151_9               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-aws-c-event-stream                  0.5.7            h28f887f_1               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-aws-c-http                          0.10.7           ha8fc4e3_5               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-aws-c-io                            0.23.3           hdaf4b65_5               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-aws-c-mqtt                          0.13.3           hc63082f_11              https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-aws-c-s3                            0.11.3           h06ab39a_1               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-aws-c-sdkutils                      0.2.4            h8b1a151_4               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-aws-checksums                       0.2.7            h8b1a151_5               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-aws-crt-cpp                         0.35.2           h8824e59_6               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-aws-sdk-cpp                         1.11.606         hf38915e_9               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-azure-core-cpp                      1.16.1           h3a458e0_0               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-azure-identity-cpp                  1.13.2           h3a5f585_1               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-azure-storage-blobs-cpp             12.15.0          h2a74896_1               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-azure-storage-common-cpp            12.11.0          h3d7a050_1               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-azure-storage-files-datalake-cpp    12.13.0          hf38f1be_1               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-backports.zstd                      1.3.0            py311h6b1f9c4_0          https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-blosc                               1.21.6           he440d0b_1               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-bokeh                               3.9.0            pyhd8ed1ab_0             https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-brotli                              1.2.0            hed03a55_1               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-brotli-bin                          1.2.0            hb03c661_1               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-brotli-python                       1.2.0            py311h66f275b_1          https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-brunsli                             0.1              hd1e3526_2               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-bzip2                               1.0.8            hda65f42_9               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-c-ares                              1.34.6           hb03c661_0               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-c-blosc2                            2.23.1           hc31b594_0               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-ca-certificates                     2026.2.25        hbd8a1cb_0               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-cached-property                     1.5.2            hd8ed1ab_1               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-cached_property                     1.5.2            pyha770c72_1             https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-cairo                               1.18.4           he90730b_1               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-capnproto                           1.2.0            hfc315d8_0               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-cartopy                             0.25.0           py311hed34c8f_1          https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-cdsapi                              0.7.7            pyhd8ed1ab_0             https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-certifi                             2026.2.25        pyhd8ed1ab_0             https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-cffi                                2.0.0            py311h03d9500_1          https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-cfgv                                3.5.0            pyhd8ed1ab_0             https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-cfitsio                             4.6.3            ha0b56bc_0               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-charls                              2.4.3            hecca717_0               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-charset-normalizer                  3.4.5            pyhd8ed1ab_0             https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-click                               8.3.1            pyh8f84b5b_1             https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-cloudpickle                         3.1.2            pyhcf101f3_1             https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-configobj                           5.0.9            pyhd8ed1ab_1             https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-contourpy                           1.3.3            py311h724c32c_4          https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-cvxopt                              1.3.3            py311h3d1f434_0          https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-cycler                              0.12.1           pyhcf101f3_2             https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-cyrus-sasl                          2.1.28           hac629b4_1               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-cytoolz                             1.1.0            py311h49ec1c0_2          https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-dask                                2026.3.0         pyhc364b38_0             https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-dask-core                           2026.3.0         pyhc364b38_0             https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-dask-jobqueue                       0.9.0            pyhd8ed1ab_0             https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-dav1d                               1.2.1            hd590300_0               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-distlib                             0.4.0            pyhd8ed1ab_0             https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-distributed                         2026.3.0         pyhc364b38_0             https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-donfig                              0.8.1.post1      pyhd8ed1ab_1             https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-dsdp                                5.8              hd9d9efa_1203            https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-eccodes                             2.46.0           h83bc92c_0               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-ecmwf-datastores-client             0.5.1            pyhd8ed1ab_0             https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-fftw                                3.3.10           nompi_h3b011a4_112       https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-filelock                            3.25.2           pyhd8ed1ab_0             https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-fmt                                 12.0.0           h2b0788b_0               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-font-ttf-dejavu-sans-mono           2.37             hab24e00_0               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-font-ttf-inconsolata                3.000            h77eed37_0               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-font-ttf-source-code-pro            2.038            h77eed37_0               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-font-ttf-ubuntu                     0.83             h77eed37_3               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-fontconfig                          2.17.1           h27c8c51_0               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-fonts-conda-ecosystem               1                0                        https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-fonts-conda-forge                   1                hc364b38_1               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-fonttools                           4.62.1           pypi_0                   pypi
-freeglut                            3.2.2            ha6d2627_3               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-freetype                            2.14.2           ha770c72_0               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-freexl                              2.0.0            h9dce30a_2               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-fsspec                              2026.3.0         pyhd8ed1ab_0             https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-gdal                                3.10.3           py311h34ccccb_27         https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-geos                                3.14.1           h480dda7_0               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-geotiff                             1.7.4            h1000f5c_4               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-gflags                              2.2.2            h5888daf_1005            https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-giflib                              5.2.2            hd590300_0               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-glog                                0.7.1            hbabe93e_0               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-glpk                                5.0              h445213a_0               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-gmp                                 6.3.0            hac33072_2               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-gsl                                 2.7              he838d99_0               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-h2                                  4.3.0            pyhcf101f3_0             https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-h5py                                3.15.1           nompi_py311h0b2f468_101  https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-hdf4                                4.2.15           h2a13503_7               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-hdf5                                1.14.6           nompi_h19486de_106       https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-hpack                               4.1.0            pyhd8ed1ab_0             https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-hyperframe                          6.1.0            pyhd8ed1ab_0             https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-icu                                 78.2             h33c6efd_0               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-identify                            2.6.18           pyhd8ed1ab_0             https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-idna                                3.11             pyhd8ed1ab_0             https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-imagecodecs                         2026.3.6         py311h9837d23_1          https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-imageio                             2.37.0           pyhfb79c49_0             https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-importlib-metadata                  8.8.0            pyhcf101f3_0             https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-isce2                               2.6.4            py311h916084f_2          https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-jasper                              4.2.9            h1588d4d_1               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-jinja2                              3.1.6            pyhcf101f3_1             https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-joblib                              1.5.3            pyhd8ed1ab_0             https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-json-c                              0.18             h6688a6e_0               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-jxrlib                              1.1              hd590300_3               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-kealib                              1.6.2            hb2f3951_2               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-keyutils                            1.6.3            hb9d3cd8_0               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-kiwisolver                          1.5.0            py311h724c32c_0          https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-krb5                                1.22.2           ha1258a1_0               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-lazy-loader                         0.5              pyhd8ed1ab_0             https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-lcms2                               2.18             h0c24ade_0               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-ld_impl_linux-64                    2.45.1           default_hbd61a6d_102     https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-lerc                                4.1.0            hdb68285_0               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-libabseil                           20250512.1       cxx17_hba17884_0         https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-libacl                              2.3.2            h0f662aa_0               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-libaec                              1.1.5            h088129d_0               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-libamd                              3.3.3            haaf9dc3_7100102         https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-libarchive                          3.8.5            gpl_hc2c16d8_100         https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-libarrow                            22.0.0           h2937f24_4_cuda          https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-libarrow-acero                      22.0.0           hb826db4_4_cuda          https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-libarrow-compute                    22.0.0           h58682fd_4_cuda          https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-libarrow-dataset                    22.0.0           hb826db4_4_cuda          https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-libarrow-substrait                  22.0.0           h9d9f3f8_4_cuda          https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-libattr                             2.5.2            hb03c661_1               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-libavif16                           1.4.0            hcfa2d63_0               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-libblas                             3.11.0           5_h4a7cf45_openblas      https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-libbrotlicommon                     1.2.0            hb03c661_1               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-libbrotlidec                        1.2.0            hb03c661_1               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-libbrotlienc                        1.2.0            hb03c661_1               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-libbtf                              2.3.2            h32481e8_7100102         https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-libcamd                             3.3.3            h32481e8_7100102         https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-libcblas                            3.11.0           5_h0358290_openblas      https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-libccolamd                          3.3.4            h32481e8_7100102         https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-libcholmod                          5.3.1            h59ddab4_7100102         https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
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-libcrc32c                           1.1.2            h9c3ff4c_0               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
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-spdlog                              1.16.0           hffee6e0_1               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-sqlite                              3.52.0           h04a0ce9_0               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-suitesparse                         7.10.1           ha0f6916_7100102         https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-svt-av1                             4.0.1            hecca717_0               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-tblib                               3.2.2            pyhcf101f3_0             https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-tifffile                            2026.3.3         pyhd8ed1ab_0             https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-tiledb                              2.29.2           h8821262_1               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-tk                                  8.6.13           noxft_h366c992_103       https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-toolz                               1.1.0            pyhd8ed1ab_1             https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-tornado                             6.5.5            py311h49ec1c0_0          https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-tqdm                                4.67.3           pyh8f84b5b_0             https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-typing_extensions                   4.15.0           pyhcf101f3_0             https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-tzcode                              2026a            h280c20c_0               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-tzdata                              2025c            hc9c84f9_1               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-ukkonen                             1.1.0            py311hdf67eae_0          https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
-unicodedata2                        17.0.1           py311h49ec1c0_0          https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
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-xorg-libxau                         1.0.12           hb03c661_1               https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
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experiments/isce2_sbas_timeseries/configs/env_snapshots/20260406/isce2_mintpy_v1.explicit.txt

@@ -1,352 +0,0 @@
-# This file may be used to create an environment using:
-# $ conda create --name <env> --file <this file>
-# platform: linux-64
-# created-by: conda 26.1.1
-@EXPLICIT
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experiments/isce2_sbas_timeseries/configs/env_snapshots/20260406/isce2_mintpy_v1.no_builds.yml

@@ -1,354 +0,0 @@
-name: isce2_mintpy_v1
-channels:
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-  - defaults
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-  - libopentelemetry-cpp-headers=1.21.0
-  - libparquet=22.0.0
-  - libparu=1.0.0
-  - libpng=1.6.55
-  - libpq=18.3
-  - libprotobuf=6.31.1
-  - librbio=4.3.4
-  - libre2-11=2025.11.05
-  - librttopo=1.1.0
-  - libspatialite=5.1.0
-  - libspex=3.2.3
-  - libspqr=4.3.4
-  - libsqlite=3.52.0
-  - libssh2=1.11.1
-  - libstdcxx=15.2.0
-  - libstdcxx-ng=15.2.0
-  - libsuitesparseconfig=7.10.1
-  - libthrift=0.22.0
-  - libtiff=4.7.1
-  - libumfpack=6.3.5
-  - liburing=2.14
-  - libutf8proc=2.11.3
-  - libuuid=2.41.3
-  - libwebp-base=1.6.0
-  - libxcb=1.17.0
-  - libxcrypt=4.4.36
-  - libxml2=2.15.2
-  - libxml2-16=2.15.2
-  - libxml2-devel=2.15.2
-  - libxslt=1.1.43
-  - libzip=1.11.2
-  - libzlib=1.3.1
-  - libzopfli=1.0.3
-  - locket=1.0.0
-  - lxml=6.0.2
-  - lz4=4.4.5
-  - lz4-c=1.10.0
-  - lzo=2.10
-  - markdown-it-py=4.0.0
-  - markupsafe=3.0.3
-  - matplotlib-base=3.10.8
-  - mdurl=0.1.2
-  - metis=5.1.0
-  - minizip=4.0.10
-  - mintpy=1.6.3
-  - mpfr=4.2.2
-  - msgpack-python=1.1.2
-  - multiurl=0.3.7
-  - munkres=1.1.4
-  - narwhals=2.18.1
-  - ncurses=6.5
-  - networkx=3.6.1
-  - nlohmann_json=3.12.0
-  - nodeenv=1.10.0
-  - nspr=4.38
-  - nss=3.118
-  - numpy=1.26.4
-  - openjpeg=2.5.4
-  - openjph=0.26.3
-  - openldap=2.6.10
-  - openmotif=2.3.8
-  - openssl=3.6.1
-  - orc=2.2.1
-  - packaging=26.0
-  - pandas=3.0.2
-  - partd=1.4.2
-  - pcre2=10.47
-  - pillow=12.1.1
-  - pip=26.0.1
-  - pixman=0.46.4
-  - platformdirs=4.9.4
-  - poppler=25.07.0
-  - poppler-data=0.4.12
-  - postgresql=18.3
-  - pre-commit=4.5.1
-  - proj=9.7.1
-  - prometheus-cpp=1.3.0
-  - psutil=7.2.2
-  - pthread-stubs=0.4
-  - pyaps3=0.3.7
-  - pyarrow=22.0.0
-  - pyarrow-core=22.0.0
-  - pycparser=2.22
-  - pygments=2.20.0
-  - pygrib=2.1.8
-  - pykdtree=1.4.3
-  - pykml=0.2.0
-  - pyparsing=3.3.2
-  - pyproj=3.7.2
-  - pyresample=1.35.0
-  - pyshp=3.0.3
-  - pysocks=1.7.1
-  - pysolid=0.3.4
-  - python=3.11.15
-  - python-dateutil=2.9.0.post0
-  - python-discovery=1.2.1
-  - python_abi=3.11
-  - pytz=2026.1.post1
-  - pyyaml=6.0.3
-  - qhull=2020.2
-  - rav1e=0.8.1
-  - re2=2025.11.05
-  - readline=8.3
-  - requests=2.32.5
-  - rich=14.3.3
-  - s2n=1.6.2
-  - scikit-image=0.26.0
-  - scipy=1.17.1
-  - setuptools=82.0.1
-  - shapely=2.1.2
-  - six=1.17.0
-  - snappy=1.2.2
-  - sortedcontainers=2.4.0
-  - spdlog=1.16.0
-  - sqlite=3.52.0
-  - suitesparse=7.10.1
-  - svt-av1=4.0.1
-  - tblib=3.2.2
-  - tifffile=2026.3.3
-  - tiledb=2.29.2
-  - tk=8.6.13
-  - toolz=1.1.0
-  - tornado=6.5.5
-  - tqdm=4.67.3
-  - typing_extensions=4.15.0
-  - tzcode=2026a
-  - tzdata=2025c
-  - ukkonen=1.1.0
-  - unicodedata2=17.0.1
-  - uriparser=0.9.8
-  - urllib3=2.6.3
-  - utm=0.7.0
-  - virtualenv=21.2.0
-  - wheel=0.46.3
-  - xerces-c=3.3.0
-  - xorg-libice=1.1.2
-  - xorg-libsm=1.2.6
-  - xorg-libx11=1.8.13
-  - xorg-libxau=1.0.12
-  - xorg-libxdmcp=1.1.5
-  - xorg-libxext=1.3.7
-  - xorg-libxfixes=6.0.2
-  - xorg-libxft=2.3.9
-  - xorg-libxi=1.8.2
-  - xorg-libxmu=1.3.1
-  - xorg-libxp=1.0.4
-  - xorg-libxrender=0.9.12
-  - xorg-libxt=1.3.1
-  - xyzservices=2026.3.0
-  - yaml=0.2.5
-  - zfp=1.0.1
-  - zict=3.0.0
-  - zipp=3.23.0
-  - zlib=1.3.1
-  - zlib-ng=2.3.3
-  - zstd=1.5.7
-  - pip:
-      - fonttools==4.62.1
-prefix: /home/administrator/miniconda3/envs/isce2_mintpy_v1

experiments/isce2_sbas_timeseries/configs/env_snapshots/20260406/isce2_mintpy_v1.runtime_versions.txt

@@ -1,14 +0,0 @@
-python_executable=/home/administrator/miniconda3/envs/isce2_mintpy_v1/bin/python
-python_version=3.11.15
-isce_present=True
-mintpy_present=True
-h5py_present=True
-isce_file=/home/administrator/miniconda3/envs/isce2_mintpy_v1/lib/python3.11/site-packages/isce/__init__.py
-isce_version=2.6.3
-mintpy_file=/home/administrator/miniconda3/envs/isce2_mintpy_v1/lib/python3.11/site-packages/mintpy/__init__.py
-mintpy_version=1.6.2
-2026-04-06 15:31:20,151 - h5py._conv - DEBUG - Creating converter from 7 to 5
-2026-04-06 15:31:20,152 - h5py._conv - DEBUG - Creating converter from 5 to 7
-2026-04-06 15:31:20,153 - h5py._conv - DEBUG - Creating converter from 7 to 5
-2026-04-06 15:31:20,153 - h5py._conv - DEBUG - Creating converter from 5 to 7
-h5py_version=3.15.1

experiments/isce2_sbas_timeseries/configs/phase2_bridge_smoketest_20260406_smallbaseline.cfg

@@ -1,64 +0,0 @@
-# vim: set filetype=cfg:
-## LT-1 stripmapStack -> MintPy SBAS smoke-test config
-## Workspace:
-##   phase2_bridge_smoketest_20260406
-## Sample stack:
-##   LT1A|STRIP1|HH|DESCENDING|E123.3_N46.1
-##   dates: 20250118, 20250315, 20250510, 20250705, 20250830
-## Work dir suggestion:
-##   /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/phase2_bridge_smoketest_20260406/stack_work/mintpy_sbas_unified_phase2_20260407
-
-########## computing resource configuration
-mintpy.compute.cluster   = none
-mintpy.compute.numWorker = 4
-mintpy.compute.maxMemory = 8.0
-
-########## 1. load_data
-mintpy.load.processor      = isce
-mintpy.load.autoPath       = no
-mintpy.load.updateMode     = yes
-mintpy.load.compression    = lzf
-mintpy.load.metaFile       = /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/phase2_bridge_smoketest_20260406/stack_work/merged/SLC/20250510/referenceShelve/data.dat
-mintpy.load.baselineDir    = /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/phase2_bridge_smoketest_20260406/stack_work/baselines
-mintpy.load.unwFile        = /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/phase2_bridge_smoketest_20260406/stack_work/Igrams/*/filt*_snaphu.unw
-mintpy.load.corFile        = /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/phase2_bridge_smoketest_20260406/stack_work/Igrams/*/filt_*.cor
-mintpy.load.connCompFile   = /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/phase2_bridge_smoketest_20260406/stack_work/Igrams/*/filt*_snaphu.unw.conncomp
-mintpy.load.intFile        = None
-mintpy.load.demFile        = /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/phase2_bridge_smoketest_20260406/stack_work/geom_reference/hgt.rdr
-mintpy.load.lookupYFile    = /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/phase2_bridge_smoketest_20260406/stack_work/geom_reference/lat.rdr
-mintpy.load.lookupXFile    = /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/phase2_bridge_smoketest_20260406/stack_work/geom_reference/lon.rdr
-mintpy.load.incAngleFile   = /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/phase2_bridge_smoketest_20260406/stack_work/geom_reference/los.rdr
-mintpy.load.azAngleFile    = /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/phase2_bridge_smoketest_20260406/stack_work/geom_reference/los.rdr
-mintpy.load.shadowMaskFile = /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/phase2_bridge_smoketest_20260406/stack_work/geom_reference/shadowMask.rdr
-mintpy.load.waterMaskFile  = /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/phase2_bridge_smoketest_20260406/stack_work/geom_reference/waterMask.rdr
-
-########## 2. modify_network
-mintpy.network.coherenceBased = no
-mintpy.network.areaRatioBased = no
-
-########## 3. reference_point
-mintpy.reference.yx = 1994,52
-mintpy.reference.maskFile = maskAllValid.h5
-
-########## 4. correct_unwrap_error
-mintpy.unwrapError.method = no
-
-########## 5. invert_network
-mintpy.networkInversion.weightFunc      = no
-mintpy.networkInversion.maskDataset     = no
-mintpy.networkInversion.minRedundancy   = 1.0
-mintpy.networkInversion.waterMaskFile   = maskAllValid.h5
-
-########## 6-10. optional corrections disabled for the first unified-env replay
-mintpy.solidEarthTides             = no
-mintpy.ionosphericDelay.method     = no
-mintpy.troposphericDelay.method    = no
-mintpy.deramp                      = no
-mintpy.topographicResidual         = no
-
-########## 11-13. outputs
-mintpy.reference.date = 20250510
-mintpy.geocode        = no
-mintpy.save.kmz       = no
-mintpy.save.hdfEos5   = no
-mintpy.plot           = no

experiments/isce2_sbas_timeseries/configs/sample_psinsar_manifest_lt1_e123p3_n46p1.json

@@ -1,117 +0,0 @@
-{
-  "schema_version": "psinsar.sbas.v1",
-  "catalog_name": "psinsar",
-  "mode": "sbas",
-  "engine_code": "isce2",
-  "processor_code": "isce2_stack_mintpy",
-  "sample_group_key": "LT1A|STRIP1|HH|DESCENDING|E123.3_N46.1",
-  "reference_date": "20250510",
-  "reference_point_yx": [
-    1994,
-    52
-  ],
-  "stack_dates": [
-    "20250118",
-    "20250315",
-    "20250510",
-    "20250705",
-    "20250830"
-  ],
-  "network_pair_count": 10,
-  "mintpy_work_dir_wsl": "/mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1/stack_work/mintpy_sbas_v5",
-  "publish_dir_wsl": "/mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1/publish/mintpy_sbas_v5",
-  "quality_summary": {
-    "strict_valid_pixels": 1219001,
-    "strict_valid_pixel_ratio": 0.2991,
-    "mask_temp_coh_pixels": 62987,
-    "mask_temp_coh_threshold": 0.7
-  },
-  "artifacts": [
-    {
-      "product_type": "timeseries_cube",
-      "role": "primary",
-      "dataset": "timeseries",
-      "publish_relpath": "assets/geo_timeseries.h5",
-      "source_relpath": "assets/geo_timeseries.h5"
-    },
-    {
-      "product_type": "velocity_map",
-      "role": "primary",
-      "dataset": "velocity",
-      "publish_relpath": "assets/geo_velocity.h5",
-      "source_relpath": "assets/geo_velocity.h5"
-    },
-    {
-      "product_type": "velocity_geotiff",
-      "role": "primary",
-      "dataset": "velocity",
-      "publish_relpath": "assets/velocity.tif",
-      "source_relpath": "assets/velocity.tif"
-    },
-    {
-      "product_type": "temporal_coherence",
-      "role": "quality",
-      "dataset": "temporalCoherence",
-      "publish_relpath": "assets/geo_temporalCoherence.h5",
-      "source_relpath": "assets/geo_temporalCoherence.h5"
-    },
-    {
-      "product_type": "temporal_coherence_geotiff",
-      "role": "quality",
-      "dataset": "temporalCoherence",
-      "publish_relpath": "assets/temporalCoherence.tif",
-      "source_relpath": "assets/temporalCoherence.tif"
-    },
-    {
-      "product_type": "quality_mask",
-      "role": "quality",
-      "dataset": "mask",
-      "publish_relpath": "assets/geo_maskTempCoh.h5",
-      "source_relpath": "assets/geo_maskTempCoh.h5"
-    },
-    {
-      "product_type": "quality_mask_geotiff",
-      "role": "quality",
-      "dataset": "mask",
-      "publish_relpath": "assets/maskTempCoh.tif",
-      "source_relpath": "assets/maskTempCoh.tif"
-    },
-    {
-      "product_type": "ifgram_network",
-      "role": "diagnostic",
-      "dataset": "mask",
-      "publish_relpath": "runtime/numTriNonzeroIntAmbiguity.h5",
-      "source_relpath": "numTriNonzeroIntAmbiguity.h5"
-    },
-    {
-      "product_type": "preview_png",
-      "role": "primary",
-      "publish_relpath": "preview/velocity_preview.png",
-      "source_relpath": "preview/velocity_preview.png"
-    },
-    {
-      "product_type": "diagnostic_png",
-      "role": "diagnostic",
-      "publish_relpath": "preview/numTriNonzeroIntAmbiguity.png",
-      "source_relpath": "preview/numTriNonzeroIntAmbiguity.png"
-    }
-  ],
-  "retained_runtime_artifacts": [
-    {
-      "purpose": "strict_all_ifgram_mask",
-      "source_relpath": "maskAllValid.h5"
-    },
-    {
-      "purpose": "average_spatial_coherence",
-      "source_relpath": "avgSpatialCoh.h5"
-    },
-    {
-      "purpose": "config_backup",
-      "source_relpath": "smallbaselineApp.cfg"
-    }
-  ],
-  "notes": [
-    "This is a sample experiment manifest for system-integration design only.",
-    "Current experiment includes geocoded HDF5 outputs, GeoTIFF exports, and a publish-style manifest bundle."
-  ]
-}

experiments/isce2_sbas_timeseries/configs/sample_smallbaseline_lt1_e123p3_n46p1.cfg

@@ -1,62 +0,0 @@
-# vim: set filetype=cfg:
-## LT-1 stripmapStack -> MintPy SBAS smoke-test config
-## Sample stack:
-##   LT1A|STRIP1|HH|DESCENDING|E123.3_N46.1
-##   dates: 20250118, 20250315, 20250510, 20250705, 20250830
-## Work dir suggestion:
-##   /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1/stack_work/mintpy_sbas
-
-########## computing resource configuration
-mintpy.compute.cluster   = none
-mintpy.compute.numWorker = 4
-mintpy.compute.maxMemory = 8.0
-
-########## 1. load_data
-mintpy.load.processor      = isce
-mintpy.load.autoPath       = no
-mintpy.load.updateMode     = yes
-mintpy.load.compression    = lzf
-mintpy.load.metaFile       = /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1/stack_work/merged/SLC/20250510/referenceShelve/data.dat
-mintpy.load.baselineDir    = /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1/stack_work/baselines
-mintpy.load.unwFile        = /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1/stack_work/Igrams/*/filt*_snaphu.unw
-mintpy.load.corFile        = /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1/stack_work/Igrams/*/filt_*.cor
-mintpy.load.connCompFile   = /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1/stack_work/Igrams/*/filt*_snaphu.unw.conncomp
-mintpy.load.intFile        = None
-mintpy.load.demFile        = /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1/stack_work/geom_reference/hgt.rdr
-mintpy.load.lookupYFile    = /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1/stack_work/geom_reference/lat.rdr
-mintpy.load.lookupXFile    = /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1/stack_work/geom_reference/lon.rdr
-mintpy.load.incAngleFile   = /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1/stack_work/geom_reference/los.rdr
-mintpy.load.azAngleFile    = /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1/stack_work/geom_reference/los.rdr
-mintpy.load.shadowMaskFile = /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1/stack_work/geom_reference/shadowMask.rdr
-mintpy.load.waterMaskFile  = /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1/stack_work/geom_reference/waterMask.rdr
-
-########## 2. modify_network
-mintpy.network.coherenceBased = no
-mintpy.network.areaRatioBased = no
-
-########## 3. reference_point
-mintpy.reference.yx = 1994,52
-mintpy.reference.maskFile = maskAllValid.h5
-
-########## 4. correct_unwrap_error
-mintpy.unwrapError.method = no
-
-########## 5. invert_network
-mintpy.networkInversion.weightFunc      = no
-mintpy.networkInversion.maskDataset     = no
-mintpy.networkInversion.minRedundancy   = 1.0
-mintpy.networkInversion.waterMaskFile   = maskAllValid.h5
-
-########## 6-10. optional corrections disabled for first offline LT-1 smoke test
-mintpy.solidEarthTides             = no
-mintpy.ionosphericDelay.method     = no
-mintpy.troposphericDelay.method    = no
-mintpy.deramp                      = no
-mintpy.topographicResidual         = no
-
-########## 11-13. outputs
-mintpy.reference.date = 20250510
-mintpy.geocode        = no
-mintpy.save.kmz       = no
-mintpy.save.hdfEos5   = no
-mintpy.plot           = no

experiments/isce2_sbas_timeseries/configs/sample_stack_e123p3_n46p1.json

@@ -1,175 +0,0 @@
-{
-  "source_root_windows": "F:\\Insar_data_pool_1",
-  "source_root_wsl": "/mnt/f/Insar_data_pool_1",
-  "group_key": "LT1A|STRIP1|HH|DESCENDING|E123.3_N46.1",
-  "tile_key": "E123.3_N46.1",
-  "scene_count": 5,
-  "reference_strategy": "middle_by_date",
-  "reference_date": "20250510",
-  "stack_group": {
-    "satellite": "LT1A",
-    "imaging_mode": "STRIP1",
-    "polarization": "HH",
-    "orbit_direction": "DESCENDING",
-    "receiving_stations": [
-      "KSC",
-      "SYC"
-    ]
-  },
-  "proposed_scratch_windows": "Z:\\Code\\Insar_management_system_v2\\experiments\\isce2_sbas_timeseries\\scratch\\lt1a_strip1_hh_descending_e123p3_n46p1",
-  "proposed_scratch_wsl": "/mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1",
-  "proposed_layout": {
-    "stack_input_manifest": "/mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1/stack_input_manifest.json",
-    "slc_dir": "/mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1/SLC",
-    "orbits_dir": "/mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1/orbits",
-    "logs_dir": "/mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1/logs"
-  },
-  "stack_prep_assessment": {
-    "current_scene_layout": "per_scene_folder_with_tiff_meta_rpc",
-    "official_stripmapStack_expected_layout": "SLC/YYYYMMDD/YYYYMMDD.raw or YYYYMMDD.slc",
-    "direct_compatibility": "unproven",
-    "lt1_adapter_required_likely": true,
-    "notes": [
-      "Current repo can read these scene folders as RadarData assets.",
-      "Official stripmapStack helper scripts do not advertise LT-1/LUTAN1 preparation hooks.",
-      "A custom LT-1 stack preparation layer is likely needed before official stack execution."
-    ]
-  },
-  "scenes": [
-    {
-      "folder_name": "LT1A_MONO_SYC_STRIP1_016197_E123.3_N46.1_20250118_SLC_HH_S2A_0000623780",
-      "folder_path": "F:\\Insar_data_pool_1\\LT1A_MONO_SYC_STRIP1_016197_E123.3_N46.1_20250118_SLC_HH_S2A_0000623780",
-      "folder_path_wsl": "/mnt/f/Insar_data_pool_1/LT1A_MONO_SYC_STRIP1_016197_E123.3_N46.1_20250118_SLC_HH_S2A_0000623780",
-      "tiff_path": "F:\\Insar_data_pool_1\\LT1A_MONO_SYC_STRIP1_016197_E123.3_N46.1_20250118_SLC_HH_S2A_0000623780\\LT1A_MONO_SYC_STRIP1_016197_E123.3_N46.1_20250118_SLC_HH_S2A_0000623780.tiff",
-      "tiff_path_wsl": "/mnt/f/Insar_data_pool_1/LT1A_MONO_SYC_STRIP1_016197_E123.3_N46.1_20250118_SLC_HH_S2A_0000623780/LT1A_MONO_SYC_STRIP1_016197_E123.3_N46.1_20250118_SLC_HH_S2A_0000623780.tiff",
-      "meta_path": "F:\\Insar_data_pool_1\\LT1A_MONO_SYC_STRIP1_016197_E123.3_N46.1_20250118_SLC_HH_S2A_0000623780\\LT1A_MONO_SYC_STRIP1_016197_E123.3_N46.1_20250118_SLC_HH_S2A_0000623780.meta.xml",
-      "meta_path_wsl": "/mnt/f/Insar_data_pool_1/LT1A_MONO_SYC_STRIP1_016197_E123.3_N46.1_20250118_SLC_HH_S2A_0000623780/LT1A_MONO_SYC_STRIP1_016197_E123.3_N46.1_20250118_SLC_HH_S2A_0000623780.meta.xml",
-      "file_size_bytes": 1632365702,
-      "satellite": "LT1A",
-      "imaging_date": "20250118",
-      "imaging_mode": "STRIP1",
-      "polarization": "HH",
-      "orbit_direction": "DESCENDING",
-      "satellite_mode": "MONOSTATIC",
-      "receiving_station": "SYC",
-      "orbit_circle": "16197",
-      "scene_center_lon": 123.3290291621,
-      "scene_center_lat": 46.0963941396,
-      "acquisition_time_utc": "2025-01-18T22:5:18.778600",
-      "product_type": "COMPLEX",
-      "product_level": "LEVEL2A",
-      "product_unique_id": "0000623780",
-      "tile_key": "E123.3_N46.1",
-      "group_key": "LT1A|STRIP1|HH|DESCENDING|E123.3_N46.1",
-      "orbit_txt_expected_name": "LT1A_GpsData_GAS_C_20250118.txt"
-    },
-    {
-      "folder_name": "LT1A_MONO_KSC_STRIP1_017030_E123.3_N46.1_20250315_SLC_HH_S2A_0000678238",
-      "folder_path": "F:\\Insar_data_pool_1\\LT1A_MONO_KSC_STRIP1_017030_E123.3_N46.1_20250315_SLC_HH_S2A_0000678238",
-      "folder_path_wsl": "/mnt/f/Insar_data_pool_1/LT1A_MONO_KSC_STRIP1_017030_E123.3_N46.1_20250315_SLC_HH_S2A_0000678238",
-      "tiff_path": "F:\\Insar_data_pool_1\\LT1A_MONO_KSC_STRIP1_017030_E123.3_N46.1_20250315_SLC_HH_S2A_0000678238\\LT1A_MONO_KSC_STRIP1_017030_E123.3_N46.1_20250315_SLC_HH_S2A_0000678238.tiff",
-      "tiff_path_wsl": "/mnt/f/Insar_data_pool_1/LT1A_MONO_KSC_STRIP1_017030_E123.3_N46.1_20250315_SLC_HH_S2A_0000678238/LT1A_MONO_KSC_STRIP1_017030_E123.3_N46.1_20250315_SLC_HH_S2A_0000678238.tiff",
-      "meta_path": "F:\\Insar_data_pool_1\\LT1A_MONO_KSC_STRIP1_017030_E123.3_N46.1_20250315_SLC_HH_S2A_0000678238\\LT1A_MONO_KSC_STRIP1_017030_E123.3_N46.1_20250315_SLC_HH_S2A_0000678238.meta.xml",
-      "meta_path_wsl": "/mnt/f/Insar_data_pool_1/LT1A_MONO_KSC_STRIP1_017030_E123.3_N46.1_20250315_SLC_HH_S2A_0000678238/LT1A_MONO_KSC_STRIP1_017030_E123.3_N46.1_20250315_SLC_HH_S2A_0000678238.meta.xml",
-      "file_size_bytes": 1630628342,
-      "satellite": "LT1A",
-      "imaging_date": "20250315",
-      "imaging_mode": "STRIP1",
-      "polarization": "HH",
-      "orbit_direction": "DESCENDING",
-      "satellite_mode": "MONOSTATIC",
-      "receiving_station": "KSC",
-      "orbit_circle": "17030",
-      "scene_center_lon": 123.3320867599,
-      "scene_center_lat": 46.1149596404,
-      "acquisition_time_utc": "2025-03-15T22:5:19.382029",
-      "product_type": "COMPLEX",
-      "product_level": "LEVEL2A",
-      "product_unique_id": "0000678238",
-      "tile_key": "E123.3_N46.1",
-      "group_key": "LT1A|STRIP1|HH|DESCENDING|E123.3_N46.1",
-      "orbit_txt_expected_name": "LT1A_GpsData_GAS_C_20250315.txt"
-    },
-    {
-      "folder_name": "LT1A_MONO_KSC_STRIP1_017863_E123.3_N46.1_20250510_SLC_HH_S2A_0000738820",
-      "folder_path": "F:\\Insar_data_pool_1\\LT1A_MONO_KSC_STRIP1_017863_E123.3_N46.1_20250510_SLC_HH_S2A_0000738820",
-      "folder_path_wsl": "/mnt/f/Insar_data_pool_1/LT1A_MONO_KSC_STRIP1_017863_E123.3_N46.1_20250510_SLC_HH_S2A_0000738820",
-      "tiff_path": "F:\\Insar_data_pool_1\\LT1A_MONO_KSC_STRIP1_017863_E123.3_N46.1_20250510_SLC_HH_S2A_0000738820\\LT1A_MONO_KSC_STRIP1_017863_E123.3_N46.1_20250510_SLC_HH_S2A_0000738820.tiff",
-      "tiff_path_wsl": "/mnt/f/Insar_data_pool_1/LT1A_MONO_KSC_STRIP1_017863_E123.3_N46.1_20250510_SLC_HH_S2A_0000738820/LT1A_MONO_KSC_STRIP1_017863_E123.3_N46.1_20250510_SLC_HH_S2A_0000738820.tiff",
-      "meta_path": "F:\\Insar_data_pool_1\\LT1A_MONO_KSC_STRIP1_017863_E123.3_N46.1_20250510_SLC_HH_S2A_0000738820\\LT1A_MONO_KSC_STRIP1_017863_E123.3_N46.1_20250510_SLC_HH_S2A_0000738820.meta.xml",
-      "meta_path_wsl": "/mnt/f/Insar_data_pool_1/LT1A_MONO_KSC_STRIP1_017863_E123.3_N46.1_20250510_SLC_HH_S2A_0000738820/LT1A_MONO_KSC_STRIP1_017863_E123.3_N46.1_20250510_SLC_HH_S2A_0000738820.meta.xml",
-      "file_size_bytes": 1631554934,
-      "satellite": "LT1A",
-      "imaging_date": "20250510",
-      "imaging_mode": "STRIP1",
-      "polarization": "HH",
-      "orbit_direction": "DESCENDING",
-      "satellite_mode": "MONOSTATIC",
-      "receiving_station": "KSC",
-      "orbit_circle": "17863",
-      "scene_center_lon": 123.3311389524,
-      "scene_center_lat": 46.1155150436,
-      "acquisition_time_utc": "2025-05-10T22:5:20.466535",
-      "product_type": "COMPLEX",
-      "product_level": "LEVEL2A",
-      "product_unique_id": "0000738820",
-      "tile_key": "E123.3_N46.1",
-      "group_key": "LT1A|STRIP1|HH|DESCENDING|E123.3_N46.1",
-      "orbit_txt_expected_name": "LT1A_GpsData_GAS_C_20250510.txt"
-    },
-    {
-      "folder_name": "LT1A_MONO_KSC_STRIP1_018697_E123.3_N46.1_20250705_SLC_HH_S2A_0000796680",
-      "folder_path": "F:\\Insar_data_pool_1\\LT1A_MONO_KSC_STRIP1_018697_E123.3_N46.1_20250705_SLC_HH_S2A_0000796680",
-      "folder_path_wsl": "/mnt/f/Insar_data_pool_1/LT1A_MONO_KSC_STRIP1_018697_E123.3_N46.1_20250705_SLC_HH_S2A_0000796680",
-      "tiff_path": "F:\\Insar_data_pool_1\\LT1A_MONO_KSC_STRIP1_018697_E123.3_N46.1_20250705_SLC_HH_S2A_0000796680\\LT1A_MONO_KSC_STRIP1_018697_E123.3_N46.1_20250705_SLC_HH_S2A_0000796680.tiff",
-      "tiff_path_wsl": "/mnt/f/Insar_data_pool_1/LT1A_MONO_KSC_STRIP1_018697_E123.3_N46.1_20250705_SLC_HH_S2A_0000796680/LT1A_MONO_KSC_STRIP1_018697_E123.3_N46.1_20250705_SLC_HH_S2A_0000796680.tiff",
-      "meta_path": "F:\\Insar_data_pool_1\\LT1A_MONO_KSC_STRIP1_018697_E123.3_N46.1_20250705_SLC_HH_S2A_0000796680\\LT1A_MONO_KSC_STRIP1_018697_E123.3_N46.1_20250705_SLC_HH_S2A_0000796680.meta.xml",
-      "meta_path_wsl": "/mnt/f/Insar_data_pool_1/LT1A_MONO_KSC_STRIP1_018697_E123.3_N46.1_20250705_SLC_HH_S2A_0000796680/LT1A_MONO_KSC_STRIP1_018697_E123.3_N46.1_20250705_SLC_HH_S2A_0000796680.meta.xml",
-      "file_size_bytes": 1633523942,
-      "satellite": "LT1A",
-      "imaging_date": "20250705",
-      "imaging_mode": "STRIP1",
-      "polarization": "HH",
-      "orbit_direction": "DESCENDING",
-      "satellite_mode": "MONOSTATIC",
-      "receiving_station": "KSC",
-      "orbit_circle": "18697",
-      "scene_center_lon": 123.3345082568,
-      "scene_center_lat": 46.1000329747,
-      "acquisition_time_utc": "2025-07-05T22:5:20.665803",
-      "product_type": "COMPLEX",
-      "product_level": "LEVEL2A",
-      "product_unique_id": "0000796680",
-      "tile_key": "E123.3_N46.1",
-      "group_key": "LT1A|STRIP1|HH|DESCENDING|E123.3_N46.1",
-      "orbit_txt_expected_name": "LT1A_GpsData_GAS_C_20250705.txt"
-    },
-    {
-      "folder_name": "LT1A_MONO_KSC_STRIP1_019530_E123.3_N46.1_20250830_SLC_HH_S2A_0000857029",
-      "folder_path": "F:\\Insar_data_pool_1\\LT1A_MONO_KSC_STRIP1_019530_E123.3_N46.1_20250830_SLC_HH_S2A_0000857029",
-      "folder_path_wsl": "/mnt/f/Insar_data_pool_1/LT1A_MONO_KSC_STRIP1_019530_E123.3_N46.1_20250830_SLC_HH_S2A_0000857029",
-      "tiff_path": "F:\\Insar_data_pool_1\\LT1A_MONO_KSC_STRIP1_019530_E123.3_N46.1_20250830_SLC_HH_S2A_0000857029\\LT1A_MONO_KSC_STRIP1_019530_E123.3_N46.1_20250830_SLC_HH_S2A_0000857029.tiff",
-      "tiff_path_wsl": "/mnt/f/Insar_data_pool_1/LT1A_MONO_KSC_STRIP1_019530_E123.3_N46.1_20250830_SLC_HH_S2A_0000857029/LT1A_MONO_KSC_STRIP1_019530_E123.3_N46.1_20250830_SLC_HH_S2A_0000857029.tiff",
-      "meta_path": "F:\\Insar_data_pool_1\\LT1A_MONO_KSC_STRIP1_019530_E123.3_N46.1_20250830_SLC_HH_S2A_0000857029\\LT1A_MONO_KSC_STRIP1_019530_E123.3_N46.1_20250830_SLC_HH_S2A_0000857029.meta.xml",
-      "meta_path_wsl": "/mnt/f/Insar_data_pool_1/LT1A_MONO_KSC_STRIP1_019530_E123.3_N46.1_20250830_SLC_HH_S2A_0000857029/LT1A_MONO_KSC_STRIP1_019530_E123.3_N46.1_20250830_SLC_HH_S2A_0000857029.meta.xml",
-      "file_size_bytes": 1629875486,
-      "satellite": "LT1A",
-      "imaging_date": "20250830",
-      "imaging_mode": "STRIP1",
-      "polarization": "HH",
-      "orbit_direction": "DESCENDING",
-      "satellite_mode": "MONOSTATIC",
-      "receiving_station": "KSC",
-      "orbit_circle": "19530",
-      "scene_center_lon": 123.3286377886,
-      "scene_center_lat": 46.1152894101,
-      "acquisition_time_utc": "2025-08-30T22:5:26.558015",
-      "product_type": "COMPLEX",
-      "product_level": "LEVEL2A",
-      "product_unique_id": "0000857029",
-      "tile_key": "E123.3_N46.1",
-      "group_key": "LT1A|STRIP1|HH|DESCENDING|E123.3_N46.1",
-      "orbit_txt_expected_name": "LT1A_GpsData_GAS_C_20250830.txt"
-    }
-  ]
-}

experiments/isce2_sbas_timeseries/notes/.gitkeep

@@ -1 +0,0 @@
-

experiments/isce2_sbas_timeseries/notes/PHASE0_ENV_CHECK.md

@@ -1,62 +0,0 @@
-# Phase 0 Environment Check
-
-Updated: 2026-04-03
-
-## Confirmed
-
-- Project workspace:
-  - Windows repo root: `Z:\Code\Insar_management_system_v2`
-  - WSL mount path: `/mnt/z/Code/Insar_management_system_v2`
-- Windows project Python env:
-  - `C:\Users\Administrator\.conda\envs\InSAR`
-- WSL experiment distro:
-  - `Ubuntu-24.04`
-- WSL project access:
-  - `/mnt/z/Code/Insar_management_system_v2`
-  - `/mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries`
-- WSL system Python:
-  - `Python 3.12.3`
-- WSL conda root:
-  - `/home/administrator/miniconda3`
-- WSL conda envs found:
-  - `base`
-  - `isce2`
-- ISCE2 env package:
-  - `isce2 2.6.4`
-- ISCE2 Python import path:
-  - `/home/administrator/miniconda3/envs/isce2/lib/python3.11/site-packages/isce/__init__.py`
-- Lutan1 sensor module:
-  - `/home/administrator/miniconda3/envs/isce2/lib/python3.11/site-packages/isce/components/isceobj/Sensor/Lutan1.py`
-- Official stack directories present:
-  - `/home/administrator/miniconda3/envs/isce2/share/isce2/stripmapStack`
-  - `/home/administrator/miniconda3/envs/isce2/share/isce2/topsStack`
-
-## Confirmed Gaps
-
-- `conda` is not currently on the default shell `PATH` inside `Ubuntu-24.04`.
-  - Use `/home/administrator/miniconda3/bin/conda` directly in scripts.
-- `MintPy` is not installed in the `isce2` env yet.
-  - `conda list -n isce2 mintpy` returned no match.
-- Calling `conda list -n isce2 ...` from a WSL bash script triggered a segmentation fault once.
-  - For experiment scripts, prefer `conda run -n isce2 python ...` checks over `conda list`.
-
-## Implication
-
-Phase 0 can start immediately for:
-
-- LT-1 / ISCE2 stack compatibility checks
-- workspace and path validation
-- command-chain drafting
-
-But the full SBAS chain cannot run end to end until one of these is true:
-
-- `MintPy` is installed into `isce2`, or
-- a separate WSL env with `MintPy` is prepared
-
-## Next Checks
-
-1. Verify ISCE2 stack scripts actually exist in `Ubuntu-24.04`.
-2. Read `stripmapStack/README.md` and `stackStripMap.py` to identify required stack inputs.
-3. Decide whether `MintPy` should share the `isce2` env or live in a separate env.
-4. Verify LT-1 / LUTAN1 support is usable for stack-mode inputs, not only single-pair mode.
-5. Draft a minimal stack experiment command chain under this folder.

experiments/isce2_sbas_timeseries/notes/PHASE0_REPO_READER_FINDINGS.md

@@ -1,123 +0,0 @@
-# Phase 0 Repo Reader Findings
-
-Updated: 2026-04-03
-
-## Existing repo reader path
-
-The current repository already has a stable LT-1 single-scene metadata ingestion path.
-
-Main code path:
-
-- `backend/app/services/data_service.py`
-  - `scan_radar_data()`
-- `backend/app/utils.py`
-  - `parse_lt1_radar_filename()`
-  - `find_xml_file()`
-  - `parse_xml_metadata()`
-
-## What the existing reader does
-
-### 1. Folder-name parsing
-
-`parse_lt1_radar_filename()` extracts from the directory name:
-
-- `satellite`
-- `satellite_mode`
-- `receiving_station`
-- `imaging_mode`
-- `orbit_circle`
-- `scene_center_lon`
-- `scene_center_lat`
-- `imaging_date`
-- `acquisition_time_utc`
-- `product_type`
-- `polarization`
-- `product_level`
-- `product_unique_id`
-
-Example supported name:
-
-```text
-LT1B_MONO_SYC_STRIP1_018153_E135.4_N48.3_20250701_SLC_HH_S2A_0000790171
-```
-
-### 2. XML discovery
-
-`find_xml_file()` prefers:
-
-- `*.meta.xml`
-
-and falls back to:
-
-- the only XML file in the directory, if there is just one
-
-### 3. XML parsing
-
-`parse_xml_metadata()` extracts:
-
-- `orbit_direction`
-- `imaging_mode`
-- `polarization`
-- `receiving_station`
-- `satellite_mode`
-- `orbit_circle` from `absOrbit`
-- `scene_center_lon`
-- `scene_center_lat`
-- `acquisition_time_utc`
-- `product_type`
-- `product_level`
-- `product_unique_id`
-- `look_direction`
-- corner coordinates and coverage polygon
-
-### 4. Merge rule
-
-`scan_radar_data()` merges:
-
-- folder-name metadata
-- XML metadata
-
-with XML preferred for most fields, except `product_unique_id` where the folder-name value is preserved if present.
-
-## Why this matters for SBAS experiments
-
-This means the SBAS experiment should not invent a separate metadata interpretation unless absolutely necessary.
-
-Recommended rule:
-
-- reuse the same field semantics already used by `RadarDataORM`
-- reuse the same `.meta.xml` discovery logic
-- treat `scan_radar_data()` output as the canonical single-scene asset layer
-
-## Data layout check against `F:\Insar_data_pool_1`
-
-Sample scene directories under `F:\Insar_data_pool_1` are compatible with the current single-scene reader:
-
-- one folder per scene
-- directory name matches LT-1 parser expectations
-- contains `*.meta.xml`
-- contains `*.tiff`
-- contains preview and auxiliary files
-
-Example sample directory:
-
-```text
-F:\Insar_data_pool_1\LT1A_MONO_KSC_STRIP1_017030_E123.3_N46.1_20250315_SLC_HH_S2A_0000678238
-```
-
-Example files inside:
-
-- `...meta.xml`
-- `...tiff`
-- `...rpc`
-- `...browse.jpg`
-- `...thumb.jpg`
-
-## Practical implication
-
-For phase 1 design and experiments:
-
-- the current repo already knows how to ingest these LT-1 scene folders as `RadarData`
-- stack preparation should build on top of this asset layer
-- the real unknown is not scene metadata parsing
-- the real unknown is how to transform these scene folders into a stack layout acceptable to `stripmapStack`

experiments/isce2_sbas_timeseries/notes/PHASE0_SAMPLE_STACK_SELECTION.md

@@ -1,92 +0,0 @@
-# Phase 0 Sample Stack Selection
-
-Updated: 2026-04-03
-
-## Selected baseline sample
-
-Current baseline sample stack:
-
-- group key:
-  - `LT1A|STRIP1|HH|DESCENDING|E123.3_N46.1`
-- manifest:
-  - `experiments/isce2_sbas_timeseries/configs/sample_stack_e123p3_n46p1.json`
-
-## Sample summary
-
-- satellite:
-  - `LT1A`
-- mode:
-  - `STRIP1`
-- polarization:
-  - `HH`
-- orbit direction:
-  - `DESCENDING`
-- scene count:
-  - `5`
-- dates:
-  - `20250118`
-  - `20250315`
-  - `20250510`
-  - `20250705`
-  - `20250830`
-- recommended reference date:
-  - `20250510`
-- receiving stations observed:
-  - `SYC`
-  - `KSC`
-
-## Why this sample is useful
-
-- It already satisfies a minimal SBAS smoke-test stack size.
-- All scenes share the same:
-  - satellite
-  - imaging mode
-  - polarization
-  - orbit direction
-  - tile key
-- The dates are evenly spaced enough to act as a first time-series experiment set.
-
-## Important adjacent-tile signal
-
-This sample is not isolated.
-
-The same date sequence also appears in multiple neighboring descending tiles, including:
-
-- `E123.5_N46.6`
-- `E123.6_N47.0`
-- `E123.8_N47.5`
-- `E123.9_N48.0`
-- `E124.5_N49.9`
-- `E124.7_N50.3`
-- `E124.8_N50.8`
-- `E125.0_N51.3`
-- `E125.1_N51.8`
-- `E125.3_N52.2`
-- `E125.5_N52.7`
-
-These neighboring tiles share the same 5 acquisition dates:
-
-- `20250118`
-- `20250315`
-- `20250510`
-- `20250705`
-- `20250830`
-
-## Implication
-
-This strongly suggests the data pool contains a larger repeated strip-family, not just isolated scenes.
-
-Recommended experiment order:
-
-1. Start with one tile-level stack smoke test using `E123.3_N46.1`.
-2. If stack-prep works, expand to multiple adjacent tiles with the same date family.
-3. Only after that, test a wider strip or mosaic strategy.
-
-## Current risk judgment
-
-The main remaining uncertainty is still not scene selection.
-
-The main uncertainty is:
-
-- how to convert LT-1 per-scene `tiff + meta.xml` folders
-- into a stack layout and sensor input form acceptable to the ISCE2 stripmap stack workflow

experiments/isce2_sbas_timeseries/notes/PHASE0_STACK_FINDINGS.md

@@ -1,140 +0,0 @@
-# Phase 0 Stack Findings
-
-Updated: 2026-04-03
-
-## Confirmed
-
-- Official stack tooling exists in the `isce2` env:
-  - `/home/administrator/miniconda3/envs/isce2/share/isce2/stripmapStack`
-  - `/home/administrator/miniconda3/envs/isce2/share/isce2/topsStack`
-- `stackStripMap.py` exists and is the stripmap stack entry point.
-- `prepStripmap4timeseries.py` exists in the official `stripmapStack` toolset.
-- `stackStripMap.py` expects:
-  - an SLC root directory via `-s/--slc_directory`
-  - a DEM via `-d/--dem`
-  - an optional reference date via `-m/--reference_date`
-  - temporal and baseline thresholds
-- The script scans date subdirectories under the SLC root.
-- Default behavior looks for `<date>.raw` inside each acquisition directory.
-- With `--nofocus`, it instead looks for `<date>.slc`.
-- Deeper code inspection confirms:
-  - `topo.py` opens `<date>/data`
-  - `geo2rdr.py` opens each secondary `<date>/data`
-  - `refineSecondaryTiming` uses both `<date>.slc` and the acquisition directory as metadata roots
-
-## Important implication
-
-Official stack processing expects a stack-style input layout such as:
-
-```text
-SLC/
-  YYYYMMDD/
-    YYYYMMDD.raw
-```
-
-or, when data are already focused:
-
-```text
-SLC/
-  YYYYMMDD/
-    YYYYMMDD.slc
-    YYYYMMDD.slc.xml
-    data
-```
-
-This is different from the current repository's custom LT-1 single-pair production flow.
-
-## Time-series bridge signal
-
-- `prepStripmap4timeseries.py` takes:
-  - pair/interferogram directories
-  - baseline directory
-  - geometry directory
-  - shelve metadata directory
-- The script writes `.rsc` sidecars and explicitly references `pysar`-style downstream usage.
-
-This is useful because it confirms the official stripmap stack toolset already contains a bridge from stack outputs toward time-series preparation.
-The weak point is still the LT-1 stack input/preparation stage, not the existence of a downstream time-series bridge.
-
-## Existing repo bridge signal
-
-The repository's current LT-1 single-pair pipeline already proves one important thing:
-
-- `stripmapApp.py` can be driven with:
-  - `sensor name = LUTAN1`
-  - direct `tiff` input path
-  - direct `orbitFile` XML path
-
-See:
-
-- `backend/app/isce2_pipeline/run_lt1_dinsar_pipeline.py`
-
-The generated XML writes:
-
-- `Reference -> tiff`
-- `Reference -> orbitFile`
-- `Secondary -> tiff`
-- `Secondary -> orbitFile`
-
-This suggests a promising adapter direction:
-
-- do not try to pretend LT-1 is ALOS or another officially prepared raw sensor
-- instead, explore generating LT-1-aware stack configs directly from:
-  - scene `tiff`
-  - scene `meta.xml`
-  - converted orbit XML
-
-That does not prove the official stack driver will accept this without modification.
-But it is the strongest current indication for how a custom LT-1 `stack-prep` layer should be shaped.
-
-## LT-1 / LUTAN1 signal so far
-
-- ISCE core does include a `Lutan1.py` sensor module.
-- But no direct `lutan` match was found in the `stripmapStack` helper scripts.
-- The `stripmapStack` README examples and preparation hints mention:
-  - `prepRawALOS.py`
-  - `prepRawSensor.py`
-- The README explicitly states automatic raw-data preparation support is currently oriented to:
-  - ALOS
-  - CSK
-- `prepRawSensors.py` automatic raw detection currently covers:
-  - Envisat
-  - ERS CEOS
-  - ERS ENV
-  - ALOS1
-  - CSK
-- `prepSlcSensors.py` automatic SLC detection currently covers:
-  - Envisat
-  - ALOS1
-  - CSK
-  - RSAT2
-  - TSX/TDX
-- No LT-1 or LUTAN1 hook was found in these official stack preparation scripts.
-
-## Interim conclusion
-
-Current evidence suggests:
-
-- ISCE2 core can parse LT-1/LUTAN1 at the sensor level.
-- Official `stripmapStack` tooling is present.
-- But the official stack preparation helpers do not currently advertise LT-1/LUTAN1 support.
-- There is no direct evidence yet that LT-1 can be fed into the official stack helpers without an adapter step.
-- `--nofocus` does not remove the need for acquisition metadata preparation.
-  - It still needs a per-date `data` shelve and an ISCE-style `.slc` image.
-
-This means the working assumption should be:
-
-- `LT-1 stack via official stripmapStack` is possible but unproven
-- an LT-1-specific stack preparation or conversion layer is required unless an existing hidden tool can materialize `data` + `.slc` directly for LUTAN1
-
-## Next checks
-
-1. Implement a dry-run LT-1 stack-prep workspace generator against the selected sample manifest.
-2. Design a scene materializer that transforms one LT-1 scene into:
-   - `YYYYMMDD.slc`
-   - `YYYYMMDD.slc.xml`
-   - `data`
-3. Decide whether that materializer should:
-   - call ISCE/LUTAN1 directly, or
-   - reuse parts of the existing pair pipeline
-4. After materialization is proven, run `stackStripMap.py --nofocus` on one tile-level stack

experiments/isce2_sbas_timeseries/notes/PHASE1_STACK_GENERATION_SMOKETEST.md

@@ -1,285 +0,0 @@
-# Phase 1 Stack Generation Smoke Test
-
-Updated: 2026-04-05
-
-Follow-up note:
-
-- MintPy SBAS continuation is now recorded separately in:
-  - `notes/PHASE2_MINTPY_SBAS_SMOKETEST.md`
-
-## Goal
-
-Validate that one LT-1 stack can be transformed from:
-
-- per-scene `tiff + meta.xml + orbit.xml`
-
-into:
-
-- `stripmapStack --nofocus` compatible acquisition directories
-- a generated stripmap stack work plan
-
-without changing production code yet.
-
-## Sample
-
-- group key:
-  - `LT1A|STRIP1|HH|DESCENDING|E123.3_N46.1`
-- dates:
-  - `20250118`
-  - `20250315`
-  - `20250510`
-  - `20250705`
-  - `20250830`
-- reference date:
-  - `20250510`
-
-## Commands Used
-
-1. Build dry-run stack workspace:
-
-```text
-C:\Users\Administrator\.conda\envs\InSAR\python.exe experiments\isce2_sbas_timeseries\scripts\build_lt1_stack_prep.py --manifest-path experiments\isce2_sbas_timeseries\configs\sample_stack_e123p3_n46p1.json
-```
-
-2. Materialize LT-1 acquisitions inside `Ubuntu-24.04`:
-
-```text
-wsl -d Ubuntu-24.04 /home/administrator/miniconda3/bin/conda run -n isce2 python /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scripts/materialize_lt1_stack_scenes.py --stack-manifest /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1/stack_input_manifest.json
-```
-
-3. Run generated wrapper:
-
-```text
-wsl -d Ubuntu-24.04 bash /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1/run_stripmap_stack_dryrun.sh
-```
-
-4. Execute the frozen stack step chain inside `Ubuntu-24.04`:
-
-```text
-wsl -d Ubuntu-24.04 bash /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scripts/run_generated_stack_runfile_ubuntu2404.sh /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1 run_01_reference
-wsl -d Ubuntu-24.04 bash /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scripts/run_generated_stack_runfile_ubuntu2404.sh /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1 run_02_focus_split
-wsl -d Ubuntu-24.04 bash /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scripts/run_generated_stack_runfile_ubuntu2404.sh /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1 run_03_geo2rdr_coarseResamp
-wsl -d Ubuntu-24.04 bash /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scripts/run_generated_stack_runfile_ubuntu2404.sh /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1 run_04_refineSecondaryTiming
-wsl -d Ubuntu-24.04 bash /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scripts/run_generated_stack_runfile_ubuntu2404.sh /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1 run_05_invertMisreg
-wsl -d Ubuntu-24.04 bash /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scripts/run_generated_stack_runfile_ubuntu2404.sh /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1 run_06_fineResamp
-wsl -d Ubuntu-24.04 bash /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scripts/run_generated_stack_runfile_ubuntu2404.sh /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1 run_07_grid_baseline
-```
-
-5. Regenerate the stack in `interferogram` workflow mode and execute the new pair-processing stage:
-
-```text
-C:\Users\Administrator\.conda\envs\InSAR\python.exe experiments\isce2_sbas_timeseries\scripts\build_lt1_stack_prep.py --manifest-path experiments\isce2_sbas_timeseries\configs\sample_stack_e123p3_n46p1.json --workflow interferogram
-wsl -d Ubuntu-24.04 bash /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1/run_stripmap_stack_dryrun.sh
-wsl -d Ubuntu-24.04 bash /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scripts/run_generated_stack_runfile_ubuntu2404.sh /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1 run_08_igram
-```
-
-6. Prepare MintPy metadata in the dedicated `mintpy` env while bridging the working `isce2` Python package:
-
-```text
-wsl -d Ubuntu-24.04 bash /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scripts/install_mintpy_runtime_ubuntu2404.sh
-wsl -d Ubuntu-24.04 bash /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scripts/run_mintpy_with_isce_ubuntu2404.sh prep_isce.py -f "/mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1/stack_work/Igrams/*/filt_*.unw" -m /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1/stack_work/Igrams/20250118_20250315/referenceShelve/data.dat -b /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1/stack_work/baselines -g /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1/stack_work/geom_reference
-```
-
-## Confirmed Results
-
-- All 5 acquisitions were materialized into:
-  - `scratch/lt1a_strip1_hh_descending_e123p3_n46p1/SLC/YYYYMMDD/`
-- Each acquisition directory now contains:
-  - `YYYYMMDD.slc`
-  - `YYYYMMDD.slc.xml`
-  - `YYYYMMDD.slc.vrt`
-  - `data.dat/.dir/.bak`
-- Example materialized output:
-  - `20250510.slc`
-  - size: `3262658784` bytes
-- `stackStripMap.py --nofocus` ran successfully far enough to:
-  - discover all 5 acquisitions
-  - estimate stack baselines
-  - select interferometric pairs
-  - generate stack config files
-  - generate run files
-
-## Baseline Snapshot
-
-Relative to reference date `20250510`, the generated stack reported:
-
-- `20250118`
-  - `-199.6873591838194`
-- `20250315`
-  - `-89.0330513325973`
-- `20250705`
-  - `-561.9056433404087`
-- `20250830`
-  - `215.98283570831154`
-
-The generated network reported:
-
-- minimum connection degree:
-  - `4.0`
-- number of pairs:
-  - `10`
-
-## Generated Stack Work Products
-
-Under `scratch/lt1a_strip1_hh_descending_e123p3_n46p1/stack_work/`:
-
-- `baselines/`
-- `configs/`
-- `run_files/`
-- `pairs.pdf`
-
-Generated run files:
-
-- `run_01_reference`
-- `run_02_focus_split`
-- `run_03_geo2rdr_coarseResamp`
-- `run_04_refineSecondaryTiming`
-- `run_05_invertMisreg`
-- `run_06_fineResamp`
-- `run_07_grid_baseline`
-
-## Important Runtime Fixes
-
-- `matplotlib` was missing from the `isce2` env.
-  - fixed by installing it with `pip` inside the WSL `isce2` environment
-- `stackStripMap.py` could not import `stripmapStack.Stack` by default.
-  - fixed by exporting:
-    - `PYTHONPATH=/home/administrator/miniconda3/envs/isce2/share/isce2`
-    - `PATH=/home/administrator/miniconda3/envs/isce2/share/isce2/stripmapStack:$PATH`
-- the generated run files now include these prefixes automatically
-- `run_01_reference` reached `topo` successfully but `createWaterMask.py` failed without Earthdata credentials.
-  - root cause:
-    - `SWBD` download requires `~/.netrc` for `urs.earthdata.nasa.gov`
-  - current judgment:
-    - local DEM is already sufficient for this experiment
-    - the only missing optional online input is the water-body mask download
-  - experimental fallback:
-    - `scripts/run_generated_stack_runfile_ubuntu2404.sh` now auto-generates a synthetic all-land `geom_reference/waterMask.rdr`
-    - the helper script is `scripts/create_synthetic_watermask.py`
-  - limitation:
-    - this fallback preserves stack execution but does not provide a true coastline mask
-- LT-1 input preparation now has a shared helper:
-  - `backend/app/isce2_pipeline/lt1_input_resolver.py`
-  - purpose:
-    - centralize DEM resolution
-    - centralize orbit-pool resolution
-    - centralize LT-1 precise-orbit XML reuse or generation
-  - compatibility rule:
-    - this is a refactor of shared input-prep logic
-    - the original D-InSAR execution path was not removed
-    - `run_lt1_dinsar_pipeline.py` still keeps its original public workflow entry and now calls the helper internally
-
-## Latest Execution Status
-
-- `run_01_reference`
-  - `topo` completed successfully in `Ubuntu-24.04`
-  - local `geom_reference/waterMask.rdr` was synthesized from `shadowMask.rdr`
-- `run_02_focus_split`
-  - completed successfully
-  - generated configs were effectively no-op under the current `--nofocus` contract
-- `run_03_geo2rdr_coarseResamp`
-  - completed successfully in `Ubuntu-24.04`
-  - generated `offsets/<date>/range.off` and `azimuth.off` for:
-    - `20250118`
-    - `20250315`
-    - `20250705`
-    - `20250830`
-  - generated `coregSLC/Coarse/<date>/YYYYMMDD.slc` products for:
-    - `20250118`
-    - `20250315`
-    - `20250705`
-    - `20250830`
-  - runtime observation:
-    - this stage is long-running and mostly silent in the log file
-    - progress is easier to confirm from product directories than from stdout
-- `run_04_refineSecondaryTiming`
-  - completed successfully in `Ubuntu-24.04`
-  - generated pair-level `refineSecondaryTiming/pairs/<pair>/misreg.*` for all 10 pairs
-  - log observation:
-    - `Bad match at level 1` and `correlation error` appeared in the log
-    - despite that noise, the stage exited `0` and downstream inversion succeeded
-- `run_05_invertMisreg`
-  - completed successfully in `Ubuntu-24.04`
-  - generated date-level `refineSecondaryTiming/dates/<date>/misreg.*` for:
-    - `20250118`
-    - `20250315`
-    - `20250510`
-    - `20250705`
-    - `20250830`
-  - inversion observation:
-    - design matrix was reported as full rank
-    - RMSE in azimuth was `0.002341399255443996` pixels
-    - RMSE in range was `0.0027480408593210303` pixels
-- `run_06_fineResamp`
-  - completed successfully in `Ubuntu-24.04`
-  - generated fine coregistered `merged/SLC/<date>/YYYYMMDD.slc` for all 5 dates
-  - each merged date directory now also includes:
-    - `referenceShelve/`
-    - `secondaryShelve/`
-- `run_07_grid_baseline`
-  - completed successfully in `Ubuntu-24.04`
-  - generated `merged/baselines/<date>/` baseline grids for all 5 dates
-  - each date-level baseline directory now includes:
-    - raw baseline raster
-    - `.xml`
-    - `.vrt`
-    - `.full.vrt`
-- `build_lt1_stack_prep.py --workflow interferogram`
-  - now regenerates the official stripmapStack command in `interferogram` mode instead of hard-coding `slc`
-  - regenerated run files now include:
-    - `run_08_igram`
-- `run_08_igram`
-  - completed successfully in `Ubuntu-24.04`
-  - generated 10 pair directories under `stack_work/Igrams/`
-  - each pair now includes:
-    - wrapped interferogram `.int`
-    - amplitude `.amp`
-    - filtered interferogram `filt_*.int`
-    - coherence `filt_*.cor`
-    - unwrapped phase `filt_*_snaphu.unw`
-    - connected components `*.unw.conncomp`
-    - `referenceShelve/data.*`
-- MintPy runtime bootstrap
-  - `scripts/install_mintpy_runtime_ubuntu2404.sh` created a dedicated WSL env:
-    - `mintpy`
-  - verified commands:
-    - `smallbaselineApp.py`
-    - `prep_isce.py`
-  - installed MintPy version:
-    - `1.6.2`
-- `prep_isce.py`
-  - first run in the clean `mintpy` env failed because `mintpy.utils.isce_utils` imports `isce`
-  - experimental resolution:
-    - `scripts/run_mintpy_with_isce_ubuntu2404.sh` now bridges only the top-level `isce` package from the WSL `isce2` env into the `mintpy` env
-  - result:
-    - `prep_isce.py` completed successfully over the LT-1 `stripmapStack` outputs
-    - geometry `.rsc` files were written under `stack_work/geom_reference/`
-    - observation `.rsc` files were written for all 10 unwrapped interferograms under `stack_work/Igrams/*/`
-
-## Current Boundary
-
-This smoke test confirms:
-
-- LT-1 scenes can be materialized into `stripmapStack` acquisition directories
-- the official stripmap stack driver can build the stack work plan over those LT-1 products
-- the generated `run_01` to `run_07` chain can complete offline in `Ubuntu-24.04` over the sample LT-1 stack
-- local DEM plus local orbit data are sufficient for this stack-preparation stage
-- Earthdata credentials are not a hard blocker for this experiment track because the wrapper can recover `run_01_reference` with a synthetic all-land `waterMask`
-- the same LT-1 stack can be regenerated in `interferogram` workflow mode to produce 10 filtered and unwrapped pair products
-- MintPy metadata preparation is now viable through the dedicated `mintpy` env plus the explicit ISCE bridge wrapper
-
-This smoke test does not yet confirm:
-
-- `smallbaselineApp.py` execution beyond `prep_isce.py`
-- final time-series or velocity products
-
-Follow-up status:
-
-- both of the above were later confirmed in:
-  - `notes/PHASE2_MINTPY_SBAS_SMOKETEST.md`
-
-## Next Tasks
-
-1. Keep this note focused on stack-generation findings only.
-2. Use `notes/PHASE2_MINTPY_SBAS_SMOKETEST.md` for MintPy SBAS runtime conclusions.
-3. Promote the stable runtime and artifact contract into backend workflow code and `docs/`.

experiments/isce2_sbas_timeseries/notes/PHASE2_BRIDGE_SMOKETEST_20260406.md

@@ -1,157 +0,0 @@
-# Phase 2 Bridge Smoketest
-
-Date: 2026-04-06
-
-## Scope
-
-Validate the current SBAS bridge chain with the previously verified LT-1 sample stack:
-
-1. `build_lt1_stack_prep.py`
-2. `materialize_lt1_stack_scenes.py`
-3. `build_lt1_stack_prep.py` refresh
-
-This run validates the current bridge boundary only:
-
-- raw LT-1 scenes
-- local precise orbit pool
-- local prepared DEM
-- fresh scratch workspace
-
-It does not run:
-
-- `stripmapStack`
-- MintPy
-- geocode/export/publish
-
-## Inputs
-
-- sample manifest:
-  - `experiments/isce2_sbas_timeseries/configs/sample_stack_e123p3_n46p1.json`
-- orbit pool:
-  - `/mnt/d/orbit_pools/isce2`
-- DEM:
-  - `/mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1/inputs/dem/stack_dem_window.wgs84`
-
-## Workspace
-
-- scratch root:
-  - `experiments/isce2_sbas_timeseries/scratch/phase2_bridge_smoketest_20260406`
-
-## Result
-
-- final readiness: `True`
-- scene count: `5`
-- reference date: `20250510`
-- all orbits resolved: `True`
-- all `.slc/.slc.xml` present: `True`
-- all `data` shelves present: `True`
-
-## Materialization Summary
-
-- dates:
-  - `20250118`
-  - `20250315`
-  - `20250510`
-  - `20250705`
-  - `20250830`
-- status counts:
-  - `materialized: 5`
-- total bytes written:
-  - `16313641344`
-
-## Artifacts
-
-- selected manifest used for this WSL run:
-  - `experiments/isce2_sbas_timeseries/scratch/phase2_bridge_smoketest_20260406/selected_stack_manifest_wsl.json`
-- generated stack manifest:
-  - `experiments/isce2_sbas_timeseries/scratch/phase2_bridge_smoketest_20260406/stack_input_manifest.json`
-- materialization summary:
-  - `experiments/isce2_sbas_timeseries/scratch/phase2_bridge_smoketest_20260406/materialization_summary.json`
-- generated stack dry-run wrapper:
-  - `experiments/isce2_sbas_timeseries/scratch/phase2_bridge_smoketest_20260406/run_stripmap_stack_dryrun.sh`
-- synthetic water-mask recovery report:
-  - `experiments/isce2_sbas_timeseries/scratch/phase2_bridge_smoketest_20260406/stack_work/logs/run_01_reference.synthetic_watermask.json`
-
-## Finding
-
-`build_lt1_stack_prep.py` currently reads `scene["tiff_path"]` and `scene["meta_path"]` directly.
-When the script is run inside WSL against the sample manifest, the original `F:\...` Windows paths are not readable as Linux paths.
-
-For this smoketest, a temporary WSL-path manifest copy was generated and used:
-
-- `selected_stack_manifest_wsl.json`
-
-This is an experiment-side workaround only.
-No production/system logic was changed for this run.
-
-## Update 2026-04-07
-
-The same fresh workspace was then continued through the stripmap stack run files.
-
-### Additional Result
-
-- `run_01_reference`
-  - reached `createWaterMask`
-  - failed on remote `SWBD` retrieval from:
-    - `https://e4ftl01.cr.usgs.gov/MEASURES/SRTMSWBD.003/...`
-  - recovered with a local synthetic all-land `waterMask.rdr`
-- `run_02_focus_split`
-  - completed
-- `run_03_geo2rdr_coarseResamp`
-  - completed
-- `run_04_refineSecondaryTiming`
-  - completed
-- `run_05_invertMisreg`
-  - completed
-- `run_06_fineResamp`
-  - completed
-- `run_07_grid_baseline`
-  - completed
-- `run_08_igram`
-  - completed through interferogram generation, filtering, coherence, and `snaphu` unwrapping
-
-### Interferogram Snapshot
-
-- pair count on disk:
-  - `10`
-- verified pair folders:
-  - `20250118_20250315`
-  - `20250118_20250510`
-  - `20250118_20250705`
-  - `20250118_20250830`
-  - `20250315_20250510`
-  - `20250315_20250705`
-  - `20250315_20250830`
-  - `20250510_20250705`
-  - `20250510_20250830`
-  - `20250705_20250830`
-- verified key files in every pair directory:
-  - `filt_<date12>.int`
-  - `filt_<date12>.cor`
-  - `filt_<date12>_snaphu.unw`
-  - `filt_<date12>_snaphu.unw.conncomp`
-
-### Finding Update
-
-The original `run_generated_stack_runfile_ubuntu2404.sh` fallback only matched the `.netrc` credential failure text.
-This workspace showed a second offline failure mode:
-
-- `createWaterMask` started normally
-- ISCE2 `DataRetriever` failed during `SWBD` file retrieval
-- the wrapper therefore did not auto-recover on the first attempt
-
-The experiment helper has now been widened to recognize both:
-
-- missing Earthdata credential text
-- direct `SWBD` retrieval failure text from `createWaterMask`
-
-No production/system runtime was changed by this fix.
-
-## Recommended Next Step
-
-Use this fresh workspace to continue with:
-
-1. unified-env MintPy smoketest using:
-   - `configs/phase2_bridge_smoketest_20260406_smallbaseline.cfg`
-2. publish-style geocode/export if MintPy succeeds
-3. compare this fresh replay with the earlier baseline workspace

experiments/isce2_sbas_timeseries/notes/PHASE2_MINTPY_SBAS_SMOKETEST.md

@@ -1,200 +0,0 @@
-# Phase 2 MintPy SBAS Smoke Test
-
-Updated: 2026-04-05
-
-Follow-up note:
-
-- publish-style geocode/export continuation is now recorded separately in:
-  - `notes/PHASE3_PUBLISH_EXPORT_SMOKETEST.md`
-
-## Goal
-
-Validate that the LT-1 sample stack can continue from `stripmapStack` interferogram products into MintPy SBAS outputs under `Ubuntu-24.04`.
-
-## Sample
-
-- group key:
-  - `LT1A|STRIP1|HH|DESCENDING|E123.3_N46.1`
-- dates:
-  - `20250118`
-  - `20250315`
-  - `20250510`
-  - `20250705`
-  - `20250830`
-- pair count:
-  - `10`
-- reference date:
-  - `20250510`
-- reference point:
-  - `y/x = 1994,52`
-
-## Successful Run
-
-Successful SBAS smoke-test work directory:
-
-- `/mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1/stack_work/mintpy_sbas_v5`
-
-Successful WSL command:
-
-```text
-wsl -d Ubuntu-24.04 bash /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scripts/run_mintpy_sbas_smoketest_ubuntu2404.sh /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/configs/sample_smallbaseline_lt1_e123p3_n46p1.cfg /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1/stack_work/mintpy_sbas_v5
-```
-
-This run completed through:
-
-- `load_data`
-- `modify_network`
-- `reference_point`
-- `quick_overview`
-- `invert_network`
-- `reference_date`
-- `velocity`
-
-Disabled for this first offline smoke test:
-
-- unwrap-error correction
-- solid-earth-tide correction
-- ionosphere correction
-- troposphere correction
-- deramp
-- topographic residual correction
-- geocode
-
-## Output Snapshot
-
-Generated under `mintpy_sbas_v5/`:
-
-- `timeseries.h5`
-  - size: `82576752` bytes
-- `velocity.h5`
-  - size: `83086408` bytes
-- `temporalCoherence.h5`
-  - size: `16632424` bytes
-- `maskTempCoh.h5`
-  - size: `4136792` bytes
-- `avgSpatialCoh.h5`
-  - size: `16631784` bytes
-- `numTriNonzeroIntAmbiguity.h5`
-  - size: `16632000` bytes
-- `numTriNonzeroIntAmbiguity.png`
-  - size: `232878` bytes
-
-Quality summary from the successful run:
-
-- strict valid pixels for inversion:
-  - `1219001 / 4076199`
-  - `29.91%`
-- reliable pixels in `maskTempCoh.h5` with threshold `0.7`:
-  - `62987`
-
-## Required Runtime Decisions
-
-### 1. Keep MintPy separate from ISCE2
-
-- keep stack processing in WSL conda env:
-  - `isce2`
-- keep MintPy in WSL conda env:
-  - `mintpy`
-
-Reason:
-
-- avoids mutating the already working ISCE2 processing env on the development machine
-
-### 2. Bridge only the top-level `isce` package
-
-Required helper:
-
-- `scripts/run_mintpy_with_isce_ubuntu2404.sh`
-
-Current rule:
-
-- do not add the entire `isce2` `site-packages` into `PYTHONPATH`
-- only bridge the top-level `isce` package into a cache directory
-
-Reason:
-
-- adding the whole `site-packages` caused MintPy to import `h5py` from the wrong env and fail during `load_data`
-
-### 3. Do not load `wrapPhase` for this LT-1 smoke test
-
-Current config rule:
-
-- `mintpy.load.intFile = None`
-
-Reason:
-
-- loading `filt_*.int` into MintPy `wrapPhase` caused HDF5 type-conversion failure during `load_data`
-
-### 4. Build a strict `maskAllValid.h5` before inversion
-
-Required helper:
-
-- `scripts/create_mintpy_all_ifgram_mask.py`
-
-Current rule:
-
-- keep only pixels that are finite and non-zero in all unwrapped interferograms
-- also require non-zero connected components in all interferograms
-
-Reason:
-
-- this reduces unstable partial-network pixels before SBAS inversion
-
-### 5. Use the repo-local patched launcher
-
-Required helper:
-
-- `scripts/run_smallbaselineApp_patched.py`
-
-Current workaround:
-
-- patch `mintpy.ifgram_inversion.estimate_timeseries()` at runtime
-- coerce shape-`(1,)` inversion-quality output into a scalar for the single-pixel partial-network branch
-
-Reason:
-
-- MintPy `1.6.2` hit a `ValueError: setting an array element with a sequence`
-- failure point:
-  - `mintpy/ifgram_inversion.py`
-  - partial-network pixel branch inside `run_ifgram_inversion_patch()`
-
-Current judgment:
-
-- this is a MintPy runtime issue in the current environment
-- it is better to keep the workaround in repo-local launcher code than silently editing the third-party env
-
-## Current Boundary
-
-This smoke test now confirms:
-
-- LT-1 `stripmapStack` outputs can be loaded by MintPy in the dedicated `mintpy` env
-- the LT-1 sample stack can be inverted into radar-coordinate `timeseries.h5`
-- the LT-1 sample stack can generate radar-coordinate `velocity.h5`
-- the current repo-local workaround chain is reproducible in `Ubuntu-24.04`
-
-This smoke test does not yet confirm:
-
-- geocoded SBAS exports
-- atmospheric or DEM-residual correction quality
-- product publishing into backend `psinsar` catalog
-- frontend rendering of published SBAS products
-
-## System Embedding Implications
-
-The current experiment suggests the future backend runtime contract should be:
-
-1. Run ISCE2 stack workflow in WSL `isce2`.
-2. Run MintPy through the repo-controlled bridge runner instead of calling upstream `smallbaselineApp.py` directly.
-3. Generate a strict inversion mask after `load_data`.
-4. Persist the following files as first-class workflow artifacts:
-   - `timeseries.h5`
-   - `velocity.h5`
-   - `temporalCoherence.h5`
-   - `maskTempCoh.h5`
-   - `numTriNonzeroIntAmbiguity.h5`
-   - `numTriNonzeroIntAmbiguity.png`
-5. Convert these into a stable publish manifest before catalog registration.
-
-Current sample publish-manifest draft:
-
-- `configs/sample_psinsar_manifest_lt1_e123p3_n46p1.json`

experiments/isce2_sbas_timeseries/notes/PHASE3_PUBLISH_EXPORT_SMOKETEST.md

@@ -1,142 +0,0 @@
-# Phase 3 Publish Export Smoke Test
-
-Updated: 2026-04-06
-
-## Goal
-
-Validate that the successful MintPy SBAS experiment can be converted into a publish-style artifact bundle without touching the main system.
-
-## Inputs
-
-Source MintPy work directory:
-
-- `/mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1/stack_work/mintpy_sbas_v5`
-
-Source stack:
-
-- group key:
-  - `LT1A|STRIP1|HH|DESCENDING|E123.3_N46.1`
-- dates:
-  - `20250118`
-  - `20250315`
-  - `20250510`
-  - `20250705`
-  - `20250830`
-
-## Successful Command
-
-```text
-wsl -d Ubuntu-24.04 bash /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scripts/export_mintpy_publish_products_ubuntu2404.sh /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1/stack_work/mintpy_sbas_v5 /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1/publish/mintpy_sbas_v5
-```
-
-## Current Export Scripts
-
-- `scripts/export_mintpy_publish_products_ubuntu2404.sh`
-  - geocode core MintPy outputs
-  - convert selected outputs to GeoTIFF
-  - copy preview and metadata files
-  - build root `manifest.json`
-- `scripts/build_mintpy_publish_bundle.py`
-  - generate `preview/velocity_preview.png`
-  - generate `metadata/source_quality_summary.json`
-  - generate publish-style root `manifest.json`
-
-## Geocode Contract
-
-Current experiment settings:
-
-- lookup source:
-  - `inputs/geometryRadar.h5`
-- output pixel size:
-  - latitude step:
-    - `-0.000185185`
-  - longitude step:
-    - `0.000185185`
-- interpolation:
-  - `nearest`
-
-Observed geocoded grid:
-
-- extent:
-  - south:
-    - `45.80391`
-  - north:
-    - `46.42206`
-  - west:
-    - `122.930244`
-  - east:
-    - `123.76654`
-- shape:
-  - rows:
-    - `3338`
-  - columns:
-    - `4516`
-
-## Generated Publish Bundle
-
-Successful publish-style directory:
-
-- `/mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1/publish/mintpy_sbas_v5`
-
-Main outputs:
-
-- `manifest.json`
-- `assets/geo_timeseries.h5`
-- `assets/geo_velocity.h5`
-- `assets/geo_temporalCoherence.h5`
-- `assets/geo_maskTempCoh.h5`
-- `assets/velocity.tif`
-- `assets/temporalCoherence.tif`
-- `assets/maskTempCoh.tif`
-- `preview/velocity_preview.png`
-- `preview/numTriNonzeroIntAmbiguity.png`
-- `metadata/smallbaselineApp.cfg`
-- `metadata/source_quality_summary.json`
-
-## Current Interpretation
-
-This confirms:
-
-- the experiment now supports radar-coordinate MintPy inversion
-- the experiment also supports geocoded HDF5 exports
-- the experiment can produce publish-style GeoTIFF outputs
-- the experiment can build a stable manifest-driven bundle outside the MintPy work directory
-
-This does not yet confirm:
-
-- direct backend catalog registration
-- frontend rendering against the real system APIs
-- whether `EPSG:4326` should remain the final publish CRS decision
-
-## Important Notes
-
-### 1. Current CRS assumption
-
-`save_gdal.py` warned that no explicit `EPSG` metadata was found and assumed:
-
-- `EPSG:4326`
-
-Current judgment:
-
-- acceptable for this experiment because the geocoded outputs are in latitude/longitude grids
-- should still be checked when formalizing the production publish contract
-
-### 2. Group key in the generated manifest
-
-Because PowerShell treats `|` specially, passing group keys on the command line is awkward from Windows.
-
-Current practical rule:
-
-- the sample manifest stored in git remains the clean reference:
-  - `configs/sample_psinsar_manifest_lt1_e123p3_n46p1.json`
-- the generated publish bundle manifest can be post-filled or generated from backend metadata later
-
-## System Embedding Implication
-
-At this point the experiment-layer chain is split cleanly into three stages:
-
-1. `stripmapStack` preprocessing
-2. MintPy SBAS inversion
-3. geocode + publish-bundle export
-
-That means the future system workflow can wire them as separate workflow steps without changing the validated experiment logic first.

experiments/isce2_sbas_timeseries/notes/PHASE4_UNIFIED_ENV_DECISION.md

@@ -1,120 +0,0 @@
-# Phase 4 Unified-Environment Decision
-
-Updated: 2026-04-06
-
-## Decision
-
-Current experiment preference:
-
-- prefer the unified WSL environment for SBAS experiment work
-
-Current production safety rule:
-
-- do not replace or mutate the existing D-InSAR production environment
-- keep pair-oriented D-InSAR on the existing WSL `isce2` env
-- keep the current backend/public D-InSAR entry unchanged
-
-Current environment split:
-
-- D-InSAR production baseline:
-  - `isce2`
-- SBAS experiment preferred runtime:
-  - `isce2_mintpy_v1`
-
-## Why This Decision Is Reasonable
-
-The unified env has now completed the full current experiment chain:
-
-- MintPy command invocation without the `isce` bridge
-- `load_data`
-- strict-mask generation
-- `modify_network -> velocity`
-- publish export to geocoded HDF5, GeoTIFF, preview, and `manifest.json`
-
-This makes the unified env a valid experiment baseline.
-
-At the same time, the existing pair-oriented D-InSAR route is already working and should not be destabilized just to simplify the SBAS experiment runtime.
-
-The safest rule is therefore:
-
-- let SBAS experiments move forward in a separate unified env
-- do not touch the current `isce2` production env used by D-InSAR
-
-## Evidence
-
-Successful unified env:
-
-- `/home/administrator/miniconda3/envs/isce2_mintpy_v1`
-
-Successful unified SBAS work directory:
-
-- `/mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1/stack_work/mintpy_sbas_unified_v1`
-
-Successful unified publish directory:
-
-- `/mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1/publish/mintpy_sbas_unified_v1`
-
-Matched quality indicators:
-
-- `maskAllValid`:
-  - `1219001 / 4076199`
-  - `29.91%`
-- `maskTempCoh`:
-  - `62987 / 4076199`
-  - `1.55%`
-
-Key package difference:
-
-- current `isce2` env does not provide the MintPy-side package set needed for this SBAS route
-- current `isce2_mintpy_v1` env includes:
-  - `mintpy`
-  - `cartopy`
-  - `pyaps3`
-  - `pykml`
-  - `cvxopt`
-
-## What This Decision Does Not Mean
-
-It does not mean:
-
-- the backend should immediately switch to unified-env execution
-- the bridge route must be deleted now
-- the current D-InSAR runtime should be modified
-
-It only means:
-
-- for the next experiment steps, unified env is the preferred path
-- for current production safety, `isce2` remains untouched
-
-## Required Guardrails
-
-For the next phase, keep these rules:
-
-- do not install MintPy into the existing `isce2` env
-- do not redirect current D-InSAR scripts to `isce2_mintpy_v1`
-- do not remove the bridge-based helpers yet
-- keep all SBAS work in experiment scripts, notes, and scratch directories
-
-## Reproducibility
-
-Environment snapshots should be exported and kept with the experiment record.
-
-Current snapshot command:
-
-```text
-wsl -d Ubuntu-24.04 bash /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scripts/export_phase4_env_snapshots_ubuntu2404.sh /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/configs/env_snapshots/20260406
-```
-
-## Next Stable Experiment Steps
-
-Before any system integration work:
-
-1. Keep the unified env as the default SBAS experiment runtime.
-2. Preserve environment snapshots for both `isce2` and `isce2_mintpy_v1`.
-3. Write one comparison note focused on:
-   - runtime simplicity
-   - reproducibility
-   - remaining workarounds
-   - risk to D-InSAR production
-4. Optionally repeat the chain on one more LT-1 sample stack.
-5. Only after the experiment is stable, design the system integration boundary.

experiments/isce2_sbas_timeseries/notes/PHASE4_UNIFIED_ENV_EXPERIMENT.md

@@ -1,221 +0,0 @@
-# Phase 4 Unified-Environment Experiment
-
-Updated: 2026-04-06
-
-## Goal
-
-Validate whether the current WSL `isce2` runtime can be cloned and extended with MintPy so that the SBAS experiment can run without the temporary `isce` bridge helper.
-
-This is still an experiment-layer task.
-
-Do not change the production backend yet.
-
-## Why run this phase
-
-The bridge-based route is already validated, but a unified environment may be cleaner because:
-
-- many ISCE2 + MintPy users operate in one environment
-- command invocation becomes simpler
-- future worker deployment may be easier if one runtime is stable
-
-The bridge-based route still remains the fallback baseline until this phase is verified.
-
-## Current Known Starting Point
-
-WSL distro:
-
-- `Ubuntu-24.04`
-
-Current environments observed on 2026-04-06:
-
-- `isce2`
-- `mintpy`
-
-Observed package state:
-
-- `isce2` env:
-  - `isce2 2.6.4`
-  - `h5py 3.15.1`
-  - `mintpy` not installed
-- dedicated `mintpy` env:
-  - `mintpy 1.6.3`
-
-## Initial Hypothesis
-
-Expected best-case outcome:
-
-- clone `isce2` into `isce2_mintpy`
-- install `mintpy` directly into the clone
-- reuse the same repo-local strict-mask and patched-launcher helpers
-- run the same LT-1 smoke test without the `isce` bridge wrapper
-
-Main risk areas:
-
-- package solver may replace or downgrade key ISCE2-side numeric dependencies
-- MintPy may still require the same repo-local runtime workaround even in a unified env
-- GDAL / h5py / pyaps3 dependency changes may alter the known-good stack behavior
-
-## Reproducible Commands
-
-### 1. Bootstrap the unified env
-
-```text
-wsl -d Ubuntu-24.04 env TARGET_ENV=isce2_mintpy_v1 BOOTSTRAP_MODE=recreate USE_TUNA_MIRROR=1 MINTPY_SPEC=mintpy=1.6.3 bash /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scripts/install_mintpy_into_cloned_isce2_env_ubuntu2404.sh
-```
-
-Why `BOOTSTRAP_MODE=recreate`:
-
-- direct `conda create --clone` was not stable enough for this machine
-- it still followed source-package URLs and hit channel/TOS friction
-- the successful path was:
-  - export the current `isce2` dependency list
-  - recreate the env through Tsinghua mirror channels
-  - reinstall exported pip packages
-  - install MintPy into the recreated env
-
-Optional environment override:
-
-```text
-TARGET_ENV=isce2_mintpy_v1 MINTPY_SPEC='mintpy=1.6.3'
-```
-
-### 2. Run MintPy commands directly inside the unified env
-
-```text
-wsl -d Ubuntu-24.04 env MINTPY_ENV=isce2_mintpy_v1 bash /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scripts/run_mintpy_unified_env_ubuntu2404.sh prep_isce.py -h
-```
-
-### 3. Re-run the current LT-1 SBAS smoke test in the unified env
-
-```text
-wsl -d Ubuntu-24.04 env MINTPY_ENV=isce2_mintpy_v1 bash /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scripts/run_mintpy_sbas_unified_env_smoketest_ubuntu2404.sh /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/configs/sample_smallbaseline_lt1_e123p3_n46p1.cfg /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1/stack_work/mintpy_sbas_unified_v1
-```
-
-### 4. Export publish bundle in the unified env
-
-```text
-wsl -d Ubuntu-24.04 env MINTPY_ENV=isce2_mintpy_v1 bash /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scripts/export_mintpy_publish_products_unified_env_ubuntu2404.sh /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1/stack_work/mintpy_sbas_unified_v1 /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1/publish/mintpy_sbas_unified_v1
-```
-
-## Comparison Checklist
-
-When this phase is executed, compare it against the bridge route on:
-
-- package versions after install
-- whether `prep_isce.py` imports cleanly without bridge
-- whether `load_data` succeeds
-- whether the strict-mask step is still required
-- whether the patched launcher is still required
-- whether output files match the existing bridge-based artifact set
-- whether geocode/export still succeeds from the unified env
-
-## Current Status
-
-Successful environment:
-
-- `/home/administrator/miniconda3/envs/isce2_mintpy_v1`
-
-Observed package/version state in the successful unified env:
-
-- `conda list` shows:
-  - `mintpy 1.6.3`
-- runtime `mintpy.__version__` reports:
-  - `1.6.2`
-- `isce` import path:
-  - `/home/administrator/miniconda3/envs/isce2_mintpy_v1/lib/python3.11/site-packages/isce/__init__.py`
-- `mintpy` import path:
-  - `/home/administrator/miniconda3/envs/isce2_mintpy_v1/lib/python3.11/site-packages/mintpy/__init__.py`
-- `h5py`:
-  - `3.15.1`
-
-Successful unified-env SBAS work directory:
-
-- `/mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1/stack_work/mintpy_sbas_unified_v1`
-
-Successful unified-env publish directory:
-
-- `/mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1/publish/mintpy_sbas_unified_v1`
-
-Validated in the unified env:
-
-- `prep_isce.py -h` works without the `isce` bridge
-- `load_data` succeeded
-- strict-mask generation succeeded
-- `modify_network -> velocity` succeeded
-- publish export succeeded through geocoded HDF5, GeoTIFF, preview, and `manifest.json`
-
-Observed unified-env output set under `mintpy_sbas_unified_v1/`:
-
-- `timeseries.h5`
-- `velocity.h5`
-- `temporalCoherence.h5`
-- `maskTempCoh.h5`
-- `maskAllValid.h5`
-- `avgSpatialCoh.h5`
-- `numTriNonzeroIntAmbiguity.h5`
-- `numTriNonzeroIntAmbiguity.png`
-
-Observed publish bundle under `publish/mintpy_sbas_unified_v1/`:
-
-- `manifest.json`
-- `assets/geo_timeseries.h5`
-- `assets/geo_velocity.h5`
-- `assets/geo_temporalCoherence.h5`
-- `assets/geo_maskTempCoh.h5`
-- `assets/velocity.tif`
-- `assets/temporalCoherence.tif`
-- `assets/maskTempCoh.tif`
-- `preview/velocity_preview.png`
-- `preview/numTriNonzeroIntAmbiguity.png`
-- `metadata/smallbaselineApp.cfg`
-- `metadata/source_quality_summary.json`
-
-Quality summary matched the bridge-based route:
-
-- `maskAllValid`:
-  - `1219001 / 4076199`
-  - `29.91%`
-- `maskTempCoh`:
-  - `62987 / 4076199`
-  - `1.55%`
-
-Still required in the unified env:
-
-- strict `maskAllValid.h5` before inversion
-- repo-local patched `smallbaselineApp` launcher
-
-Prepared:
-
-- unified-env bootstrap script
-- unified-env MintPy runner
-- unified-env SBAS smoke-test runner
-- unified-env publish-export wrapper
-
-Completed:
-
-- actual clone + install execution
-- actual smoke-test result capture
-- actual publish-export capture
-
-Pending:
-
-- deeper comparison of output metadata against the bridge route
-- decide whether unified env or bridge env should be the default production candidate
-- decide whether to pin the runtime to the conda package label `1.6.3` or the internal MintPy version string `1.6.2`
-
-## Current Judgment
-
-At experiment level, the unified environment is now viable.
-
-This phase confirms:
-
-- the current LT-1 SBAS route does not fundamentally require the `isce` bridge
-- a recreated `isce2 + mintpy` WSL env can complete:
-  - MintPy load/inversion
-  - geocode/export
-  - publish-bundle generation
-
-Current recommendation:
-
-- keep the bridge route as the already-known baseline until a fuller diff is written
-- but treat the unified env as a valid candidate for the future production runtime

experiments/isce2_sbas_timeseries/notes/PHASE4_UNIFIED_ENV_REPLAY_PHASE2_20260408.md

@@ -1,193 +0,0 @@
-# Phase 4 Unified-Env Replay On Fresh Phase-2 Workspace
-
-Updated: 2026-04-08
-
-## Goal
-
-Re-run the already validated unified-env SBAS route on the fresh workspace:
-
-- `scratch/phase2_bridge_smoketest_20260406`
-
-This checks that the current experiment does not rely on the older sample workspace only.
-
-## Inputs
-
-- WSL distro:
-  - `Ubuntu-24.04`
-- unified env:
-  - `/home/administrator/miniconda3/envs/isce2_mintpy_v1`
-- stack config:
-  - `configs/phase2_bridge_smoketest_20260406_smallbaseline.cfg`
-- stack workspace:
-  - `/mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/phase2_bridge_smoketest_20260406`
-- MintPy work dir:
-  - `/mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/phase2_bridge_smoketest_20260406/stack_work/mintpy_sbas_unified_phase2_20260407`
-- publish dir:
-  - `/mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/phase2_bridge_smoketest_20260406/publish/mintpy_sbas_unified_phase2_20260407`
-
-## Successful Commands
-
-Unified-env MintPy smoke test:
-
-```text
-wsl -d Ubuntu-24.04 env MINTPY_ENV=isce2_mintpy_v1 bash /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scripts/run_mintpy_sbas_unified_env_smoketest_ubuntu2404.sh /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/configs/phase2_bridge_smoketest_20260406_smallbaseline.cfg /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/phase2_bridge_smoketest_20260406/stack_work/mintpy_sbas_unified_phase2_20260407
-```
-
-Unified-env publish export:
-
-```text
-wsl -d Ubuntu-24.04 env MINTPY_ENV=isce2_mintpy_v1 bash /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scripts/export_mintpy_publish_products_unified_env_ubuntu2404.sh /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/phase2_bridge_smoketest_20260406/stack_work/mintpy_sbas_unified_phase2_20260407 /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/phase2_bridge_smoketest_20260406/publish/mintpy_sbas_unified_phase2_20260407
-```
-
-## Result
-
-The fresh workspace replay succeeded through:
-
-- `load_data`
-- strict `maskAllValid.h5` generation
-- `modify_network`
-- `reference_point`
-- `quick_overview`
-- `invert_network`
-- `reference_date`
-- `velocity`
-- geocode/export
-- publish-bundle generation
-
-This confirms the current fresh workspace now reaches the same experiment boundary as the earlier baseline sample:
-
-- radar-coordinate MintPy runtime products
-- geocoded publish bundle
-
-## Runtime Output Snapshot
-
-Generated under `stack_work/mintpy_sbas_unified_phase2_20260407/`:
-
-- `timeseries.h5`
-  - `82579888` bytes
-- `velocity.h5`
-  - `83086408` bytes
-- `temporalCoherence.h5`
-  - `16632424` bytes
-- `maskTempCoh.h5`
-  - `4136848` bytes
-- `maskAllValid.h5`
-  - `4095215` bytes
-- `avgSpatialCoh.h5`
-  - `16631784` bytes
-- `numTriNonzeroIntAmbiguity.h5`
-  - `16632000` bytes
-- `numTriNonzeroIntAmbiguity.png`
-  - `232923` bytes
-
-## Publish Bundle Snapshot
-
-Generated under `publish/mintpy_sbas_unified_phase2_20260407/`:
-
-- `manifest.json`
-  - `32442` bytes
-- `assets/geo_timeseries.h5`
-  - `304443360` bytes
-- `assets/geo_velocity.h5`
-  - `305627744` bytes
-- `assets/geo_temporalCoherence.h5`
-  - `61141152` bytes
-- `assets/geo_maskTempCoh.h5`
-  - `15260536` bytes
-- `assets/velocity.tif`
-  - `60318026` bytes
-- `assets/temporalCoherence.tif`
-  - `60318026` bytes
-- `assets/maskTempCoh.tif`
-  - `15094802` bytes
-- `preview/velocity_preview.png`
-  - `813928` bytes
-- `preview/numTriNonzeroIntAmbiguity.png`
-  - `232923` bytes
-- `metadata/smallbaselineApp.cfg`
-  - `26419` bytes
-- `metadata/source_quality_summary.json`
-  - `403` bytes
-
-## Quality Summary
-
-From `metadata/source_quality_summary.json`:
-
-- `maskAllValid`
-  - `1219067 / 4076199`
-  - `29.91%`
-- `maskTempCoh`
-  - `63092 / 4076199`
-  - `1.55%`
-- preview stretch:
-  - `vmin = -0.2251889556646347`
-  - `vmax = 0.2251889556646347`
-
-## Findings
-
-### 1. The fresh workspace replay is reproducible
-
-The new workspace produced:
-
-- the full 10-pair interferogram stack
-- MintPy `timeseries.h5`
-- MintPy `velocity.h5`
-- publish-layer geocoded HDF5 / GeoTIFF / preview / `manifest.json`
-
-This is the current strongest experiment proof that the SBAS route is not tied to the earlier historical scratch directory.
-
-### 2. The same two MintPy experiment helpers are still required
-
-The unified env still depends on:
-
-- `create_mintpy_all_ifgram_mask.py`
-- `run_smallbaselineApp_patched.py`
-
-Current interpretation:
-
-- unified env removes the temporary `isce` bridge
-- it does not remove the current strict-mask or patched-launcher workarounds
-
-### 3. Offline water-mask strategy remains valid
-
-This replay consumed the synthetic all-land `waterMask.rdr` created earlier in the fresh workspace.
-
-No Earthdata / `SWBD` download was needed for the MintPy or publish stages.
-
-### 4. Geocode/export completed with a tolerable warning
-
-`save_gdal.py` warned that no EPSG / UTM metadata was found and assumed:
-
-- `EPSG:4326`
-
-For this experiment chain, that is acceptable because the export was already driven by latitude / longitude lookup plus explicit `--lalo` sampling.
-
-This warning should still be recorded for later production hardening.
-
-### 5. `group_key` should come from system metadata
-
-This host-side replay exported a valid publish bundle, and the bundle should carry:
-
-- `"group_key": "LT1A|STRIP1|HH|DESCENDING|E123.3_N46.1"`
-
-Reason:
-
-- the bundle builder accepts `group_key` as a CLI argument
-- the LT-1 group key contains pipe characters:
-  - `LT1A|STRIP1|HH|DESCENDING|E123.3_N46.1`
-- when invoked naively from Windows PowerShell into WSL, the value may be truncated or split by the host shell
-
-Current judgment:
-
-- this is not a blocker for the SBAS scientific chain
-- future system embedding should write `group_key` from task/run metadata inside backend code instead of relying on manual shell arguments
-
-## Current Judgment
-
-The current fresh workspace now confirms the full experiment chain:
-
-- `raw LT-1 -> stripmapStack -> MintPy SBAS -> geocode/export -> publish bundle`
-
-At experiment level, the unified env remains the preferred SBAS runtime.
-
-At production-safety level, the existing D-InSAR `isce2` environment should still remain untouched.

experiments/isce2_sbas_timeseries/scripts/.gitkeep

@@ -1 +0,0 @@
-

experiments/isce2_sbas_timeseries/scripts/build_lt1_stack_prep.py

@@ -1,647 +0,0 @@
-#!/usr/bin/env python3
-from __future__ import annotations
-
-import argparse
-import importlib.util
-import json
-import re
-import sys
-from dataclasses import dataclass
-from datetime import datetime
-from pathlib import Path, PurePosixPath
-from typing import Any, Dict, List, Optional
-
-
-REPO_ROOT = Path(__file__).resolve().parents[3]
-DEFAULT_MANIFEST_PATH = (
-    REPO_ROOT
-    / "experiments"
-    / "isce2_sbas_timeseries"
-    / "configs"
-    / "sample_stack_e123p3_n46p1.json"
-)
-DEFAULT_SHARED_ENV_NAME = "insar_wsl_v1"
-DEFAULT_CONDA_ROOT_WSL = "/home/administrator/miniconda3"
-DEFAULT_CONDA_WSL = f"{DEFAULT_CONDA_ROOT_WSL}/bin/conda"
-SUPPORTED_STACK_WORKFLOWS = ("slc", "interferogram", "ionosphere")
-
-
-def windows_to_wsl(path: str | Path) -> str:
-    text = str(path)
-    match = re.match(r"^([A-Za-z]):[\\/](.*)$", text)
-    if not match:
-        return text.replace("\\", "/")
-    drive = match.group(1).lower()
-    tail = match.group(2).replace("\\", "/").lstrip("/")
-    return f"/mnt/{drive}/{tail}"
-
-
-def load_isce2_input_helper_module():
-    helper_path = REPO_ROOT / "backend" / "app" / "isce2_pipeline" / "lt1_input_resolver.py"
-    spec = importlib.util.spec_from_file_location("lt1_orbit_helper", helper_path)
-    if spec is None or spec.loader is None:
-        raise RuntimeError(f"Unable to load orbit helper module: {helper_path}")
-    module = importlib.util.module_from_spec(spec)
-    sys.modules[spec.name] = module
-    spec.loader.exec_module(module)
-    return module
-
-
-ISCE2_INPUT_HELPER = load_isce2_input_helper_module()
-
-
-def _default_python_wsl(env_name: str) -> str:
-    normalized_env = str(env_name or "").strip() or DEFAULT_SHARED_ENV_NAME
-    return f"{DEFAULT_CONDA_ROOT_WSL}/envs/{normalized_env}/bin/python"
-
-
-def _resolve_runtime_paths(env_values: Dict[str, Any]) -> Dict[str, str]:
-    env_name = str(
-        env_values.get("TIMESERIES_ENV_NAME")
-        or env_values.get("WSL_SHARED_CONDA_ENV")
-        or DEFAULT_SHARED_ENV_NAME
-    ).strip() or DEFAULT_SHARED_ENV_NAME
-    python_wsl = str(
-        env_values.get("TIMESERIES_PYTHON")
-        or env_values.get("WSL_SHARED_PYTHON")
-        or env_values.get("ISCE2_PYTHON")
-        or _default_python_wsl(env_name)
-    ).strip() or _default_python_wsl(env_name)
-
-    python_path = PurePosixPath(python_wsl)
-    env_root = python_path.parent.parent
-    conda_root = env_root.parent.parent
-    conda_bin_wsl = str(conda_root / "bin" / "conda")
-    isce2_share_wsl = str(env_root / "share" / "isce2")
-    stripmap_stack_dir_wsl = str(PurePosixPath(isce2_share_wsl) / "stripmapStack")
-    stack_script_wsl = str(PurePosixPath(stripmap_stack_dir_wsl) / "stackStripMap.py")
-    stack_text_cmd = (
-        f"export PATH={stripmap_stack_dir_wsl}:$PATH; "
-        f"export PYTHONPATH={stripmap_stack_dir_wsl}:{isce2_share_wsl}${{PYTHONPATH:+:$PYTHONPATH}}; "
-    )
-
-    return {
-        "env_name": env_name,
-        "python_wsl": python_wsl,
-        "conda_bin_wsl": conda_bin_wsl,
-        "isce2_share_wsl": isce2_share_wsl,
-        "stripmap_stack_dir_wsl": stripmap_stack_dir_wsl,
-        "stack_script_wsl": stack_script_wsl,
-        "stack_text_cmd": stack_text_cmd,
-    }
-
-
-def require_file(path: Path, label: str) -> None:
-    if not path.exists():
-        raise FileNotFoundError(f"Missing {label}: {path}")
-
-
-def shelve_stem_exists(stem: Path) -> bool:
-    for suffix in ("", ".db", ".dat", ".dir", ".bak"):
-        if Path(str(stem) + suffix).exists():
-            return True
-    return False
-
-
-@dataclass
-class ScenePlan:
-    date: str
-    target_dir_windows: str
-    target_dir_wsl: str
-    source_scene_json_windows: str
-    source_scene_json_wsl: str
-    source_tiff_windows: str
-    source_tiff_wsl: str
-    source_meta_windows: str
-    source_meta_wsl: str
-    orbit_xml_windows: Optional[str]
-    orbit_xml_wsl: Optional[str]
-    orbit_xml_exists: bool
-    orbit_resolution_mode: Optional[str]
-    orbit_resolution_error: Optional[str]
-    source_exists: bool
-    scene_start_utc: str
-    scene_stop_utc: str
-    orbit_window_start_utc: str
-    orbit_window_stop_utc: str
-    expected_slc_windows: str
-    expected_slc_wsl: str
-    expected_slc_xml_windows: str
-    expected_slc_xml_wsl: str
-    expected_data_shelve_windows: str
-    expected_data_shelve_wsl: str
-    materialized_slc_exists: bool
-    materialized_data_exists: bool
-    stack_ready: bool
-    status: str
-
-
-def build_scene_plan(
-    scene: Dict[str, Any],
-    slc_root: Path,
-    orbit_pool: Optional[Path],
-    orbit_stage_dir: Path,
-    margin_sec: float,
-) -> ScenePlan:
-    date = str(scene["imaging_date"])
-    satellite = str(scene["satellite"])
-    source_tiff = Path(scene["tiff_path"])
-    source_meta = Path(scene["meta_path"])
-    require_file(source_tiff, f"scene TIFF for {date}")
-    require_file(source_meta, f"scene meta XML for {date}")
-
-    scene_start_dt, scene_stop_dt = ISCE2_INPUT_HELPER.parse_scene_window(source_meta, margin_sec=0.0)
-    orbit_window_start_dt, orbit_window_stop_dt = ISCE2_INPUT_HELPER.parse_scene_window(
-        source_meta,
-        margin_sec=margin_sec,
-    )
-    scene_start_utc = scene_start_dt.isoformat()
-    scene_stop_utc = scene_stop_dt.isoformat()
-    orbit_window_start_utc = orbit_window_start_dt.isoformat()
-    orbit_window_stop_utc = orbit_window_stop_dt.isoformat()
-
-    target_dir = slc_root / date
-    expected_slc = target_dir / f"{date}.slc"
-    expected_slc_xml = target_dir / f"{date}.slc.xml"
-    expected_data = target_dir / "data"
-    source_scene_json = target_dir / "source_scene.json"
-
-    orbit_xml: Optional[Path] = None
-    orbit_resolution_mode: Optional[str] = None
-    orbit_resolution_error: Optional[str] = None
-    if orbit_pool is not None:
-        try:
-            orbit_resolution = ISCE2_INPUT_HELPER.ensure_lt1_orbit_xml(
-                date_yyyymmdd=date,
-                satellite=satellite,
-                annotation_xml=source_meta,
-                orbit_root=orbit_pool,
-                orbit_output_dir=orbit_stage_dir,
-                margin_sec=margin_sec,
-            )
-            orbit_xml = orbit_resolution.path
-            orbit_resolution_mode = orbit_resolution.source
-        except Exception as exc:
-            orbit_resolution_error = str(exc)
-
-    materialized_slc_exists = expected_slc.exists() and expected_slc_xml.exists()
-    materialized_data_exists = shelve_stem_exists(expected_data)
-    stack_ready = bool(orbit_xml and materialized_slc_exists and materialized_data_exists)
-
-    if not orbit_xml:
-        status = "missing_orbit_xml"
-    elif not materialized_slc_exists and not materialized_data_exists:
-        status = "waiting_for_scene_materializer"
-    elif not materialized_slc_exists:
-        status = "missing_slc"
-    elif not materialized_data_exists:
-        status = "missing_data_shelve"
-    else:
-        status = "ready"
-
-    return ScenePlan(
-        date=date,
-        target_dir_windows=str(target_dir),
-        target_dir_wsl=windows_to_wsl(target_dir),
-        source_scene_json_windows=str(source_scene_json),
-        source_scene_json_wsl=windows_to_wsl(source_scene_json),
-        source_tiff_windows=str(source_tiff),
-        source_tiff_wsl=windows_to_wsl(source_tiff),
-        source_meta_windows=str(source_meta),
-        source_meta_wsl=windows_to_wsl(source_meta),
-        orbit_xml_windows=str(orbit_xml) if orbit_xml else None,
-        orbit_xml_wsl=windows_to_wsl(orbit_xml) if orbit_xml else None,
-        orbit_xml_exists=bool(orbit_xml),
-        orbit_resolution_mode=orbit_resolution_mode,
-        orbit_resolution_error=orbit_resolution_error,
-        source_exists=True,
-        scene_start_utc=scene_start_utc,
-        scene_stop_utc=scene_stop_utc,
-        orbit_window_start_utc=orbit_window_start_utc,
-        orbit_window_stop_utc=orbit_window_stop_utc,
-        expected_slc_windows=str(expected_slc),
-        expected_slc_wsl=windows_to_wsl(expected_slc),
-        expected_slc_xml_windows=str(expected_slc_xml),
-        expected_slc_xml_wsl=windows_to_wsl(expected_slc_xml),
-        expected_data_shelve_windows=str(expected_data),
-        expected_data_shelve_wsl=windows_to_wsl(expected_data),
-        materialized_slc_exists=materialized_slc_exists,
-        materialized_data_exists=materialized_data_exists,
-        stack_ready=stack_ready,
-        status=status,
-    )
-
-
-def render_stack_command(
-    slc_dir_wsl: str,
-    dem_wsl: str,
-    work_dir_wsl: str,
-    reference_date: str,
-    workflow: str,
-    runtime: Dict[str, str],
-) -> List[str]:
-    return [
-        runtime["conda_bin_wsl"],
-        "run",
-        "-n",
-        runtime["env_name"],
-        "python",
-        runtime["stack_script_wsl"],
-        "-s",
-        slc_dir_wsl,
-        "-d",
-        dem_wsl,
-        "-w",
-        work_dir_wsl,
-        "-m",
-        reference_date,
-        "--nofocus",
-        "-W",
-        workflow,
-        "-u",
-        "snaphu",
-        "-c",
-        runtime["stack_text_cmd"],
-    ]
-
-
-def shell_quote(value: str) -> str:
-    return "'" + value.replace("'", "'\"'\"'") + "'"
-
-
-def render_shell_command(argv: List[str]) -> str:
-    return " ".join(shell_quote(item) for item in argv)
-
-
-def build_blockers(scene_plans: List[ScenePlan], orbit_pool: Optional[Path], dem_path: Optional[Path]) -> List[str]:
-    blockers: List[str] = []
-    if orbit_pool is None:
-        blockers.append("ORBIT_POOL_ISCE2 was not resolved.")
-    if dem_path is None:
-        blockers.append("Prepared DEM with .xml sidecar was not resolved.")
-
-    missing_orbit = [item.date for item in scene_plans if not item.orbit_xml_exists]
-    if missing_orbit:
-        blockers.append("Missing orbit XML for dates: " + ", ".join(missing_orbit))
-    orbit_errors = [f"{item.date}: {item.orbit_resolution_error}" for item in scene_plans if item.orbit_resolution_error]
-    if orbit_errors:
-        blockers.append("Orbit resolution errors: " + "; ".join(orbit_errors))
-
-    missing_slc = [item.date for item in scene_plans if not item.materialized_slc_exists]
-    if missing_slc:
-        blockers.append("Materialized .slc/.slc.xml are missing for dates: " + ", ".join(missing_slc))
-
-    missing_data = [item.date for item in scene_plans if not item.materialized_data_exists]
-    if missing_data:
-        blockers.append("ISCE data shelve is missing for dates: " + ", ".join(missing_data))
-
-    return blockers
-
-
-def render_contract_markdown(report: Dict[str, Any]) -> str:
-    lines: List[str] = []
-    ready = bool(report["readiness"]["ready_for_stackStripMap_nofocus"])
-    lines.append("# LT-1 Stack Prep Contract")
-    lines.append("")
-    lines.append(f"Generated: {report['generated_at_utc']}")
-    lines.append("")
-    lines.append("## Selected Stack")
-    lines.append("")
-    lines.append(f"- Group key: `{report['group_key']}`")
-    lines.append(f"- Reference date: `{report['reference_date']}`")
-    lines.append(f"- Workflow: `{report['processing_workflow']}`")
-    lines.append(f"- Scene count: `{report['scene_count']}`")
-    lines.append("")
-    lines.append("## Resolved Runtime Inputs")
-    lines.append("")
-    lines.append(f"- Orbit pool (Windows): `{report['resolved_dependencies']['orbit_pool_windows'] or 'UNRESOLVED'}`")
-    lines.append(f"- Orbit pool (WSL): `{report['resolved_dependencies']['orbit_pool_wsl'] or 'UNRESOLVED'}`")
-    lines.append(f"- DEM (Windows): `{report['resolved_dependencies']['dem_path_windows'] or 'UNRESOLVED'}`")
-    lines.append(f"- DEM (WSL): `{report['resolved_dependencies']['dem_path_wsl'] or 'UNRESOLVED'}`")
-    lines.append("")
-    lines.append("## Confirmed stripmapStack Contract")
-    lines.append("")
-    lines.append("- `stackStripMap.py --nofocus` discovers dates from `SLC/YYYYMMDD/YYYYMMDD.slc`.")
-    lines.append("- `topo.py` opens `SLC/YYYYMMDD/data` for the reference acquisition.")
-    lines.append("- `geo2rdr.py` opens `SLC/YYYYMMDD/data` for each secondary acquisition.")
-    lines.append("- Therefore each acquisition directory must contain at least:")
-    lines.append("  - `YYYYMMDD.slc`")
-    lines.append("  - `YYYYMMDD.slc.xml`")
-    lines.append("  - `data` shelve with `frame` and optional `doppler`")
-    lines.append("")
-    lines.append("## Scene Status")
-    lines.append("")
-    lines.append("| Date | Orbit XML | SLC | Data | Status |")
-    lines.append("| --- | --- | --- | --- | --- |")
-    for scene in report["scenes"]:
-        orbit_ok = "yes" if scene["orbit_xml_exists"] else "no"
-        slc_ok = "yes" if scene["materialized_slc_exists"] else "no"
-        data_ok = "yes" if scene["materialized_data_exists"] else "no"
-        lines.append(f"| {scene['date']} | {orbit_ok} | {slc_ok} | {data_ok} | `{scene['status']}` |")
-    lines.append("")
-    lines.append("## Draft stackStripMap Command")
-    lines.append("")
-    lines.append("```bash")
-    lines.append(report["stack_command"]["shell"])
-    lines.append("```")
-    lines.append("")
-    lines.append("## Current Blockers")
-    lines.append("")
-    blockers = report["readiness"]["blocking_reasons"]
-    if blockers:
-        for blocker in blockers:
-            lines.append(f"- {blocker}")
-    else:
-        lines.append("- none")
-    lines.append("")
-    lines.append("## Next Tasks")
-    lines.append("")
-    if ready:
-        lines.append("- Execute `run_01_reference` and confirm geometry generation succeeds.")
-        lines.append("- Execute `run_02` to `run_07` step by step and record any LT-1-specific failures.")
-        lines.append("- Inspect `baselines/`, `configs/`, and the first coarse coregistration outputs.")
-        lines.append("- Install MintPy only after the stack run outputs are stable.")
-    else:
-        lines.append("- Use the LT-1 scene materializer to finish the remaining acquisitions under the generated `SLC/` root.")
-        lines.append("- Re-run the generated preflight script, then execute `stackStripMap.py --nofocus`.")
-        lines.append("- Install MintPy only after the stack materializer contract is working end to end.")
-    lines.append("")
-    return "\n".join(lines)
-
-
-def render_run_script(report: Dict[str, Any]) -> str:
-    slc_dir = report["workspace"]["slc_dir_wsl"]
-    work_dir = report["workspace"]["stack_work_dir_wsl"]
-    dem_path = report["resolved_dependencies"]["dem_path_wsl"] or "__MISSING_DEM__"
-    reference_date = report["reference_date"]
-    dates = " ".join(scene["date"] for scene in report["scenes"])
-    command = report["stack_command"]["shell"]
-    runtime = report["runtime"]
-
-    return f"""#!/usr/bin/env bash
-set -euo pipefail
-
-SLC_DIR={shell_quote(slc_dir)}
-WORK_DIR={shell_quote(work_dir)}
-DEM={shell_quote(dem_path)}
-REFERENCE_DATE={shell_quote(reference_date)}
-CONDA_ENV={shell_quote(runtime["env_name"])}
-CONDA_BIN={shell_quote(runtime["conda_bin_wsl"])}
-ISCE2_SHARE={shell_quote(runtime["isce2_share_wsl"])}
-STRIPMAP_STACK_DIR={shell_quote(runtime["stripmap_stack_dir_wsl"])}
-DATES=({dates})
-
-export PYTHONPATH="$STRIPMAP_STACK_DIR:$ISCE2_SHARE${{PYTHONPATH:+:$PYTHONPATH}}"
-export PATH="$STRIPMAP_STACK_DIR:$PATH"
-
-echo "LT-1 stripmap stack dry-run preflight"
-echo "SLC root: $SLC_DIR"
-echo "Work dir: $WORK_DIR"
-echo "DEM: $DEM"
-echo "Reference date: $REFERENCE_DATE"
-echo "Conda env: $CONDA_ENV"
-echo "Conda bin: $CONDA_BIN"
-echo "PYTHONPATH: $PYTHONPATH"
-echo "PATH prefix: $STRIPMAP_STACK_DIR"
-
-missing=0
-for d in "${{DATES[@]}}"; do
-  if [[ ! -f "$SLC_DIR/$d/$d.slc" ]]; then
-    echo "MISSING: $SLC_DIR/$d/$d.slc"
-    missing=1
-  fi
-  if [[ ! -f "$SLC_DIR/$d/$d.slc.xml" ]]; then
-    echo "MISSING: $SLC_DIR/$d/$d.slc.xml"
-    missing=1
-  fi
-  if [[ ! -e "$SLC_DIR/$d/data" && ! -e "$SLC_DIR/$d/data.db" && ! -e "$SLC_DIR/$d/data.dat" && ! -e "$SLC_DIR/$d/data.dir" && ! -e "$SLC_DIR/$d/data.bak" ]]; then
-    echo "MISSING: $SLC_DIR/$d/data"
-    missing=1
-  fi
-done
-
-if [[ "$missing" -ne 0 ]]; then
-  echo "Dry-run only. LT-1 scene materialization is still missing."
-  exit 2
-fi
-
-echo "Preflight passed. Running stackStripMap."
-{command}
-"""
-
-
-def write_json(path: Path, payload: Dict[str, Any]) -> None:
-    path.write_text(json.dumps(payload, indent=2, ensure_ascii=False), encoding="utf-8")
-
-
-def parse_args() -> argparse.Namespace:
-    parser = argparse.ArgumentParser(
-        description="Build a dry-run LT-1 SBAS stack-prep workspace for ISCE2 stripmapStack."
-    )
-    parser.add_argument(
-        "--manifest-path",
-        default=str(DEFAULT_MANIFEST_PATH),
-        help="Path to the selected stack manifest JSON.",
-    )
-    parser.add_argument(
-        "--scratch-root",
-        default=None,
-        help="Override the stack scratch root directory. Defaults to proposed_scratch_windows in the manifest.",
-    )
-    parser.add_argument(
-        "--orbit-pool",
-        default=None,
-        help="Override ORBIT_POOL_ISCE2 (Windows path containing LT1A_GpsData_GAS_C_YYYYMMDD.xml).",
-    )
-    parser.add_argument(
-        "--dem-path",
-        default=None,
-        help="Override the prepared DEM base path (must have a .xml sidecar).",
-    )
-    parser.add_argument(
-        "--orbit-margin-sec",
-        type=float,
-        default=60.0,
-        help="Margin used when reporting the recommended orbit clip window.",
-    )
-    parser.add_argument(
-        "--workflow",
-        default="slc",
-        choices=SUPPORTED_STACK_WORKFLOWS,
-        help="stripmapStack workflow to generate: slc, interferogram, or ionosphere.",
-    )
-    return parser.parse_args()
-
-
-def main() -> int:
-    args = parse_args()
-    env_values = ISCE2_INPUT_HELPER.load_env_file(REPO_ROOT / ".env")
-    runtime = _resolve_runtime_paths(env_values)
-
-    manifest_path = Path(args.manifest_path).resolve()
-    require_file(manifest_path, "stack manifest")
-    manifest = json.loads(manifest_path.read_text(encoding="utf-8"))
-
-    scratch_root = Path(args.scratch_root or manifest["proposed_scratch_windows"]).resolve()
-    slc_root = scratch_root / "SLC"
-    orbits_dir = scratch_root / "orbits"
-    logs_dir = scratch_root / "logs"
-    notes_dir = scratch_root / "notes"
-    inputs_dir = scratch_root / "inputs"
-    stack_work_dir = scratch_root / "stack_work"
-
-    for path in (scratch_root, slc_root, orbits_dir, logs_dir, notes_dir, inputs_dir, stack_work_dir):
-        path.mkdir(parents=True, exist_ok=True)
-
-    orbit_pool = ISCE2_INPUT_HELPER.resolve_orbit_pool_path(
-        explicit_path=args.orbit_pool,
-        env_values=env_values,
-        default_candidates=ISCE2_INPUT_HELPER.DEFAULT_WINDOWS_ORBIT_POOL_CANDIDATES,
-    )
-    local_dem_candidate = inputs_dir / "dem" / "stack_dem_window.wgs84"
-    dem_path = ISCE2_INPUT_HELPER.resolve_prepared_dem_path(
-        explicit_path=args.dem_path,
-        env_values=env_values,
-        extra_candidates=[local_dem_candidate],
-        default_candidates=ISCE2_INPUT_HELPER.DEFAULT_WINDOWS_DEM_CANDIDATES,
-    )
-
-    scene_plans = [
-        build_scene_plan(
-            scene,
-            slc_root=slc_root,
-            orbit_pool=orbit_pool,
-            orbit_stage_dir=orbits_dir,
-            margin_sec=args.orbit_margin_sec,
-        )
-        for scene in manifest["scenes"]
-    ]
-    scene_plans.sort(key=lambda item: item.date)
-
-    for plan, source_scene in zip(scene_plans, sorted(manifest["scenes"], key=lambda item: item["imaging_date"])):
-        target_dir = Path(plan.target_dir_windows)
-        target_dir.mkdir(parents=True, exist_ok=True)
-        scene_payload = dict(source_scene)
-        scene_payload["stack_prep"] = {
-            "date": plan.date,
-            "target_dir_windows": plan.target_dir_windows,
-            "target_dir_wsl": plan.target_dir_wsl,
-            "orbit_xml_windows": plan.orbit_xml_windows,
-            "orbit_xml_wsl": plan.orbit_xml_wsl,
-            "orbit_resolution_mode": plan.orbit_resolution_mode,
-            "orbit_resolution_error": plan.orbit_resolution_error,
-            "scene_start_utc": plan.scene_start_utc,
-            "scene_stop_utc": plan.scene_stop_utc,
-            "orbit_window_start_utc": plan.orbit_window_start_utc,
-            "orbit_window_stop_utc": plan.orbit_window_stop_utc,
-            "expected_slc_windows": plan.expected_slc_windows,
-            "expected_slc_xml_windows": plan.expected_slc_xml_windows,
-            "expected_data_shelve_windows": plan.expected_data_shelve_windows,
-            "status": plan.status,
-        }
-        write_json(target_dir / "source_scene.json", scene_payload)
-
-    stack_command_argv = render_stack_command(
-        slc_dir_wsl=windows_to_wsl(slc_root),
-        dem_wsl=windows_to_wsl(dem_path) if dem_path else "__MISSING_DEM__",
-        work_dir_wsl=windows_to_wsl(stack_work_dir),
-        reference_date=manifest["reference_date"],
-        workflow=args.workflow,
-        runtime=runtime,
-    )
-
-    blockers = build_blockers(scene_plans, orbit_pool=orbit_pool, dem_path=dem_path)
-    readiness = {
-        "all_orbits_resolved": all(item.orbit_xml_exists for item in scene_plans),
-        "all_materialized_slc_present": all(item.materialized_slc_exists for item in scene_plans),
-        "all_data_shelves_present": all(item.materialized_data_exists for item in scene_plans),
-        "ready_for_stackStripMap_nofocus": not blockers,
-        "blocking_reasons": blockers,
-    }
-
-    report: Dict[str, Any] = {
-        "manifest_version": 1,
-        "generated_at_utc": datetime.utcnow().replace(microsecond=0).isoformat() + "Z",
-        "source_manifest_windows": str(manifest_path),
-        "source_manifest_wsl": windows_to_wsl(manifest_path),
-        "group_key": manifest["group_key"],
-        "tile_key": manifest["tile_key"],
-        "scene_count": manifest["scene_count"],
-        "reference_date": manifest["reference_date"],
-        "reference_strategy": manifest["reference_strategy"],
-        "processing_workflow": args.workflow,
-        "sensor_name": "LUTAN1",
-        "stack_driver": "isce2.stripmapStack.stackStripMap",
-        "runtime": runtime,
-        "workspace": {
-            "root_windows": str(scratch_root),
-            "root_wsl": windows_to_wsl(scratch_root),
-            "slc_dir_windows": str(slc_root),
-            "slc_dir_wsl": windows_to_wsl(slc_root),
-            "orbits_dir_windows": str(orbits_dir),
-            "orbits_dir_wsl": windows_to_wsl(orbits_dir),
-            "logs_dir_windows": str(logs_dir),
-            "logs_dir_wsl": windows_to_wsl(logs_dir),
-            "notes_dir_windows": str(notes_dir),
-            "notes_dir_wsl": windows_to_wsl(notes_dir),
-            "inputs_dir_windows": str(inputs_dir),
-            "inputs_dir_wsl": windows_to_wsl(inputs_dir),
-            "stack_work_dir_windows": str(stack_work_dir),
-            "stack_work_dir_wsl": windows_to_wsl(stack_work_dir),
-        },
-        "resolved_dependencies": {
-            "orbit_pool_windows": str(orbit_pool) if orbit_pool else None,
-            "orbit_pool_wsl": windows_to_wsl(orbit_pool) if orbit_pool else None,
-            "dem_path_windows": str(dem_path) if dem_path else None,
-            "dem_path_wsl": windows_to_wsl(dem_path) if dem_path else None,
-        },
-        "stack_contract": {
-            "mode": "nofocus",
-            "workflow": args.workflow,
-            "required_per_acquisition_files": [
-                "YYYYMMDD.slc",
-                "YYYYMMDD.slc.xml",
-                "data shelve",
-            ],
-            "current_source_layout": "per_scene_folder_with_tiff_meta_rpc",
-            "adapter_needed": True,
-            "adapter_goal": "materialize a stripmapStack-ready date directory from LT-1 TIFF/meta/orbit inputs",
-        },
-        "stack_command": {
-            "argv": stack_command_argv,
-            "shell": render_shell_command(stack_command_argv),
-        },
-        "readiness": readiness,
-        "scenes": [plan.__dict__ for plan in scene_plans],
-        "next_tasks": [
-            "Use the LT-1 scene materializer to build YYYYMMDD.slc and data shelve for the remaining acquisitions.",
-            "Keep raw scene data external and store only lightweight source manifests plus generated ISCE products under scratch/SLC/YYYYMMDD.",
-            f"Run stripmapStack in --nofocus mode with workflow={args.workflow} once every date directory is materialized.",
-            "Install MintPy only after stackStripMap produces stable interferogram outputs.",
-        ],
-    }
-
-    report_path = scratch_root / "stack_input_manifest.json"
-    contract_path = scratch_root / "stack_prep_contract.md"
-    run_script_path = scratch_root / "run_stripmap_stack_dryrun.sh"
-
-    write_json(report_path, report)
-    contract_path.write_text(render_contract_markdown(report), encoding="utf-8")
-    run_script_path.write_text(render_run_script(report), encoding="utf-8", newline="\n")
-
-    print(f"Manifest:     {report_path}")
-    print(f"Contract:     {contract_path}")
-    print(f"Run script:   {run_script_path}")
-    print(f"Scratch root: {scratch_root}")
-    print(f"Orbit pool:   {orbit_pool if orbit_pool else 'UNRESOLVED'}")
-    print(f"DEM:          {dem_path if dem_path else 'UNRESOLVED'}")
-    print(f"Ready:        {readiness['ready_for_stackStripMap_nofocus']}")
-    if blockers:
-        print("Blockers:")
-        for blocker in blockers:
-            print(f"  - {blocker}")
-    return 0
-
-
-if __name__ == "__main__":
-    raise SystemExit(main())

experiments/isce2_sbas_timeseries/scripts/build_mintpy_publish_bundle.py

@@ -1,202 +0,0 @@
-#!/usr/bin/env python3
-"""Build a publish-style manifest and preview bundle from MintPy outputs."""
-
-from __future__ import annotations
-
-import argparse
-import json
-from pathlib import Path
-
-import h5py
-import matplotlib
-
-matplotlib.use("Agg")
-import matplotlib.pyplot as plt
-import numpy as np
-
-
-def _decode_date(value):
-    return value.decode() if isinstance(value, (bytes, np.bytes_)) else str(value)
-
-
-def _read_h5_summary(h5_path: Path) -> dict:
-    with h5py.File(h5_path, "r") as f:
-        datasets = sorted(f.keys())
-        attrs = {k: (v.item() if hasattr(v, "item") else v) for k, v in f.attrs.items()}
-        serializable_attrs = {}
-        for key, value in attrs.items():
-            if isinstance(value, bytes):
-                serializable_attrs[key] = value.decode()
-            elif isinstance(value, np.ndarray):
-                serializable_attrs[key] = value.tolist()
-            else:
-                serializable_attrs[key] = value
-
-        summary = {
-            "path": h5_path.name,
-            "datasets": datasets,
-            "attrs": serializable_attrs,
-        }
-
-        if "date" in f:
-            summary["dates"] = [_decode_date(x) for x in f["date"][:]]
-
-        return summary
-
-
-def _write_velocity_preview(geo_velocity_h5: Path, output_png: Path) -> dict:
-    with h5py.File(geo_velocity_h5, "r") as f:
-        velocity = f["velocity"][:]
-
-    finite = np.isfinite(velocity)
-    valid = velocity[finite]
-
-    if valid.size == 0:
-        raise RuntimeError(f"No finite velocity values found in {geo_velocity_h5}")
-
-    vmax = float(np.nanpercentile(np.abs(valid), 98))
-    vmax = max(vmax, 1e-6)
-    vmin = -vmax
-
-    fig = plt.figure(figsize=(10, 7), dpi=150)
-    ax = fig.add_subplot(111)
-    im = ax.imshow(velocity, cmap="RdBu_r", vmin=vmin, vmax=vmax)
-    ax.set_title("Velocity Preview (m/year)")
-    ax.set_xticks([])
-    ax.set_yticks([])
-    cbar = fig.colorbar(im, ax=ax, shrink=0.82)
-    cbar.set_label("m/year")
-    fig.tight_layout()
-    output_png.parent.mkdir(parents=True, exist_ok=True)
-    fig.savefig(output_png, bbox_inches="tight")
-    plt.close(fig)
-
-    return {
-        "vmin": vmin,
-        "vmax": vmax,
-        "valid_pixels": int(valid.size),
-    }
-
-
-def _count_mask_pixels(mask_h5: Path) -> dict:
-    with h5py.File(mask_h5, "r") as f:
-        dataset_name = "mask" if "mask" in f else "waterMask"
-        data = f[dataset_name][:]
-
-    total = int(data.size)
-    valid = int(np.count_nonzero(data))
-    return {
-        "dataset": dataset_name,
-        "valid_pixels": valid,
-        "total_pixels": total,
-        "valid_ratio": valid / total if total else 0.0,
-    }
-
-
-def build_bundle(mintpy_work_dir: Path, publish_dir: Path, group_key: str | None) -> None:
-    assets_dir = publish_dir / "assets"
-    preview_dir = publish_dir / "preview"
-    metadata_dir = publish_dir / "metadata"
-
-    geo_velocity_h5 = assets_dir / "geo_velocity.h5"
-    geo_timeseries_h5 = assets_dir / "geo_timeseries.h5"
-    geo_temporal_coh_h5 = assets_dir / "geo_temporalCoherence.h5"
-    geo_mask_temp_coh_h5 = assets_dir / "geo_maskTempCoh.h5"
-
-    preview_stats = _write_velocity_preview(
-        geo_velocity_h5=geo_velocity_h5,
-        output_png=preview_dir / "velocity_preview.png",
-    )
-
-    with h5py.File(mintpy_work_dir / "timeseries.h5", "r") as ts_file:
-        ref_date = ts_file.attrs.get("REF_DATE")
-        ref_x = ts_file.attrs.get("REF_X")
-        ref_y = ts_file.attrs.get("REF_Y")
-        stack_dates = [_decode_date(x) for x in ts_file["date"][:]]
-
-    manifest = {
-        "schema_version": "psinsar.publish.v1",
-        "catalog_name": "psinsar",
-        "mode": "sbas",
-        "engine_code": "isce2",
-        "processor_code": "isce2_stack_mintpy",
-        "group_key": group_key,
-        "mintpy_work_dir": str(mintpy_work_dir),
-        "publish_dir": str(publish_dir),
-        "reference_date": _decode_date(ref_date) if ref_date is not None else None,
-        "reference_point": {
-            "x": int(ref_x) if ref_x is not None else None,
-            "y": int(ref_y) if ref_y is not None else None,
-        },
-        "stack_dates": stack_dates,
-        "artifacts": [
-            {"product_type": "timeseries_cube", "path": "assets/geo_timeseries.h5"},
-            {"product_type": "velocity_map", "path": "assets/geo_velocity.h5"},
-            {"product_type": "velocity_geotiff", "path": "assets/velocity.tif"},
-            {"product_type": "temporal_coherence", "path": "assets/geo_temporalCoherence.h5"},
-            {"product_type": "temporal_coherence_geotiff", "path": "assets/temporalCoherence.tif"},
-            {"product_type": "quality_mask", "path": "assets/geo_maskTempCoh.h5"},
-            {"product_type": "quality_mask_geotiff", "path": "assets/maskTempCoh.tif"},
-            {"product_type": "preview_png", "path": "preview/velocity_preview.png"},
-            {"product_type": "diagnostic_png", "path": "preview/numTriNonzeroIntAmbiguity.png"},
-        ],
-        "quality": {
-            "mask_all_valid": _count_mask_pixels(mintpy_work_dir / "maskAllValid.h5"),
-            "mask_temp_coh": _count_mask_pixels(mintpy_work_dir / "maskTempCoh.h5"),
-            "velocity_preview": preview_stats,
-        },
-        "summaries": {
-            "geo_velocity": _read_h5_summary(geo_velocity_h5),
-            "geo_timeseries": _read_h5_summary(geo_timeseries_h5),
-            "geo_temporal_coherence": _read_h5_summary(geo_temporal_coh_h5),
-            "geo_mask_temp_coh": _read_h5_summary(geo_mask_temp_coh_h5),
-        },
-        "metadata_files": [
-            "metadata/smallbaselineApp.cfg",
-            "metadata/source_quality_summary.json",
-        ],
-    }
-
-    summary_json = {
-        "maskAllValid": manifest["quality"]["mask_all_valid"],
-        "maskTempCoh": manifest["quality"]["mask_temp_coh"],
-        "preview": manifest["quality"]["velocity_preview"],
-    }
-
-    publish_dir.mkdir(parents=True, exist_ok=True)
-    metadata_dir.mkdir(parents=True, exist_ok=True)
-
-    (publish_dir / "manifest.json").write_text(
-        json.dumps(manifest, indent=2, ensure_ascii=False),
-        encoding="utf-8",
-    )
-    (metadata_dir / "source_quality_summary.json").write_text(
-        json.dumps(summary_json, indent=2, ensure_ascii=False),
-        encoding="utf-8",
-    )
-
-    print(f"Wrote manifest: {publish_dir / 'manifest.json'}")
-    print(f"Wrote quality summary: {metadata_dir / 'source_quality_summary.json'}")
-    print(f"Wrote preview: {preview_dir / 'velocity_preview.png'}")
-
-
-def parse_args() -> argparse.Namespace:
-    parser = argparse.ArgumentParser(description="Build publish-style artifacts for MintPy SBAS outputs.")
-    parser.add_argument("--mintpy-work-dir", required=True, help="MintPy work directory containing timeseries.h5, velocity.h5, etc.")
-    parser.add_argument("--publish-dir", required=True, help="Publish output directory.")
-    parser.add_argument("--group-key", default=None, help="Optional stack group key to embed in manifest.")
-    return parser.parse_args()
-
-
-def main() -> int:
-    args = parse_args()
-    build_bundle(
-        mintpy_work_dir=Path(args.mintpy_work_dir),
-        publish_dir=Path(args.publish_dir),
-        group_key=args.group_key,
-    )
-    return 0
-
-
-if __name__ == "__main__":
-    raise SystemExit(main())

experiments/isce2_sbas_timeseries/scripts/check_env_ubuntu2404.sh

@@ -1,33 +0,0 @@
-#!/usr/bin/env bash
-set -euo pipefail
-
-CONDA_BIN="${CONDA_BIN:-/home/administrator/miniconda3/bin/conda}"
-REPO_ROOT="${REPO_ROOT:-/mnt/z/Code/Insar_management_system_v2}"
-EXP_ROOT="${EXP_ROOT:-$REPO_ROOT/experiments/isce2_sbas_timeseries}"
-
-echo "== repo =="
-echo "$REPO_ROOT"
-test -d "$REPO_ROOT"
-
-echo "== experiment root =="
-echo "$EXP_ROOT"
-test -d "$EXP_ROOT"
-
-echo "== python3 =="
-python3 --version
-
-echo "== conda env list =="
-"$CONDA_BIN" env list
-
-echo "== isce2 runtime =="
-"$CONDA_BIN" run -n isce2 python -c "import sys; import isce; print(sys.executable); print(isce.__file__)"
-
-echo "== Lutan1 sensor module =="
-"$CONDA_BIN" run -n isce2 python -c "from isce.components.isceobj.Sensor import Lutan1; print(Lutan1.__file__)"
-
-echo "== mintpy import check =="
-"$CONDA_BIN" run -n isce2 python -c "import importlib.util; print('mintpy:present' if importlib.util.find_spec('mintpy') else 'mintpy:missing')"
-
-echo "== candidate ISCE stack directories =="
-find /home/administrator/miniconda3/envs/isce2 -maxdepth 6 \
-  \( -iname 'stripmapStack' -o -iname 'topsStack' -o -iname 'stack' \) 2>/dev/null || true

experiments/isce2_sbas_timeseries/scripts/create_mintpy_all_ifgram_mask.py

@@ -1,83 +0,0 @@
-#!/usr/bin/env python3
-"""Create a strict MintPy mask containing only pixels valid in all interferograms."""
-
-from __future__ import annotations
-
-import argparse
-from pathlib import Path
-
-import h5py
-import numpy as np
-
-
-def build_mask(ifgram_stack: Path, output_path: Path, block_rows: int) -> None:
-    with h5py.File(ifgram_stack, "r") as src:
-        unwrap = src["unwrapPhase"]
-        conn = src.get("connectComponent")
-
-        num_ifg, length, width = unwrap.shape
-        mask = np.ones((length, width), dtype=np.bool_)
-
-        print(f"Input stack: {ifgram_stack}")
-        print(f"Interferograms: {num_ifg}")
-        print(f"Shape: {length} x {width}")
-        print(f"Block rows: {block_rows}")
-
-        for row0 in range(0, length, block_rows):
-            row1 = min(row0 + block_rows, length)
-            block = unwrap[:, row0:row1, :]
-            block_mask = np.all(np.isfinite(block) & (block != 0.0), axis=0)
-
-            if conn is not None:
-                conn_block = conn[:, row0:row1, :]
-                block_mask &= np.all(conn_block != 0, axis=0)
-
-            mask[row0:row1, :] = block_mask
-            print(f"Processed rows {row0}:{row1}")
-
-        attrs = dict(src.attrs)
-
-    output_path.parent.mkdir(parents=True, exist_ok=True)
-
-    with h5py.File(output_path, "w") as dst:
-        dst.create_dataset("mask", data=mask, dtype=np.bool_)
-        for key, value in attrs.items():
-            dst.attrs[key] = value
-        dst.attrs["FILE_TYPE"] = "mask"
-        dst.attrs["DATASET_NAME"] = "mask"
-        dst.attrs["SOURCE_FILE"] = str(ifgram_stack)
-        dst.attrs["MASK_RULE"] = "all_ifgrams_finite_nonzero_and_conncomp_nonzero"
-
-    valid_pixels = int(mask.sum())
-    total_pixels = int(mask.size)
-    print(f"Output mask: {output_path}")
-    print(f"Valid pixels: {valid_pixels}/{total_pixels} ({valid_pixels / total_pixels * 100:.2f}%)")
-
-
-def parse_args() -> argparse.Namespace:
-    parser = argparse.ArgumentParser(
-        description="Create a strict mask of pixels valid in all MintPy interferograms."
-    )
-    parser.add_argument("--ifgram-stack", required=True, help="Path to MintPy inputs/ifgramStack.h5")
-    parser.add_argument("--output", required=True, help="Output HDF5 path, e.g. maskAllValid.h5")
-    parser.add_argument(
-        "--block-rows",
-        type=int,
-        default=256,
-        help="Number of image rows processed per block.",
-    )
-    return parser.parse_args()
-
-
-def main() -> int:
-    args = parse_args()
-    build_mask(
-        ifgram_stack=Path(args.ifgram_stack),
-        output_path=Path(args.output),
-        block_rows=args.block_rows,
-    )
-    return 0
-
-
-if __name__ == "__main__":
-    raise SystemExit(main())

experiments/isce2_sbas_timeseries/scripts/create_synthetic_watermask.py

@@ -1,145 +0,0 @@
-#!/usr/bin/env python3
-from __future__ import annotations
-
-import argparse
-import json
-from datetime import datetime
-from pathlib import Path
-import xml.etree.ElementTree as ET
-
-import numpy as np
-
-
-def parse_args() -> argparse.Namespace:
-    parser = argparse.ArgumentParser(
-        description=(
-            "Create a synthetic stripmapStack water mask in radar coordinates. "
-            "The default fill value 1 means all-land, which preserves downstream pixels."
-        )
-    )
-    parser.add_argument(
-        "--like-image",
-        required=True,
-        help="Existing ISCE image base path or .xml path used only for shape/metadata, for example shadowMask.rdr",
-    )
-    parser.add_argument(
-        "--output",
-        required=True,
-        help="Output water-mask base path, for example .../geom_reference/waterMask.rdr",
-    )
-    parser.add_argument(
-        "--fill-value",
-        type=int,
-        default=1,
-        choices=(0, 1),
-        help="Pixel value to write. 1 keeps all pixels, 0 masks all pixels.",
-    )
-    parser.add_argument(
-        "--force",
-        action="store_true",
-        help="Overwrite an existing output mask.",
-    )
-    parser.add_argument(
-        "--report",
-        default=None,
-        help="Optional JSON report path.",
-    )
-    return parser.parse_args()
-
-
-def resolve_like_paths(value: str) -> tuple[Path, Path]:
-    candidate = Path(value)
-    if candidate.suffix == ".xml":
-        xml_path = candidate
-        image_path = Path(str(candidate)[:-4])
-    else:
-        image_path = candidate
-        xml_path = Path(str(candidate) + ".xml")
-
-    if not xml_path.exists():
-        raise FileNotFoundError(f"Template image XML not found: {xml_path}")
-    return image_path, xml_path
-
-
-def maybe_unlink(path: Path) -> None:
-    if path.exists():
-        path.unlink()
-
-
-def require_xml_value(root: ET.Element, property_name: str) -> str:
-    value_node = root.find(f"./property[@name='{property_name}']/value")
-    if value_node is None or value_node.text is None:
-        raise ValueError(f"Missing XML property '{property_name}'")
-    return value_node.text.strip()
-
-
-def write_template_metadata(template_image: Path, template_xml: Path, output: Path) -> tuple[int, int]:
-    root = ET.parse(template_xml).getroot()
-    width = int(require_xml_value(root, "width"))
-    length = int(require_xml_value(root, "length"))
-
-    file_name_node = root.find("./property[@name='file_name']/value")
-    if file_name_node is None:
-        raise ValueError(f"Missing XML file_name entry: {template_xml}")
-    file_name_node.text = str(output)
-
-    xml_output = Path(str(output) + ".xml")
-    ET.indent(root, space="    ")
-    ET.ElementTree(root).write(xml_output, encoding="utf-8")
-
-    hdr_template = template_image.with_suffix(".hdr")
-    hdr_output = output.with_suffix(".hdr")
-    if hdr_template.exists():
-        hdr_text = hdr_template.read_text(encoding="utf-8", errors="ignore")
-        hdr_output.write_text(hdr_text.replace(str(template_image), str(output)), encoding="utf-8")
-
-    vrt_template = Path(str(template_image) + ".vrt")
-    vrt_output = Path(str(output) + ".vrt")
-    if vrt_template.exists():
-        vrt_text = vrt_template.read_text(encoding="utf-8", errors="ignore")
-        vrt_text = vrt_text.replace(template_image.name, output.name)
-        vrt_output.write_text(vrt_text, encoding="utf-8")
-
-    return width, length
-
-
-def main() -> int:
-    args = parse_args()
-    template_image, template_xml = resolve_like_paths(args.like_image)
-    output = Path(args.output)
-
-    if output.exists() and not args.force:
-        raise FileExistsError(f"Output already exists, use --force to overwrite: {output}")
-
-    output.parent.mkdir(parents=True, exist_ok=True)
-    width, length = write_template_metadata(template_image=template_image, template_xml=template_xml, output=output)
-
-    mask = np.full((length, width), args.fill_value, dtype=np.uint8)
-    mask.tofile(output)
-
-    maybe_unlink(output.with_suffix(".rdr.aux.xml"))
-
-    report = {
-        "generated_at_utc": datetime.utcnow().replace(microsecond=0).isoformat() + "Z",
-        "template_xml": str(template_xml),
-        "output": str(output),
-        "width": width,
-        "length": length,
-        "fill_value": args.fill_value,
-        "data_type": "BYTE",
-        "note": "Synthetic all-land water mask for local stripmapStack experiments without Earthdata SWBD access.",
-    }
-
-    report_path = Path(args.report) if args.report else output.parent / "synthetic_watermask_report.json"
-    report_path.write_text(json.dumps(report, indent=2, ensure_ascii=False), encoding="utf-8")
-
-    print(f"Template: {template_xml}")
-    print(f"Output:   {output}")
-    print(f"Shape:    {length} x {width}")
-    print(f"Value:    {args.fill_value}")
-    print(f"Report:   {report_path}")
-    return 0
-
-
-if __name__ == "__main__":
-    raise SystemExit(main())

experiments/isce2_sbas_timeseries/scripts/export_conda_env_snapshot_ubuntu2404.sh

@@ -1,76 +0,0 @@
-#!/usr/bin/env bash
-set -euo pipefail
-
-if [[ $# -ne 2 ]]; then
-  echo "Usage: $0 <env-name> <output-dir-wsl>" >&2
-  exit 1
-fi
-
-ENV_NAME="$1"
-OUTPUT_DIR="$2"
-CONDA_BIN="${CONDA_BIN:-/home/administrator/miniconda3/bin/conda}"
-
-if [[ ! -x "$CONDA_BIN" ]]; then
-  echo "Missing conda binary: $CONDA_BIN" >&2
-  exit 1
-fi
-
-mkdir -p "$OUTPUT_DIR"
-
-SAFE_NAME="${ENV_NAME//[^A-Za-z0-9._-]/_}"
-YAML_PATH="$OUTPUT_DIR/${SAFE_NAME}.no_builds.yml"
-EXPLICIT_PATH="$OUTPUT_DIR/${SAFE_NAME}.explicit.txt"
-LIST_PATH="$OUTPUT_DIR/${SAFE_NAME}.conda_list.txt"
-RUNTIME_PATH="$OUTPUT_DIR/${SAFE_NAME}.runtime_versions.txt"
-
-echo "Exporting conda environment snapshot"
-echo "Env:        $ENV_NAME"
-echo "Output dir: $OUTPUT_DIR"
-
-"$CONDA_BIN" env export -n "$ENV_NAME" --no-builds > "$YAML_PATH"
-"$CONDA_BIN" list -n "$ENV_NAME" --explicit > "$EXPLICIT_PATH"
-"$CONDA_BIN" list -n "$ENV_NAME" > "$LIST_PATH"
-
-"$CONDA_BIN" run -n "$ENV_NAME" python -c "
-import importlib.util
-import logging
-import platform
-import sys
-
-logging.getLogger().setLevel(logging.WARNING)
-
-def version_of(name):
-    try:
-        mod = __import__(name)
-        return getattr(mod, '__version__', '<missing>')
-    except Exception as exc:
-        return f'<import failed: {exc}>'
-
-for line in [
-    f'python_executable={sys.executable}',
-    f'python_version={platform.python_version()}',
-    f'isce_present={importlib.util.find_spec(\"isce\") is not None}',
-    f'mintpy_present={importlib.util.find_spec(\"mintpy\") is not None}',
-    f'h5py_present={importlib.util.find_spec(\"h5py\") is not None}',
-]:
-    print(line)
-
-if importlib.util.find_spec('isce') is not None:
-    import isce
-    print(f'isce_file={isce.__file__}')
-    print(f'isce_version={getattr(isce, \"__version__\", \"<missing>\")}')
-
-if importlib.util.find_spec('mintpy') is not None:
-    import mintpy
-    print(f'mintpy_file={mintpy.__file__}')
-    print(f'mintpy_version={getattr(mintpy, \"__version__\", \"<missing>\")}')
-
-if importlib.util.find_spec('h5py') is not None:
-    import h5py
-    print(f'h5py_version={h5py.__version__}')
-" > "$RUNTIME_PATH"
-
-echo "Wrote: $YAML_PATH"
-echo "Wrote: $EXPLICIT_PATH"
-echo "Wrote: $LIST_PATH"
-echo "Wrote: $RUNTIME_PATH"

experiments/isce2_sbas_timeseries/scripts/export_mintpy_publish_products_ubuntu2404.sh

@@ -1,63 +0,0 @@
-#!/usr/bin/env bash
-set -euo pipefail
-
-if [[ $# -lt 2 || $# -gt 3 ]]; then
-  echo "Usage: $0 <mintpy-work-dir-wsl> <publish-dir-wsl> [group-key]" >&2
-  exit 1
-fi
-
-MINTPY_WORK_DIR="$1"
-PUBLISH_DIR="$2"
-GROUP_KEY="${3:-}"
-
-SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
-MINTPY_RUNNER="${MINTPY_RUNNER:-$SCRIPT_DIR/run_mintpy_with_isce_ubuntu2404.sh}"
-PUBLISH_BUILDER="$SCRIPT_DIR/build_mintpy_publish_bundle.py"
-
-GEO_LAT_STEP="${GEO_LAT_STEP:--0.000185185}"
-GEO_LON_STEP="${GEO_LON_STEP:-0.000185185}"
-GEO_INTERP_METHOD="${GEO_INTERP_METHOD:-nearest}"
-
-ASSETS_DIR="$PUBLISH_DIR/assets"
-PREVIEW_DIR="$PUBLISH_DIR/preview"
-METADATA_DIR="$PUBLISH_DIR/metadata"
-
-mkdir -p "$ASSETS_DIR" "$PREVIEW_DIR" "$METADATA_DIR"
-
-LOOKUP_FILE="$MINTPY_WORK_DIR/inputs/geometryRadar.h5"
-
-echo "MintPy publish export"
-echo "Work dir:     $MINTPY_WORK_DIR"
-echo "Publish dir:  $PUBLISH_DIR"
-echo "Lookup file:  $LOOKUP_FILE"
-echo "Runner:       $MINTPY_RUNNER"
-echo "Geo step:     $GEO_LAT_STEP, $GEO_LON_STEP"
-echo "Interp:       $GEO_INTERP_METHOD"
-
-for src in velocity.h5 temporalCoherence.h5 maskTempCoh.h5 timeseries.h5; do
-  bash "$MINTPY_RUNNER" geocode.py \
-    "$MINTPY_WORK_DIR/$src" \
-    -l "$LOOKUP_FILE" \
-    --lalo "$GEO_LAT_STEP" "$GEO_LON_STEP" \
-    -i "$GEO_INTERP_METHOD" \
-    --outdir "$ASSETS_DIR" \
-    --update
-done
-
-bash "$MINTPY_RUNNER" save_gdal.py "$ASSETS_DIR/geo_velocity.h5" -d velocity -o "$ASSETS_DIR/velocity.tif"
-bash "$MINTPY_RUNNER" save_gdal.py "$ASSETS_DIR/geo_temporalCoherence.h5" -d temporalCoherence -o "$ASSETS_DIR/temporalCoherence.tif"
-bash "$MINTPY_RUNNER" save_gdal.py "$ASSETS_DIR/geo_maskTempCoh.h5" -d mask -o "$ASSETS_DIR/maskTempCoh.tif"
-
-cp "$MINTPY_WORK_DIR/smallbaselineApp.cfg" "$METADATA_DIR/smallbaselineApp.cfg"
-cp "$MINTPY_WORK_DIR/numTriNonzeroIntAmbiguity.png" "$PREVIEW_DIR/numTriNonzeroIntAmbiguity.png"
-
-if [[ -n "$GROUP_KEY" ]]; then
-  bash "$MINTPY_RUNNER" python "$PUBLISH_BUILDER" \
-    --mintpy-work-dir "$MINTPY_WORK_DIR" \
-    --publish-dir "$PUBLISH_DIR" \
-    --group-key "$GROUP_KEY"
-else
-  bash "$MINTPY_RUNNER" python "$PUBLISH_BUILDER" \
-    --mintpy-work-dir "$MINTPY_WORK_DIR" \
-    --publish-dir "$PUBLISH_DIR"
-fi

experiments/isce2_sbas_timeseries/scripts/export_mintpy_publish_products_unified_env_ubuntu2404.sh

@@ -1,9 +0,0 @@
-#!/usr/bin/env bash
-set -euo pipefail
-
-SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
-GENERIC_EXPORTER="$SCRIPT_DIR/export_mintpy_publish_products_ubuntu2404.sh"
-
-export MINTPY_RUNNER="${MINTPY_RUNNER:-$SCRIPT_DIR/run_mintpy_unified_env_ubuntu2404.sh}"
-
-bash "$GENERIC_EXPORTER" "$@"

experiments/isce2_sbas_timeseries/scripts/export_phase4_env_snapshots_ubuntu2404.sh

@@ -1,14 +0,0 @@
-#!/usr/bin/env bash
-set -euo pipefail
-
-if [[ $# -ne 1 ]]; then
-  echo "Usage: $0 <output-dir-wsl>" >&2
-  exit 1
-fi
-
-OUTPUT_DIR="$1"
-SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
-EXPORTER="$SCRIPT_DIR/export_conda_env_snapshot_ubuntu2404.sh"
-
-bash "$EXPORTER" isce2 "$OUTPUT_DIR"
-bash "$EXPORTER" isce2_mintpy_v1 "$OUTPUT_DIR"

experiments/isce2_sbas_timeseries/scripts/install_isce2_stack_runtime_ubuntu2404.sh

@@ -1,26 +0,0 @@
-#!/usr/bin/env bash
-set -euo pipefail
-
-CONDA_BIN="${CONDA_BIN:-/home/administrator/miniconda3/bin/conda}"
-CONDA_ENV="${CONDA_ENV:-isce2}"
-PIP_INDEX_URL="${PIP_INDEX_URL:-https://pypi.tuna.tsinghua.edu.cn/simple}"
-PACKAGES=(
-  matplotlib
-)
-
-if [[ ! -x "$CONDA_BIN" ]]; then
-  echo "Missing conda binary: $CONDA_BIN" >&2
-  exit 1
-fi
-
-echo "ISCE2 stack runtime bootstrap"
-echo "Conda: $CONDA_BIN"
-echo "Env:   $CONDA_ENV"
-echo "Index: $PIP_INDEX_URL"
-
-for pkg in "${PACKAGES[@]}"; do
-  echo "Installing $pkg into $CONDA_ENV"
-  "$CONDA_BIN" run -n "$CONDA_ENV" python -m pip install -i "$PIP_INDEX_URL" "$pkg"
-done
-
-echo "Runtime bootstrap complete"

experiments/isce2_sbas_timeseries/scripts/install_mintpy_into_cloned_isce2_env_ubuntu2404.sh

@@ -1,128 +0,0 @@
-#!/usr/bin/env bash
-set -euo pipefail
-
-CONDA_BIN="${CONDA_BIN:-/home/administrator/miniconda3/bin/conda}"
-SOURCE_ENV="${SOURCE_ENV:-isce2}"
-TARGET_ENV="${TARGET_ENV:-isce2_mintpy}"
-PYTHON_VERSION="${PYTHON_VERSION:-3.11}"
-BOOTSTRAP_MODE="${BOOTSTRAP_MODE:-clone}"
-USE_TUNA_MIRROR="${USE_TUNA_MIRROR:-1}"
-CHANNEL_CONDA_FORGE="${CHANNEL_CONDA_FORGE:-https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge}"
-CHANNEL_MAIN="${CHANNEL_MAIN:-https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main}"
-CHANNEL_R="${CHANNEL_R:-https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/r}"
-MINTPY_SPEC="${MINTPY_SPEC:-mintpy}"
-CLONE_OFFLINE="${CLONE_OFFLINE:-1}"
-
-if [[ ! -x "$CONDA_BIN" ]]; then
-  echo "Missing conda binary: $CONDA_BIN" >&2
-  exit 1
-fi
-
-channel_args=()
-if [[ "$USE_TUNA_MIRROR" == "1" ]]; then
-  channel_args=(
-    --override-channels
-    -c "$CHANNEL_CONDA_FORGE"
-    -c "$CHANNEL_MAIN"
-    -c "$CHANNEL_R"
-  )
-fi
-
-env_exists() {
-  "$CONDA_BIN" env list | awk '{print $1}' | grep -Fxq "$1"
-}
-
-echo "Unified ISCE2 + MintPy runtime bootstrap"
-echo "Conda:        $CONDA_BIN"
-echo "Source env:   $SOURCE_ENV"
-echo "Target env:   $TARGET_ENV"
-echo "Python:       $PYTHON_VERSION"
-echo "Mode:         $BOOTSTRAP_MODE"
-echo "MintPy spec:  $MINTPY_SPEC"
-echo "Use mirror:   $USE_TUNA_MIRROR"
-echo "Clone offline:$CLONE_OFFLINE"
-
-if ! env_exists "$SOURCE_ENV"; then
-  echo "Missing source environment: $SOURCE_ENV" >&2
-  exit 1
-fi
-
-if [[ "$BOOTSTRAP_MODE" != "clone" && "$BOOTSTRAP_MODE" != "recreate" ]]; then
-  echo "Unsupported BOOTSTRAP_MODE: $BOOTSTRAP_MODE" >&2
-  exit 1
-fi
-
-if env_exists "$TARGET_ENV"; then
-  echo "Environment $TARGET_ENV already exists. Reusing it."
-else
-  if [[ "$BOOTSTRAP_MODE" == "clone" ]]; then
-    echo "Cloning $SOURCE_ENV into $TARGET_ENV"
-    clone_args=("${channel_args[@]}" -y -n "$TARGET_ENV" --clone "$SOURCE_ENV")
-    if [[ "$CLONE_OFFLINE" == "1" ]]; then
-      clone_args+=(--offline)
-    fi
-    "$CONDA_BIN" create "${clone_args[@]}"
-  else
-    tmp_export="$(mktemp)"
-    tmp_conda_specs="$(mktemp)"
-    tmp_pip_specs="$(mktemp)"
-    trap 'rm -f "$tmp_export" "$tmp_conda_specs" "$tmp_pip_specs"' EXIT
-
-    echo "Exporting $SOURCE_ENV into a recreate spec"
-    "$CONDA_BIN" env export -n "$SOURCE_ENV" --no-builds > "$tmp_export"
-
-    awk \
-      '
-      /^dependencies:/ {
-        in_dependencies = 1
-        next
-      }
-      /^prefix:/ {
-        exit
-      }
-      in_dependencies == 1 && /^  - pip:$/ {
-        exit
-      }
-      in_dependencies == 1 && /^  - / {
-        print substr($0, 5)
-      }
-    ' "$tmp_export" > "$tmp_conda_specs"
-
-    awk \
-      '
-      /^  - pip:$/ {
-        in_pip = 1
-        next
-      }
-      /^prefix:/ {
-        exit
-      }
-      in_pip == 1 && /^    - / {
-        print substr($0, 7)
-      }
-    ' "$tmp_export" > "$tmp_pip_specs"
-
-    mapfile -t conda_specs < "$tmp_conda_specs"
-    if [[ ${#conda_specs[@]} -eq 0 ]]; then
-      echo "Failed to extract conda dependency specs from $SOURCE_ENV export" >&2
-      exit 1
-    fi
-
-    echo "Recreating $TARGET_ENV from exported dependency list"
-    "$CONDA_BIN" create -y -n "$TARGET_ENV" "${channel_args[@]}" "${conda_specs[@]}"
-
-    if [[ -s "$tmp_pip_specs" ]]; then
-      mapfile -t pip_specs < "$tmp_pip_specs"
-      echo "Reinstalling exported pip packages into $TARGET_ENV"
-      "$CONDA_BIN" run -n "$TARGET_ENV" python -m pip install "${pip_specs[@]}"
-    fi
-  fi
-fi
-
-echo "Installing MintPy into $TARGET_ENV"
-"$CONDA_BIN" install -y -n "$TARGET_ENV" "${channel_args[@]}" "$MINTPY_SPEC"
-
-echo "Verifying unified runtime imports"
-"$CONDA_BIN" run -n "$TARGET_ENV" python -c "import sys; import isce; import mintpy; import h5py; print(sys.executable); print(isce.__file__); print(mintpy.__file__); print('h5py=' + h5py.__version__)"
-
-echo "Unified runtime bootstrap complete"

experiments/isce2_sbas_timeseries/scripts/install_mintpy_runtime_ubuntu2404.sh

@@ -1,47 +0,0 @@
-#!/usr/bin/env bash
-set -euo pipefail
-
-CONDA_BIN="${CONDA_BIN:-/home/administrator/miniconda3/bin/conda}"
-TARGET_ENV="${TARGET_ENV:-mintpy}"
-PYTHON_VERSION="${PYTHON_VERSION:-3.11}"
-USE_TUNA_MIRROR="${USE_TUNA_MIRROR:-1}"
-CHANNEL_CONDA_FORGE="${CHANNEL_CONDA_FORGE:-https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge}"
-CHANNEL_MAIN="${CHANNEL_MAIN:-https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main}"
-CHANNEL_R="${CHANNEL_R:-https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/r}"
-
-if [[ ! -x "$CONDA_BIN" ]]; then
-  echo "Missing conda binary: $CONDA_BIN" >&2
-  exit 1
-fi
-
-channel_args=()
-if [[ "$USE_TUNA_MIRROR" == "1" ]]; then
-  channel_args=(
-    --override-channels
-    -c "$CHANNEL_CONDA_FORGE"
-    -c "$CHANNEL_MAIN"
-    -c "$CHANNEL_R"
-  )
-fi
-
-env_exists() {
-  "$CONDA_BIN" env list | awk '{print $1}' | grep -Fxq "$TARGET_ENV"
-}
-
-echo "MintPy runtime bootstrap"
-echo "Conda:       $CONDA_BIN"
-echo "Target env:  $TARGET_ENV"
-echo "Python:      $PYTHON_VERSION"
-echo "Use mirror:  $USE_TUNA_MIRROR"
-
-if env_exists; then
-  echo "Environment $TARGET_ENV already exists. Installing or updating MintPy."
-  "$CONDA_BIN" install -y -n "$TARGET_ENV" "${channel_args[@]}" mintpy
-else
-  echo "Creating environment $TARGET_ENV with MintPy."
-  "$CONDA_BIN" create -y -n "$TARGET_ENV" "${channel_args[@]}" "python=$PYTHON_VERSION" mintpy
-fi
-
-echo "Verifying MintPy import"
-"$CONDA_BIN" run -n "$TARGET_ENV" python -c "import mintpy; print(mintpy.__file__)"
-echo "MintPy runtime bootstrap complete"

experiments/isce2_sbas_timeseries/scripts/materialize_lt1_stack_scenes.py

@@ -1,201 +0,0 @@
-#!/usr/bin/env python3
-from __future__ import annotations
-
-import argparse
-import json
-import os
-import shelve
-import shutil
-from dataclasses import dataclass
-from datetime import datetime
-from pathlib import Path
-from typing import Any, Dict, List, Optional
-
-
-def choose_path(scene: Dict[str, Any], primary_key: str, fallback_key: str) -> str:
-    primary = scene.get(primary_key)
-    fallback = scene.get(fallback_key)
-    for candidate in (primary, fallback):
-        if candidate and Path(candidate).exists():
-            return str(Path(candidate))
-    raise FileNotFoundError(
-        f"Neither {primary_key} nor {fallback_key} exists for scene {scene.get('date') or scene.get('imaging_date')}"
-    )
-
-
-def load_manifest(path: Path) -> Dict[str, Any]:
-    return json.loads(path.read_text(encoding="utf-8"))
-
-
-def remove_existing_shelve(stem: Path) -> None:
-    for suffix in ("", ".db", ".dat", ".dir", ".bak"):
-        candidate = Path(str(stem) + suffix)
-        if candidate.exists():
-            if candidate.is_dir():
-                shutil.rmtree(candidate)
-            else:
-                candidate.unlink()
-
-
-def shelve_stem_exists(stem: Path) -> bool:
-    for suffix in ("", ".db", ".dat", ".dir", ".bak"):
-        if Path(str(stem) + suffix).exists():
-            return True
-    return False
-
-
-@dataclass
-class SceneResult:
-    date: str
-    output_dir: str
-    slc_path: str
-    data_shelve: str
-    status: str
-    bytes_written: Optional[int]
-    started_at_utc: str
-    ended_at_utc: str
-
-
-def materialize_one_scene(
-    scene: Dict[str, Any],
-    force: bool,
-) -> SceneResult:
-    import isce
-    from isceobj.Sensor import createSensor
-
-    date = str(scene["date"])
-    output_dir = Path(scene["target_dir_wsl"])
-    output_dir.mkdir(parents=True, exist_ok=True)
-
-    slc_path = Path(scene["expected_slc_wsl"])
-    slc_xml_path = Path(scene["expected_slc_xml_wsl"])
-    data_shelve = Path(scene["expected_data_shelve_wsl"])
-
-    tiff_path = choose_path(scene, "source_tiff_wsl", "source_tiff_windows")
-    orbit_xml = choose_path(scene, "orbit_xml_wsl", "orbit_xml_windows")
-
-    if force:
-        for path in (slc_path, slc_xml_path, Path(str(slc_path) + ".vrt")):
-            if path.exists():
-                path.unlink()
-        remove_existing_shelve(data_shelve)
-
-    if slc_path.exists() and slc_xml_path.exists() and shelve_stem_exists(data_shelve):
-        now = datetime.utcnow().replace(microsecond=0).isoformat() + "Z"
-        return SceneResult(
-            date=date,
-            output_dir=str(output_dir),
-            slc_path=str(slc_path),
-            data_shelve=str(data_shelve),
-            status="skipped_existing",
-            bytes_written=slc_path.stat().st_size,
-            started_at_utc=now,
-            ended_at_utc=now,
-        )
-
-    started_at = datetime.utcnow().replace(microsecond=0).isoformat() + "Z"
-
-    sensor = createSensor("LUTAN1")
-    sensor.configure()
-    sensor.tiff = tiff_path
-    sensor.orbitFile = orbit_xml
-    sensor.output = str(slc_path)
-    sensor.extractImage()
-    sensor.extractDoppler()
-    sensor.frame.getImage().renderHdr()
-
-    remove_existing_shelve(data_shelve)
-    with shelve.open(str(data_shelve)) as db:
-        db["frame"] = sensor.frame
-
-    ended_at = datetime.utcnow().replace(microsecond=0).isoformat() + "Z"
-    report = {
-        "date": date,
-        "source_tiff": tiff_path,
-        "orbit_xml": orbit_xml,
-        "output_slc": str(slc_path),
-        "output_slc_xml": str(slc_xml_path),
-        "data_shelve": str(data_shelve),
-        "frame_lines": sensor.frame.getNumberOfLines(),
-        "frame_samples": sensor.frame.getNumberOfSamples(),
-        "started_at_utc": started_at,
-        "ended_at_utc": ended_at,
-    }
-    (output_dir / "materialization_report.json").write_text(
-        json.dumps(report, indent=2, ensure_ascii=False),
-        encoding="utf-8",
-    )
-
-    return SceneResult(
-        date=date,
-        output_dir=str(output_dir),
-        slc_path=str(slc_path),
-        data_shelve=str(data_shelve),
-        status="materialized",
-        bytes_written=slc_path.stat().st_size if slc_path.exists() else None,
-        started_at_utc=started_at,
-        ended_at_utc=ended_at,
-    )
-
-
-def parse_args() -> argparse.Namespace:
-    parser = argparse.ArgumentParser(
-        description="Materialize LT-1 stack acquisitions into stripmapStack-ready SLC/date directories."
-    )
-    parser.add_argument(
-        "--stack-manifest",
-        required=True,
-        help="Path to stack_input_manifest.json generated by build_lt1_stack_prep.py",
-    )
-    parser.add_argument(
-        "--dates",
-        nargs="+",
-        default=None,
-        help="Optional subset of acquisition dates to materialize, for example 20250510 20250705",
-    )
-    parser.add_argument(
-        "--force",
-        action="store_true",
-        help="Overwrite existing .slc/.xml/data outputs for the selected dates.",
-    )
-    return parser.parse_args()
-
-
-def main() -> int:
-    args = parse_args()
-    manifest_path = Path(args.stack_manifest)
-    if not manifest_path.exists():
-        raise FileNotFoundError(f"Stack manifest not found: {manifest_path}")
-
-    manifest = load_manifest(manifest_path)
-    scenes = list(manifest.get("scenes", []))
-    if not scenes:
-        raise ValueError(f"No scenes found in stack manifest: {manifest_path}")
-
-    selected_dates = set(args.dates or [])
-    if selected_dates:
-        scenes = [scene for scene in scenes if str(scene["date"]) in selected_dates]
-        if not scenes:
-            raise ValueError(f"No matching dates found in manifest for selection: {sorted(selected_dates)}")
-
-    results: List[SceneResult] = []
-    for scene in scenes:
-        print(f"Materializing {scene['date']} -> {scene['target_dir_wsl']}")
-        result = materialize_one_scene(scene, force=args.force)
-        results.append(result)
-        print(f"  status={result.status} slc={result.slc_path}")
-
-    report = {
-        "generated_at_utc": datetime.utcnow().replace(microsecond=0).isoformat() + "Z",
-        "stack_manifest": str(manifest_path),
-        "results": [result.__dict__ for result in results],
-    }
-
-    report_path = manifest_path.parent / "materialization_summary.json"
-    report_path.write_text(json.dumps(report, indent=2, ensure_ascii=False), encoding="utf-8")
-    print(f"Summary: {report_path}")
-    return 0
-
-
-if __name__ == "__main__":
-    raise SystemExit(main())

experiments/isce2_sbas_timeseries/scripts/phase0_todo.md

@@ -1,59 +0,0 @@
-# Phase 0 Practical TODO
-
-## Immediate
-
-- [x] Run `scripts/check_env_ubuntu2404.sh` inside `Ubuntu-24.04`.
-- [x] Use `scripts/scan_lt1_stack_candidates.py` to keep one baseline sample stack manifest current.
-- [x] Treat `E123.3_N46.1` as the first tile-level smoke-test sample unless a better sample appears.
-- [x] Confirm ISCE2 stack-processing scripts are present.
-- [x] Confirm the official helper scripts do not advertise LT-1/LUTAN1 stack prep.
-- [x] Record required orbit, DEM, and metadata adaptations.
-- [x] Run `scripts/build_lt1_stack_prep.py` to keep the dry-run stack workspace current.
-
-## Before first end-to-end run
-
-- [x] Implement an LT-1 scene materializer that creates `YYYYMMDD.slc`, `YYYYMMDD.slc.xml`, and `data`.
-- [x] Materialize the remaining acquisitions for `E123.3_N46.1` under `scratch/.../SLC/`.
-- [x] Smoke-test the materializer on the reference date `20250510`.
-- [x] Run the generated `run_stripmap_stack_dryrun.sh` preflight and then `stackStripMap.py --nofocus`.
-- [x] Inspect the produced `baseline/`, `configs/`, and `run_files/` outputs.
-- [x] Prepare a stack-local DEM to avoid global-DEM bbox behavior during `createWaterMask`.
-- [x] Add a reproducible synthetic `waterMask` fallback for `run_01_reference` when Earthdata credentials are unavailable.
-  Working rule: DEM is already local and sufficient; do not download `SWBD` during this experiment stage.
-- [x] Extract shared LT-1 input preparation helper for DEM/orbit resolution.
-  Compatibility rule: original D-InSAR entry logic remains in place; only the duplicated input-prep internals were consolidated.
-- [x] Decide MintPy installation strategy after stack generation is stable.
-  Decision: default to a dedicated WSL conda env named `mintpy` so the working `isce2` processing env stays unchanged on the development machine.
-- [x] Freeze the first smoke-test command chain.
-  Frozen chain: `run_01_reference -> run_02_focus_split -> run_03_geo2rdr_coarseResamp -> run_04_refineSecondaryTiming -> run_05_invertMisreg -> run_06_fineResamp -> run_07_grid_baseline`
-- [x] Execute `run_01_reference` through the WSL wrapper and verify the fallback-recovered geometry outputs.
-- [x] Execute `run_02` to `run_07` and record LT-1-specific failures if they appear.
-  Result: all stages exited `0` in `Ubuntu-24.04`. `run_04_refineSecondaryTiming` logs still contain `Bad match at level 1` and `correlation error`, but pair-level `misreg`, date-level `misreg`, merged SLC, and merged baseline products were all generated successfully.
-
-## Next Focus
-
-- [x] Run `scripts/install_mintpy_runtime_ubuntu2404.sh` in `Ubuntu-24.04` and verify the new env.
-  Result: dedicated WSL env `mintpy` was created successfully and `smallbaselineApp.py` / `prep_isce.py` are available.
-- [x] Validate MintPy ingestion against the current `stack_work/merged/` outputs.
-  Result: `build_lt1_stack_prep.py --workflow interferogram` plus `run_08_igram` produced `Igrams/*/filt_*_snaphu.unw`, and `prep_isce.py` completed successfully after bridging the working `isce2` Python package into the `mintpy` env.
-- [x] Draft the first `smallbaselineApp.cfg` for the LT-1 sample stack.
-  Result: `configs/sample_smallbaseline_lt1_e123p3_n46p1.cfg` now records the first runnable LT-1 stripmapStack -> MintPy SBAS contract.
-- [x] Execute the first MintPy workflow steps after `prep_isce.py`.
-  Result: the repo-local smoke-test chain now reaches radar-coordinate `timeseries.h5` and `velocity.h5` in `stack_work/mintpy_sbas_v5/`.
-  Current helper chain:
-  - `scripts/run_mintpy_with_isce_ubuntu2404.sh`
-  - `scripts/create_mintpy_all_ifgram_mask.py`
-  - `scripts/run_smallbaselineApp_patched.py`
-  - `scripts/run_mintpy_sbas_smoketest_ubuntu2404.sh`
-- [x] Draft the first production-side SBAS artifact manifest and publish contract.
-  Result:
-  - `configs/sample_psinsar_manifest_lt1_e123p3_n46p1.json`
-  - `docs/ISCE2_SBAS_TIMESERIES_DESIGN.md`
-
-## New Follow-up
-
-- [ ] Decide whether production should keep the repo-local patched MintPy launcher or pin an upstream-fixed MintPy version.
-- [x] Add the geocode/export stage needed for publishable SBAS rasters and previews.
-  Result: experiment-layer publish export now succeeds into `publish/mintpy_sbas_v5/` with geocoded HDF5, GeoTIFF, preview PNG, and `manifest.json`.
-- [ ] Wire the validated SBAS runtime chain into backend workflow submission and artifact publishing.
-- [ ] Run a separate unified-environment experiment by cloning the current WSL `isce2` env and installing MintPy directly inside it.

experiments/isce2_sbas_timeseries/scripts/prepare_lt1_stack_dem.py

@@ -1,152 +0,0 @@
-#!/usr/bin/env python3
-from __future__ import annotations
-
-import argparse
-import json
-from pathlib import Path
-from typing import Any, Dict, List
-
-
-def load_manifest(path: Path) -> Dict[str, Any]:
-    return json.loads(path.read_text(encoding="utf-8"))
-
-
-def resolve_dem_source(arg_value: str | None, manifest: Dict[str, Any]) -> Path:
-    candidates: List[str] = []
-    if arg_value:
-        candidates.append(arg_value)
-    resolved = manifest.get("resolved_dependencies", {})
-    for key in ("dem_path_wsl", "dem_path_windows"):
-        value = resolved.get(key)
-        if value:
-            candidates.append(value)
-
-    for candidate in candidates:
-        path = Path(candidate)
-        if path.exists() and Path(str(path) + ".xml").exists():
-            return path
-    raise FileNotFoundError("Unable to resolve source DEM from arguments or stack manifest")
-
-
-def compute_bbox(manifest: Dict[str, Any], margin_deg: float) -> List[float]:
-    lons: List[float] = []
-    lats: List[float] = []
-    for scene in manifest["scenes"]:
-        lon = scene.get("scene_center_lon")
-        lat = scene.get("scene_center_lat")
-        if lon is None or lat is None:
-            source_scene_json = scene.get("source_scene_json_wsl") or scene.get("source_scene_json_windows")
-            if source_scene_json and Path(source_scene_json).exists():
-                source_payload = json.loads(Path(source_scene_json).read_text(encoding="utf-8"))
-                lon = source_payload.get("scene_center_lon")
-                lat = source_payload.get("scene_center_lat")
-        if lon is not None and lat is not None:
-            lons.append(float(lon))
-            lats.append(float(lat))
-    if not lons or not lats:
-        raise ValueError("Stack manifest does not include usable scene center coordinates")
-    west = min(lons) - margin_deg
-    east = max(lons) + margin_deg
-    south = min(lats) - margin_deg
-    north = max(lats) + margin_deg
-    return [south, north, west, east]
-
-
-def prepare_dem(source_dem: Path, output_dem: Path, bbox: List[float]) -> None:
-    from osgeo import gdal
-    from isce.applications.gdal2isce_xml import gdal2isce_xml
-
-    south, north, west, east = bbox
-    src_open_path = Path(str(source_dem) + ".vrt")
-    if not src_open_path.exists():
-        src_open_path = source_dem
-
-    output_dem.parent.mkdir(parents=True, exist_ok=True)
-    output_vrt = Path(str(output_dem) + ".vrt")
-    output_xml = Path(str(output_dem) + ".xml")
-    output_hdr = Path(str(output_dem) + ".hdr")
-    fallback_hdr = output_dem.with_suffix(".hdr")
-
-    src_ds = gdal.Open(str(src_open_path), gdal.GA_ReadOnly)
-    if src_ds is None:
-        raise RuntimeError(f"Unable to open DEM source: {src_open_path}")
-
-    translate_options = gdal.TranslateOptions(
-        format="ENVI",
-        projWin=[west, north, east, south],
-    )
-    out_ds = gdal.Translate(str(output_dem), src_ds, options=translate_options)
-    if out_ds is None:
-        raise RuntimeError("gdal.Translate failed while clipping the DEM")
-    out_ds = None
-    src_ds = None
-
-    vrt_ds = gdal.Open(str(output_dem), gdal.GA_ReadOnly)
-    if vrt_ds is None:
-        raise RuntimeError(f"Unable to reopen clipped DEM: {output_dem}")
-    gdal.Translate(str(output_vrt), vrt_ds, options=gdal.TranslateOptions(format="VRT"))
-    vrt_ds = None
-
-    gdal2isce_xml(str(output_vrt))
-    if not output_xml.exists():
-        raise RuntimeError(f"Expected ISCE XML was not created: {output_xml}")
-    if not output_hdr.exists() and not fallback_hdr.exists():
-        raise RuntimeError(f"Expected ENVI header was not created: {output_hdr} or {fallback_hdr}")
-
-
-def parse_args() -> argparse.Namespace:
-    parser = argparse.ArgumentParser(
-        description="Clip a local DEM window for one LT-1 stack workspace."
-    )
-    parser.add_argument(
-        "--stack-manifest",
-        required=True,
-        help="Path to stack_input_manifest.json generated by build_lt1_stack_prep.py",
-    )
-    parser.add_argument(
-        "--source-dem",
-        default=None,
-        help="Override source DEM base path.",
-    )
-    parser.add_argument(
-        "--margin-deg",
-        type=float,
-        default=1.0,
-        help="Margin around stack scene-center extents in degrees.",
-    )
-    return parser.parse_args()
-
-
-def main() -> int:
-    args = parse_args()
-    manifest_path = Path(args.stack_manifest)
-    if not manifest_path.exists():
-        raise FileNotFoundError(f"Stack manifest not found: {manifest_path}")
-
-    manifest = load_manifest(manifest_path)
-    source_dem = resolve_dem_source(args.source_dem, manifest)
-    bbox = compute_bbox(manifest, margin_deg=args.margin_deg)
-
-    workspace = manifest["workspace"]
-    dem_dir = Path(workspace["inputs_dir_wsl"]) / "dem"
-    output_dem = dem_dir / "stack_dem_window.wgs84"
-    prepare_dem(source_dem=source_dem, output_dem=output_dem, bbox=bbox)
-
-    report = {
-        "stack_manifest": str(manifest_path),
-        "source_dem": str(source_dem),
-        "output_dem": str(output_dem),
-        "bbox_south_north_west_east": bbox,
-    }
-    report_path = dem_dir / "stack_dem_window_report.json"
-    report_path.write_text(json.dumps(report, indent=2, ensure_ascii=False), encoding="utf-8")
-
-    print(f"Source DEM: {source_dem}")
-    print(f"Output DEM: {output_dem}")
-    print(f"BBox:       {bbox}")
-    print(f"Report:     {report_path}")
-    return 0
-
-
-if __name__ == "__main__":
-    raise SystemExit(main())

experiments/isce2_sbas_timeseries/scripts/run_generated_stack_runfile_ubuntu2404.sh

@@ -1,106 +0,0 @@
-#!/usr/bin/env bash
-set -euo pipefail
-
-if [[ $# -lt 2 ]]; then
-  echo "Usage: $0 <scratch_root_wsl> <run_file_name>" >&2
-  echo "Example: $0 /mnt/z/Code/Insar_management_system_v2/experiments/isce2_sbas_timeseries/scratch/lt1a_strip1_hh_descending_e123p3_n46p1 run_01_reference" >&2
-  exit 1
-fi
-
-SCRATCH_ROOT="$1"
-RUN_FILE_NAME="$2"
-SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
-CONDA_ROOT="${CONDA_ROOT:-/home/administrator/miniconda3}"
-CONDA_ENV="${CONDA_ENV:-insar_wsl_v1}"
-CONDA_BIN="${CONDA_BIN:-$CONDA_ROOT/bin/conda}"
-ISCE2_SHARE="${ISCE2_SHARE:-$CONDA_ROOT/envs/$CONDA_ENV/share/isce2}"
-STRIPMAP_STACK_DIR="${STRIPMAP_STACK_DIR:-$ISCE2_SHARE/stripmapStack}"
-SYNTHETIC_WATERMASK_SCRIPT="${SYNTHETIC_WATERMASK_SCRIPT:-$SCRIPT_DIR/create_synthetic_watermask.py}"
-ALLOW_SYNTHETIC_WATERMASK="${ALLOW_SYNTHETIC_WATERMASK:-1}"
-STACK_WORK="$SCRATCH_ROOT/stack_work"
-RUN_FILE="$STACK_WORK/run_files/$RUN_FILE_NAME"
-LOG_DIR="$STACK_WORK/logs"
-LOG_FILE="$LOG_DIR/$RUN_FILE_NAME.log"
-
-if [[ ! -x "$CONDA_BIN" ]]; then
-  echo "Missing conda binary: $CONDA_BIN" >&2
-  exit 1
-fi
-
-if [[ ! -f "$RUN_FILE" ]]; then
-  echo "Run file not found: $RUN_FILE" >&2
-  exit 1
-fi
-
-mkdir -p "$LOG_DIR"
-
-export PYTHONPATH="$STRIPMAP_STACK_DIR:$ISCE2_SHARE${PYTHONPATH:+:$PYTHONPATH}"
-export PATH="$STRIPMAP_STACK_DIR:$PATH"
-
-recover_reference_watermask() {
-  local like_image="$STACK_WORK/geom_reference/shadowMask.rdr"
-  local output_mask="$STACK_WORK/geom_reference/waterMask.rdr"
-  local report_path="$LOG_DIR/$RUN_FILE_NAME.synthetic_watermask.json"
-  local watermask_failure_pattern='Please create a \.netrc file|Running: createWaterMask|DataRetriever - ERROR|There was a problem in retrieving the file|SRTMSWBD\.003|SWBD'
-
-  if [[ "$RUN_FILE_NAME" != "run_01_reference" ]]; then
-    return 1
-  fi
-
-  if [[ "$ALLOW_SYNTHETIC_WATERMASK" != "1" ]]; then
-    return 1
-  fi
-
-  if [[ ! -f "$LOG_FILE" ]]; then
-    return 1
-  fi
-
-  # Recover only the known offline water-mask failure modes observed in this
-  # experiment: missing Earthdata credentials or SWBD retrieval failure.
-  if ! grep -Eq "$watermask_failure_pattern" "$LOG_FILE"; then
-    return 1
-  fi
-
-  if [[ ! -f "$like_image" || ! -f "$like_image.xml" ]]; then
-    echo "Synthetic water-mask fallback could not find template image: $like_image" >&2
-    return 1
-  fi
-
-  if [[ ! -f "$SYNTHETIC_WATERMASK_SCRIPT" ]]; then
-    echo "Synthetic water-mask helper script not found: $SYNTHETIC_WATERMASK_SCRIPT" >&2
-    return 1
-  fi
-
-  echo "Earthdata credentials are unavailable. Creating a synthetic all-land water mask."
-  "$CONDA_BIN" run -n "$CONDA_ENV" python "$SYNTHETIC_WATERMASK_SCRIPT" \
-    --like-image "$like_image" \
-    --output "$output_mask" \
-    --fill-value 1 \
-    --force \
-    --report "$report_path"
-}
-
-echo "Executing stripmap stack run file"
-echo "Scratch root: $SCRATCH_ROOT"
-echo "Run file:     $RUN_FILE"
-echo "Log file:     $LOG_FILE"
-echo "Conda env:    $CONDA_ENV"
-echo "Conda bin:    $CONDA_BIN"
-echo "ISCE2 share:  $ISCE2_SHARE"
-echo "PYTHONPATH:   $PYTHONPATH"
-echo "PATH prefix:  $STRIPMAP_STACK_DIR"
-
-set -o pipefail
-"$CONDA_BIN" run -n "$CONDA_ENV" bash "$RUN_FILE" 2>&1 | tee "$LOG_FILE"
-RUN_STATUS=${PIPESTATUS[0]}
-
-if [[ "$RUN_STATUS" -eq 0 ]]; then
-  exit 0
-fi
-
-if recover_reference_watermask; then
-  echo "Recovered $RUN_FILE_NAME with a synthetic all-land water mask."
-  exit 0
-fi
-
-exit "$RUN_STATUS"

experiments/isce2_sbas_timeseries/scripts/run_mintpy_sbas_smoketest_ubuntu2404.sh

@@ -1,26 +0,0 @@
-#!/usr/bin/env bash
-set -euo pipefail
-
-if [[ $# -ne 2 ]]; then
-  echo "Usage: $0 <smallbaseline-config-wsl> <mintpy-work-dir-wsl>" >&2
-  exit 1
-fi
-
-CFG_PATH="$1"
-WORK_DIR="$2"
-SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
-BRIDGE_RUNNER="$SCRIPT_DIR/run_mintpy_with_isce_ubuntu2404.sh"
-PATCHED_APP="$SCRIPT_DIR/run_smallbaselineApp_patched.py"
-STRICT_MASK_BUILDER="$SCRIPT_DIR/create_mintpy_all_ifgram_mask.py"
-
-echo "MintPy SBAS smoketest"
-echo "Config:   $CFG_PATH"
-echo "Work dir: $WORK_DIR"
-
-bash "$BRIDGE_RUNNER" python "$PATCHED_APP" "$CFG_PATH" --dir "$WORK_DIR" --dostep load_data
-
-bash "$BRIDGE_RUNNER" python "$STRICT_MASK_BUILDER" \
-  --ifgram-stack "$WORK_DIR/inputs/ifgramStack.h5" \
-  --output "$WORK_DIR/maskAllValid.h5"
-
-bash "$BRIDGE_RUNNER" python "$PATCHED_APP" "$CFG_PATH" --dir "$WORK_DIR" --start modify_network --end velocity

experiments/isce2_sbas_timeseries/scripts/run_mintpy_sbas_unified_env_smoketest_ubuntu2404.sh

@@ -1,26 +0,0 @@
-#!/usr/bin/env bash
-set -euo pipefail
-
-if [[ $# -ne 2 ]]; then
-  echo "Usage: $0 <smallbaseline-config-wsl> <mintpy-work-dir-wsl>" >&2
-  exit 1
-fi
-
-CFG_PATH="$1"
-WORK_DIR="$2"
-SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
-UNIFIED_RUNNER="$SCRIPT_DIR/run_mintpy_unified_env_ubuntu2404.sh"
-PATCHED_APP="$SCRIPT_DIR/run_smallbaselineApp_patched.py"
-STRICT_MASK_BUILDER="$SCRIPT_DIR/create_mintpy_all_ifgram_mask.py"
-
-echo "MintPy SBAS unified-env smoketest"
-echo "Config:   $CFG_PATH"
-echo "Work dir: $WORK_DIR"
-
-bash "$UNIFIED_RUNNER" python "$PATCHED_APP" "$CFG_PATH" --dir "$WORK_DIR" --dostep load_data
-
-bash "$UNIFIED_RUNNER" python "$STRICT_MASK_BUILDER" \
-  --ifgram-stack "$WORK_DIR/inputs/ifgramStack.h5" \
-  --output "$WORK_DIR/maskAllValid.h5"
-
-bash "$UNIFIED_RUNNER" python "$PATCHED_APP" "$CFG_PATH" --dir "$WORK_DIR" --start modify_network --end velocity

experiments/isce2_sbas_timeseries/scripts/run_mintpy_unified_env_ubuntu2404.sh

@@ -1,23 +0,0 @@
-#!/usr/bin/env bash
-set -euo pipefail
-
-if [[ $# -lt 1 ]]; then
-  echo "Usage: $0 <mintpy-command> [args...]" >&2
-  echo "Example: $0 prep_isce.py -h" >&2
-  exit 1
-fi
-
-CONDA_BIN="${CONDA_BIN:-/home/administrator/miniconda3/bin/conda}"
-MINTPY_ENV="${MINTPY_ENV:-isce2_mintpy}"
-
-if [[ ! -x "$CONDA_BIN" ]]; then
-  echo "Missing conda binary: $CONDA_BIN" >&2
-  exit 1
-fi
-
-echo "MintPy command in unified env"
-echo "Conda:      $CONDA_BIN"
-echo "Target env: $MINTPY_ENV"
-echo "Command:    $*"
-
-"$CONDA_BIN" run -n "$MINTPY_ENV" "$@"

experiments/isce2_sbas_timeseries/scripts/run_mintpy_with_isce_ubuntu2404.sh

@@ -1,45 +0,0 @@
-#!/usr/bin/env bash
-set -euo pipefail
-
-if [[ $# -lt 1 ]]; then
-  echo "Usage: $0 <mintpy-command> [args...]" >&2
-  echo "Example: $0 prep_isce.py -h" >&2
-  exit 1
-fi
-
-CONDA_BIN="${CONDA_BIN:-/home/administrator/miniconda3/bin/conda}"
-MINTPY_ENV="${MINTPY_ENV:-mintpy}"
-ISCE_SITE_PACKAGES="${ISCE_SITE_PACKAGES:-/home/administrator/miniconda3/envs/isce2/lib/python3.11/site-packages}"
-ISCE_PACKAGE_DIR="${ISCE_PACKAGE_DIR:-$ISCE_SITE_PACKAGES/isce}"
-ISCE_BRIDGE_DIR="${ISCE_BRIDGE_DIR:-$HOME/.cache/mintpy_isce_bridge}"
-
-if [[ ! -x "$CONDA_BIN" ]]; then
-  echo "Missing conda binary: $CONDA_BIN" >&2
-  exit 1
-fi
-
-if [[ ! -d "$ISCE_SITE_PACKAGES" ]]; then
-  echo "Missing ISCE site-packages directory: $ISCE_SITE_PACKAGES" >&2
-  exit 1
-fi
-
-if [[ ! -d "$ISCE_PACKAGE_DIR" ]]; then
-  echo "Missing ISCE package directory: $ISCE_PACKAGE_DIR" >&2
-  exit 1
-fi
-
-mkdir -p "$ISCE_BRIDGE_DIR"
-ln -sfn "$ISCE_PACKAGE_DIR" "$ISCE_BRIDGE_DIR/isce"
-
-# Bridge only the top-level ISCE package into the MintPy env.
-# The package itself extends sys.path to its internal components on import,
-# which avoids shadowing MintPy's own numpy/h5py stack with the isce2 env.
-export PYTHONPATH="$ISCE_BRIDGE_DIR${PYTHONPATH:+:$PYTHONPATH}"
-
-echo "MintPy command bridge"
-echo "Conda:        $CONDA_BIN"
-echo "MintPy env:   $MINTPY_ENV"
-echo "ISCE bridge:  $ISCE_BRIDGE_DIR -> $ISCE_PACKAGE_DIR"
-echo "Command:      $*"
-
-"$CONDA_BIN" run -n "$MINTPY_ENV" "$@"

experiments/isce2_sbas_timeseries/scripts/run_smallbaselineApp_patched.py

@@ -1,38 +0,0 @@
-#!/usr/bin/env python3
-"""Run MintPy smallbaselineApp with a local workaround for a single-pixel inversion bug."""
-
-from __future__ import annotations
-
-import sys
-
-import numpy as np
-
-import mintpy.ifgram_inversion as ifgram_inversion
-from mintpy.cli.smallbaselineApp import main as mintpy_smallbaseline_main
-
-
-_ORIGINAL_ESTIMATE_TIMESERIES = ifgram_inversion.estimate_timeseries
-
-
-def _patched_estimate_timeseries(*args, **kwargs):
-    ts, inv_quality, num_inv_obs = _ORIGINAL_ESTIMATE_TIMESERIES(*args, **kwargs)
-
-    # MintPy 1.6.2 may return a shape-(1,) inversion quality array for the
-    # single-pixel partial-network branch, while the caller expects a scalar.
-    if isinstance(inv_quality, np.ndarray) and inv_quality.size == 1:
-        inv_quality = np.asarray(inv_quality).reshape(-1)[0].item()
-
-    if isinstance(num_inv_obs, np.ndarray) and num_inv_obs.size == 1:
-        num_inv_obs = int(np.asarray(num_inv_obs).reshape(-1)[0])
-
-    return ts, inv_quality, num_inv_obs
-
-
-def main(argv: list[str] | None = None) -> int:
-    ifgram_inversion.estimate_timeseries = _patched_estimate_timeseries
-    print("Applied local MintPy estimate_timeseries single-pixel fix.")
-    return mintpy_smallbaseline_main(argv)
-
-
-if __name__ == "__main__":
-    raise SystemExit(main(sys.argv[1:]))

experiments/isce2_sbas_timeseries/scripts/scan_lt1_stack_candidates.py

@@ -1,373 +0,0 @@
-#!/usr/bin/env python3
-from __future__ import annotations
-
-import argparse
-import importlib.util
-import json
-import os
-import re
-from dataclasses import asdict, dataclass
-from pathlib import Path
-from typing import Any, Dict, List, Optional
-
-
-def _repo_root() -> Path:
-    return Path(__file__).resolve().parents[3]
-
-
-def _load_utils_module():
-    utils_path = _repo_root() / "backend" / "app" / "utils.py"
-    spec = importlib.util.spec_from_file_location("repo_utils", utils_path)
-    if spec is None or spec.loader is None:
-        raise RuntimeError(f"Unable to load repo utils module: {utils_path}")
-    module = importlib.util.module_from_spec(spec)
-    spec.loader.exec_module(module)
-    return module
-
-
-UTILS = _load_utils_module()
-
-
-LT1_NAME_RE = re.compile(
-    r"^(?P<satellite>LT1[AB])_"
-    r"(?P<satellite_mode>[^_]+)_"
-    r"(?P<receiving_station>[^_]+)_"
-    r"(?P<imaging_mode>[^_]+)_"
-    r"(?P<abs_orbit>\d+)_"
-    r"(?P<lon>E\d+\.\d+)_"
-    r"(?P<lat>N\d+\.\d+)_"
-    r"(?P<date>\d{8})_"
-    r"(?P<product_type>[^_]+)_"
-    r"(?P<polarization>[^_]+)_"
-    r"(?P<product_level>[^_]+)_"
-    r"(?P<product_unique_id>\d+)$"
-)
-
-
-@dataclass
-class SceneRecord:
-    folder_name: str
-    folder_path: str
-    folder_path_wsl: str
-    tiff_path: str
-    tiff_path_wsl: str
-    meta_path: str
-    meta_path_wsl: str
-    file_size_bytes: int
-    satellite: str
-    imaging_date: str
-    imaging_mode: Optional[str]
-    polarization: Optional[str]
-    orbit_direction: Optional[str]
-    satellite_mode: Optional[str]
-    receiving_station: Optional[str]
-    orbit_circle: Optional[str]
-    scene_center_lon: Optional[float]
-    scene_center_lat: Optional[float]
-    acquisition_time_utc: Optional[str]
-    product_type: Optional[str]
-    product_level: Optional[str]
-    product_unique_id: Optional[str]
-    tile_key: str
-    group_key: str
-    orbit_txt_expected_name: str
-
-
-def windows_to_wsl(path: str | Path) -> str:
-    text = str(path)
-    match = re.match(r"^([A-Za-z]):[\\/](.*)$", os.path.normpath(text))
-    if not match:
-        return text.replace("\\", "/")
-    drive = match.group(1).lower()
-    normalized_tail = match.group(2).replace("\\", "/").lstrip("/")
-    return f"/mnt/{drive}/{normalized_tail}"
-
-
-def choose_tiff(folder: Path) -> Optional[Path]:
-    candidates = sorted(folder.glob("*.tiff"))
-    if not candidates:
-        return None
-    slc_candidates = [path for path in candidates if "_SLC_" in path.name]
-    if len(slc_candidates) == 1:
-        return slc_candidates[0]
-    if len(candidates) == 1:
-        return candidates[0]
-    return candidates[0]
-
-
-def merge_metadata(name_meta: Dict[str, Any], xml_meta: Dict[str, Any]) -> Dict[str, Any]:
-    merged = dict(name_meta or {})
-    prefer_name_keys = {"product_unique_id"}
-    for key, value in (xml_meta or {}).items():
-        if value in (None, ""):
-            continue
-        if key in prefer_name_keys and merged.get(key):
-            continue
-        merged[key] = value
-    return merged
-
-
-def parse_scene(folder: Path) -> Optional[SceneRecord]:
-    match = LT1_NAME_RE.match(folder.name)
-    if not match:
-        return None
-
-    name_meta = UTILS.get_parser(folder.name, UTILS.RADAR_PARSERS)
-    if not name_meta:
-        return None
-
-    xml_file_path = UTILS.find_xml_file(str(folder))
-    if not xml_file_path:
-        return None
-
-    coverage_polygon, xml_meta = UTILS.parse_xml_metadata(xml_file_path)
-    if not coverage_polygon:
-        return None
-
-    tiff_path = choose_tiff(folder)
-    if tiff_path is None:
-        return None
-
-    merged = merge_metadata(name_meta, xml_meta or {})
-    tile_key = f"{match.group('lon')}_{match.group('lat')}"
-    orbit_direction = str(merged.get("orbit_direction") or "").upper() or None
-    group_key = "|".join(
-        [
-            str(merged.get("satellite") or ""),
-            str(merged.get("imaging_mode") or ""),
-            str(merged.get("polarization") or ""),
-            str(orbit_direction or ""),
-            tile_key,
-        ]
-    )
-    satellite = str(merged.get("satellite") or "")
-    imaging_date = str(merged.get("imaging_date") or "")
-
-    return SceneRecord(
-        folder_name=folder.name,
-        folder_path=str(folder),
-        folder_path_wsl=windows_to_wsl(folder),
-        tiff_path=str(tiff_path),
-        tiff_path_wsl=windows_to_wsl(tiff_path),
-        meta_path=str(xml_file_path),
-        meta_path_wsl=windows_to_wsl(xml_file_path),
-        file_size_bytes=tiff_path.stat().st_size,
-        satellite=satellite,
-        imaging_date=imaging_date,
-        imaging_mode=merged.get("imaging_mode"),
-        polarization=merged.get("polarization"),
-        orbit_direction=orbit_direction,
-        satellite_mode=merged.get("satellite_mode"),
-        receiving_station=merged.get("receiving_station"),
-        orbit_circle=merged.get("orbit_circle"),
-        scene_center_lon=merged.get("scene_center_lon"),
-        scene_center_lat=merged.get("scene_center_lat"),
-        acquisition_time_utc=merged.get("acquisition_time_utc"),
-        product_type=merged.get("product_type"),
-        product_level=merged.get("product_level"),
-        product_unique_id=merged.get("product_unique_id"),
-        tile_key=tile_key,
-        group_key=group_key,
-        orbit_txt_expected_name=f"{satellite}_GpsData_GAS_C_{imaging_date}.txt",
-    )
-
-
-def scan_scenes(root_dir: Path) -> List[SceneRecord]:
-    scenes: List[SceneRecord] = []
-    for entry in sorted(root_dir.iterdir()):
-        if not entry.is_dir():
-            continue
-        scene = parse_scene(entry)
-        if scene:
-            scenes.append(scene)
-    return scenes
-
-
-def build_group_summary(scenes: List[SceneRecord]) -> List[Dict[str, Any]]:
-    groups: Dict[str, List[SceneRecord]] = {}
-    for scene in scenes:
-        groups.setdefault(scene.group_key, []).append(scene)
-
-    summary: List[Dict[str, Any]] = []
-    for key, items in groups.items():
-        items.sort(key=lambda item: item.imaging_date)
-        first = items[0]
-        summary.append(
-            {
-                "group_key": key,
-                "count": len(items),
-                "satellite": first.satellite,
-                "imaging_mode": first.imaging_mode,
-                "polarization": first.polarization,
-                "orbit_direction": first.orbit_direction,
-                "tile_key": first.tile_key,
-                "dates": [item.imaging_date for item in items],
-                "receiving_stations": sorted({item.receiving_station for item in items if item.receiving_station}),
-            }
-        )
-    summary.sort(key=lambda item: (-item["count"], item["group_key"]))
-    return summary
-
-
-def select_group(
-    summary: List[Dict[str, Any]],
-    tile_key: Optional[str],
-    group_key: Optional[str],
-    min_scenes: int,
-) -> Optional[str]:
-    if group_key:
-        return group_key
-    if tile_key:
-        for item in summary:
-            if item["tile_key"] == tile_key and item["count"] >= min_scenes:
-                return item["group_key"]
-        return None
-    for item in summary:
-        if item["count"] >= min_scenes:
-            return item["group_key"]
-    return None
-
-
-def build_manifest(root_dir: Path, group_key: str, scenes: List[SceneRecord]) -> Dict[str, Any]:
-    group_scenes = [scene for scene in scenes if scene.group_key == group_key]
-    if not group_scenes:
-        raise ValueError(f"Group not found: {group_key}")
-    group_scenes.sort(key=lambda item: item.imaging_date)
-
-    first = group_scenes[0]
-    reference_index = len(group_scenes) // 2
-    reference_scene = group_scenes[reference_index]
-    slug = (
-        f"{first.satellite.lower()}_"
-        f"{(first.imaging_mode or 'unknown').lower()}_"
-        f"{(first.polarization or 'unknown').lower()}_"
-        f"{(first.orbit_direction or 'unknown').lower()}_"
-        f"{first.tile_key.lower().replace('.', 'p')}"
-    )
-
-    scratch_root = _repo_root() / "experiments" / "isce2_sbas_timeseries" / "scratch" / slug
-    scratch_root_wsl = windows_to_wsl(scratch_root)
-
-    return {
-        "source_root_windows": str(root_dir),
-        "source_root_wsl": windows_to_wsl(root_dir),
-        "group_key": group_key,
-        "tile_key": first.tile_key,
-        "scene_count": len(group_scenes),
-        "reference_strategy": "middle_by_date",
-        "reference_date": reference_scene.imaging_date,
-        "stack_group": {
-            "satellite": first.satellite,
-            "imaging_mode": first.imaging_mode,
-            "polarization": first.polarization,
-            "orbit_direction": first.orbit_direction,
-            "receiving_stations": sorted({item.receiving_station for item in group_scenes if item.receiving_station}),
-        },
-        "proposed_scratch_windows": str(scratch_root),
-        "proposed_scratch_wsl": scratch_root_wsl,
-        "proposed_layout": {
-            "stack_input_manifest": f"{scratch_root_wsl}/stack_input_manifest.json",
-            "slc_dir": f"{scratch_root_wsl}/SLC",
-            "orbits_dir": f"{scratch_root_wsl}/orbits",
-            "logs_dir": f"{scratch_root_wsl}/logs",
-        },
-        "stack_prep_assessment": {
-            "current_scene_layout": "per_scene_folder_with_tiff_meta_rpc",
-            "official_stripmapStack_expected_layout": "SLC/YYYYMMDD/YYYYMMDD.raw or YYYYMMDD.slc",
-            "direct_compatibility": "unproven",
-            "lt1_adapter_required_likely": True,
-            "notes": [
-                "Current repo can read these scene folders as RadarData assets.",
-                "Official stripmapStack helper scripts do not advertise LT-1/LUTAN1 preparation hooks.",
-                "A custom LT-1 stack preparation layer is likely needed before official stack execution.",
-            ],
-        },
-        "scenes": [asdict(scene) for scene in group_scenes],
-    }
-
-
-def build_parser() -> argparse.ArgumentParser:
-    parser = argparse.ArgumentParser(
-        description="Scan LT-1 scene folders and build a dry-run SBAS stack-prep manifest."
-    )
-    parser.add_argument(
-        "--root-dir",
-        default=r"F:\Insar_data_pool_1",
-        help="Windows root directory containing LT-1 scene folders.",
-    )
-    parser.add_argument(
-        "--min-scenes",
-        type=int,
-        default=4,
-        help="Minimum scenes required for candidate groups.",
-    )
-    parser.add_argument(
-        "--top-n",
-        type=int,
-        default=20,
-        help="How many candidate groups to print.",
-    )
-    parser.add_argument(
-        "--tile-key",
-        default=None,
-        help="Pick one candidate by tile key, for example E123.3_N46.1.",
-    )
-    parser.add_argument(
-        "--group-key",
-        default=None,
-        help="Pick one candidate by full group key.",
-    )
-    parser.add_argument(
-        "--manifest-path",
-        default=None,
-        help="Optional JSON output path for the selected group's dry-run manifest.",
-    )
-    return parser
-
-
-def main() -> int:
-    args = build_parser().parse_args()
-    root_dir = Path(args.root_dir)
-    if not root_dir.exists():
-        raise FileNotFoundError(f"Root directory does not exist: {root_dir}")
-
-    scenes = scan_scenes(root_dir)
-    summary = build_group_summary(scenes)
-
-    print(f"scanned_scenes={len(scenes)}")
-    print(f"candidate_groups={len(summary)}")
-    print("top_candidates:")
-    for item in summary[: args.top_n]:
-        print(
-            json.dumps(
-                {
-                    "count": item["count"],
-                    "tile_key": item["tile_key"],
-                    "group_key": item["group_key"],
-                    "dates": item["dates"],
-                    "receiving_stations": item["receiving_stations"],
-                },
-                ensure_ascii=False,
-            )
-        )
-
-    selected_group = select_group(summary, args.tile_key, args.group_key, args.min_scenes)
-    if not selected_group:
-        print("selected_group=None")
-        return 0
-
-    manifest = build_manifest(root_dir, selected_group, scenes)
-    print(f"selected_group={selected_group}")
-    print(f"reference_date={manifest['reference_date']}")
-
-    if args.manifest_path:
-        manifest_path = Path(args.manifest_path)
-        manifest_path.parent.mkdir(parents=True, exist_ok=True)
-        manifest_path.write_text(json.dumps(manifest, indent=2, ensure_ascii=False), encoding="utf-8")
-        print(f"manifest_written={manifest_path}")
-
-    return 0
-
-
-if __name__ == "__main__":
-    raise SystemExit(main())

frontend/src/DinsarProductionPanel.jsx

@@ -129,6 +129,7 @@ function epochSeconds(value) {
 
 function taskToRunRow(task) {
   const taskId = task?.task_id || '';
+  const message = task?.message || task?.task_name || '';
   return {
     run_id: taskId,
     record_type: 'task',
@@ -145,7 +146,8 @@ function taskToRunRow(task) {
     workflow_run_id: '',
     root_dir: '',
     publish_root_dir: '',
-    message: task?.message || task?.task_name || '',
+    message,
+    inferred_paths: inferTaskPaths(task),
     total_items: null,
     completed_items: null,
     failed_items: null,
@@ -153,6 +155,17 @@ function taskToRunRow(task) {
   };
 }
 
+function inferTaskPaths(task) {
+  const message = String(task?.message || '').trim();
+  const workMatch = message.match(/work_dir=([^)\s]+)/);
+  const workDir = workMatch ? workMatch[1] : '';
+  if (!workDir) return {};
+  return {
+    work_dir: workDir,
+    ifgrams_dir: workDir ? `${workDir}\\<project>\\ifgrams` : '',
+  };
+}
+
 function mergeRunRows(productionRuns, recentTasks, limit = 20) {
   const rows = (productionRuns || []).map(run => ({
     ...run,
@@ -206,6 +219,49 @@ function formatPyintPreciseOrbitMode(mode) {
   return PYINT_PRECISE_ORBIT_MODE_LABEL[mode] || mode || '-';
 }
 
+function getSchemaOptions(schema) {
+  if (Array.isArray(schema?.enum) && schema.enum.length > 0) return schema.enum;
+  if (Array.isArray(schema?.choices) && schema.choices.length > 0) return schema.choices;
+  return [];
+}
+
+function formatPathValue(value) {
+  const text = String(value || '').trim();
+  return text || '-';
+}
+
+function RunPathBlock({ run }) {
+  const items = Array.isArray(run?.items) ? run.items : [];
+  const item = items.find(entry => entry?.status === 'RUNNING') || items[0] || null;
+  const paths = item?.paths || run?.inferred_paths || {};
+  if (!item && Object.keys(paths).length === 0) return null;
+  const rows = [
+    ['任务', item?.task_alias || item?.task_name || run?.message || '-'],
+    ['运行目录', paths.run_dir],
+    ['native', paths.native_dir],
+    ['assets', paths.assets_dir],
+  ];
+  if (run?.engine === 'pyint') {
+    rows.push(['work', paths.work_dir]);
+    rows.push(['project', paths.project_dir]);
+    rows.push(['ifgrams', paths.ifgrams_dir]);
+    rows.push(['重去平日志', paths.reflatten_dir]);
+  }
+
+  return (
+    <div style={{ marginTop: 4, display: 'flex', flexDirection: 'column', gap: 2 }}>
+      {rows.filter(([, value]) => String(value || '').trim()).map(([label, value]) => (
+        <div key={label} style={{ display: 'flex', gap: 6, alignItems: 'flex-start' }}>
+          <span style={{ minWidth: 58, color: '#94a3b8' }}>{label}</span>
+          <span style={{ fontFamily: 'monospace', color: '#334155', wordBreak: 'break-all' }}>
+            {formatPathValue(value)}
+          </span>
+        </div>
+      ))}
+    </div>
+  );
+}
+
 function PreviewIssueList({ title, items, tone = 'warning' }) {
   if (!Array.isArray(items) || items.length === 0) {
     return null;
@@ -387,7 +443,8 @@ function ParamField({ name, schema, value, disabled, onChange }) {
     );
   }
 
-  if (Array.isArray(schema.enum) && schema.enum.length > 0) {
+  const options = getSchemaOptions(schema);
+  if (options.length > 0) {
     return (
       <div style={{ minWidth: 180, flex: '0 1 220px' }}>
         <div style={{ display: 'flex', alignItems: 'center', gap: 6, marginBottom: 4 }}>
@@ -407,12 +464,12 @@ function ParamField({ name, schema, value, disabled, onChange }) {
           )}
         </div>
         <select
-          value={value ?? schema.default ?? schema.enum[0]}
+          value={value ?? schema.default ?? options[0]}
           disabled={disabled || isReadonly}
           onChange={event => onChange(name, event.target.value)}
           style={inputStyle}
         >
-          {schema.enum.map(option => (
+          {options.map(option => (
             <option key={option} value={option}>{option}</option>
           ))}
         </select>
@@ -493,7 +550,7 @@ export default function DinsarProductionPanel({ readOnly = false, onJobQueued })
   const currentParamSections = buildParamSections(currentParamSchema);
   const currentDefaultTimeoutSec = Number(currentEngineObj?.default_timeout_seconds || 0) || 0;
   const currentParamHelpText = selectedEngine === 'pyint'
-    ? 'PyINT/Gamma 默认按目标网格尺寸自动换算多视，逻辑与 ENVI/SARscape 自定义流程一致；通常只需要设置目标网格、并行度和是否执行解缠/地理编码。'
+    ? 'PyINT/Gamma 会按目标网格尺寸自动换算多视；新增 Gamma 残余重去平在解缠后执行 rascc_mask/quad_fit/quad_sub，再导出 native 和标准 GeoTIFF。'
     : selectedEngine === 'isce2'
       ? '这些参数现在按执行、交付、增强分组展示。结果异常时，优先尝试关闭增强项，再回看基础几何和配对质量。'
       : '这些参数影响当前引擎的生产模板。建议先使用默认值，只有在结果边界、噪声或几何表现异常时再逐项调整。';
@@ -1090,7 +1147,7 @@ export default function DinsarProductionPanel({ readOnly = false, onJobQueued })
             )}
             {selectedEngine === 'pyint' && currentDefaultTimeoutSec > 0 && (
               <div style={{ fontSize: 11, color: '#94a3b8', marginTop: 4 }}>
-                PyINT 默认按单对任务使用 {currentDefaultTimeoutSec} 秒；当前会逐对串行创建工作区并运行外部 PyINT / Gamma 流程。
+                PyINT 默认按单对任务使用 {currentDefaultTimeoutSec} 秒；当前会逐对串行创建工作区并运行外部 PyINT / Gamma 流程，native 会在主流程和重去平后统一写入。
               </div>
             )}
           </div>
@@ -1512,7 +1569,7 @@ export default function DinsarProductionPanel({ readOnly = false, onJobQueued })
           <table style={{ width: '100%', borderCollapse: 'collapse', fontSize: 12 }}>
             <thead>
               <tr style={{ background: '#f8fafc' }}>
-                {['运行ID', '引擎', '状态', '时间', '操作'].map(header => (
+                {['运行ID', '引擎', '状态', '时间', '路径', '操作'].map(header => (
                   <th
                     key={header}
                     style={{ padding: '4px 8px', textAlign: 'left', borderBottom: '1px solid #e2e8f0', color: '#64748b' }}
@@ -1538,6 +1595,9 @@ export default function DinsarProductionPanel({ readOnly = false, onJobQueued })
                   <td style={{ padding: '4px 8px', color: '#94a3b8' }}>
                     {run.started_at ? new Date(run.started_at * 1000).toLocaleString() : '-'}
                   </td>
+                  <td style={{ padding: '4px 8px', maxWidth: 520, fontSize: 11 }}>
+                    <RunPathBlock run={run} />
+                  </td>
                   <td style={{ padding: '4px 8px' }}>
                     <button
                       onClick={() => handleViewLog(run)}

license-issuer/start_gui.bat

@@ -1,17 +1,38 @@
 @echo off
 setlocal
+chcp 65001 >nul
 cd /d "%~dp0"
 
+set "APP=%~dp0license_issuer_gui.pyw"
+set "PYTHONDONTWRITEBYTECODE=1"
+if not defined PYTHON_PATH set "PYTHON_PATH=C:\ProgramData\anaconda3\envs\InSAR\python.exe"
+for %%I in ("%PYTHON_PATH%") do set "PYTHONW_PATH=%%~dpIpythonw.exe"
+
+if exist "%PYTHONW_PATH%" (
+    start "" "%PYTHONW_PATH%" "%APP%"
+    exit /b 0
+)
+
+if exist "%PYTHON_PATH%" (
+    "%PYTHON_PATH%" "%APP%"
+    if errorlevel 1 pause
+    exit /b %errorlevel%
+)
+
 where pyw >nul 2>nul
 if %errorlevel%==0 (
-    start "" pyw -3 "%~dp0license_issuer_gui.pyw"
+    start "" pyw -3 "%APP%"
     exit /b 0
 )
 
 where pythonw >nul 2>nul
 if %errorlevel%==0 (
-    start "" pythonw "%~dp0license_issuer_gui.pyw"
+    start "" pythonw "%APP%"
     exit /b 0
 )
 
-python "%~dp0license_issuer_gui.pyw"
+echo [!] Python not found.
+echo     Expected: %PYTHON_PATH%
+echo     Or install Python Launcher / pythonw and add it to PATH.
+pause
+exit /b 1

third_party/PyINT/pyint/_utils.py

@@ -135,6 +135,7 @@ def update_template(template_file):
     
     templateDict['atmcor_all'] = '0'                 # if 1, run atmospheric correction
     templateDict['atmcor_all_parallel'] = '1'        # multi-processor number used
+    templateDict['atmcor_use_for_disp'] = '0'        # if 1, use atmcor unw as dispmap input
     
     templateDict['geocode_all'] = '0'            
     templateDict['geocode_all_parallel'] = '1'         # multi-processor number used

third_party/PyINT/pyint/atm_correction_gamma.py

@@ -16,6 +16,13 @@ import argparse
 from pyint import _utils as ut
 
 
+def _run_or_raise(call_str, stage):
+    rc = os.system(call_str)
+    if rc != 0:
+        raise RuntimeError('%s failed with rc=%s: %s' % (stage, rc, call_str))
+    return rc
+
+
 INTRODUCTION = '''
 -------------------------------------------------------------------  
        Unwrap differential interferogram using GAMMA.
@@ -74,10 +81,22 @@ def main(argv):
     
     ################ prepare file for parallel processing ###############
     HGTSIM      = demDir + '/' + masterDate + '_' + rlks + 'rlks.rdc.dem'   
+    Mamp0   = rslcDir + '/' + Mdate + '/' + Mdate + '_' + rlks + 'rlks.amp'
+    Samp0   = rslcDir + '/' + Sdate + '/' + Sdate + '_' + rlks + 'rlks.amp'
+    MampPar0 = rslcDir + '/' + Mdate + '/' + Mdate + '_' + rlks + 'rlks.amp.par'
+    SampPar0 = rslcDir + '/' + Sdate + '/' + Sdate + '_' + rlks + 'rlks.amp.par'
     Mamp    = workDir + '/' + Mdate + '_' + rlks + 'rlks.amp'
     MampPar = workDir + '/' + Mdate + '_' + rlks + 'rlks.amp.par'
     Samp    = workDir + '/' + Sdate + '_' + rlks + 'rlks.amp'
     SampPar = workDir + '/' + Sdate + '_' + rlks + 'rlks.amp.par'
+    if not os.path.isfile(Mamp):
+        ut.copy_file(Mamp0, Mamp)
+    if not os.path.isfile(Samp):
+        ut.copy_file(Samp0, Samp)
+    if not os.path.isfile(MampPar):
+        ut.copy_file(MampPar0, MampPar)
+    if not os.path.isfile(SampPar):
+        ut.copy_file(SampPar0, SampPar)
     diff_par = workDir + '/' + Mdate + '_' + Sdate + '_diff_par'
     UNWlks = workDir + '/' + Pair + '_' +rlks + 'rlks.diff_filt.unw'
     CORMASK = workDir + '/' + Pair + '_' +rlks + 'rlks.diff_filt.cor'
@@ -88,18 +107,18 @@ def main(argv):
     nLine =  ut.read_gamma_par(MampPar, 'read', 'azimuth_lines')
    ###############################################################  
     call_str = "create_diff_par " + MampPar + " " + SampPar + " " + diff_par + " 1 0 "
-    os.system(call_str)
+    _run_or_raise(call_str, 'create_diff_par_atmcor')
     call_str = "atm_mod_2d " + UNWlks + " " + HGTSIM + " " + CORMASK + " " + diff_par + " " + " - 0 a0 a1 sigma sigma_h s1"
-    os.system(call_str)
+    _run_or_raise(call_str, 'atm_mod_2d')
     call_str = "atm_sim_2d " + diff_par + " " +  HGTSIM + " a0 a1  " + ATM_PHASE
-    os.system(call_str)
+    _run_or_raise(call_str, 'atm_sim_2d')
     call_str = "sub_phase " + UNWlks + " " + ATM_PHASE + " " + diff_par + " " + ATMCOR_UNW + " 0 0 0 " 
-    os.system(call_str)
+    _run_or_raise(call_str, 'sub_phase_atmcor')
     call_str = 'rasrmg ' + ATMCOR_UNW + ' ' + Mamp + ' ' + nWidth + ' - - - - - - - - - - ' 
-    os.system(call_str)
+    _run_or_raise(call_str, 'rasrmg_atmcor_unw')
     
     print("Correct atmospheric phase is done!")
-    sys.exit(1)
+    sys.exit(0)
 
 if __name__ == '__main__':
     main(sys.argv[:])

third_party/PyINT/pyint/atm_correction_gamma_all.py

@@ -92,7 +92,7 @@ def main(argv):
     else:
         ifgList=ifgList0[:,0]   
     
-    err_txt = scratchDir + '/' + projectName + '/unwrap_gamma_all.err'
+    err_txt = scratchDir + '/' + projectName + '/atm_correction_gamma_all.err'
     if os.path.isfile(err_txt): os.remove(err_txt)
     
     data_para = []
@@ -114,7 +114,7 @@ def main(argv):
     print("Correct atmospheric phase for project %s is done! " % projectName)
     ut.print_process_time(start_time, time.time())
     
-    sys.exit(1)
+    sys.exit(0)
     
 if __name__ == '__main__':
     main(sys.argv[:])    

third_party/PyINT/pyint/diff_gamma.py

@@ -23,6 +23,39 @@ def _run_or_raise(call_str, stage):
     return rc
 
 
+def _is_binary_all_zero(path, chunk_size=1024 * 1024):
+    if not os.path.isfile(path):
+        return False
+    with open(path, 'rb') as handle:
+        while True:
+            chunk = handle.read(chunk_size)
+            if not chunk:
+                return True
+            if any(chunk):
+                return False
+
+
+def _run_slc_diff_intf(
+    Mrslc,
+    Srslc,
+    MrslcPar,
+    SrslcPar,
+    OFF,
+    SIM_UNW,
+    DIFF_IFG,
+    rlks,
+    azlks,
+    spsflg,
+    azfflg,
+):
+    call_str = (
+        'SLC_diff_intf ' + Mrslc + ' ' + Srslc + ' ' + MrslcPar + ' ' + SrslcPar
+        + ' ' + OFF + ' ' + SIM_UNW + ' ' + DIFF_IFG + ' ' + rlks + ' ' + azlks
+        + ' ' + spsflg + ' ' + azfflg + ' - 1 1'
+    )
+    _run_or_raise(call_str, 'SLC_diff_intf')
+
+
 INTRODUCTION = '''
 -------------------------------------------------------------------  
        Generate differential interferogram image from SLC using GAMMA.
@@ -138,8 +171,44 @@ def main(argv):
     _run_or_raise(call_str, 'phase_sim_orb')
     
     DIFF_IFG = workDir + '/' +  Pair + '_' + rlks + 'rlks.diff'
-    call_str = 'SLC_diff_intf ' + Mrslc + ' ' + Srslc + ' ' + MrslcPar + ' ' + SrslcPar + ' ' + OFF + ' ' + SIM_UNW + ' ' + DIFF_IFG + ' ' + rlks + ' ' + azlks + ' ' + templateDict['Igram_Spsflg'] + ' ' + templateDict['Igram_Azfflg'] + ' - 1 1'
-    _run_or_raise(call_str, 'SLC_diff_intf')
+    _run_slc_diff_intf(
+        Mrslc,
+        Srslc,
+        MrslcPar,
+        SrslcPar,
+        OFF,
+        SIM_UNW,
+        DIFF_IFG,
+        rlks,
+        azlks,
+        templateDict['Igram_Spsflg'],
+        templateDict['Igram_Azfflg'],
+    )
+    if _is_binary_all_zero(DIFF_IFG):
+        if templateDict['Igram_Azfflg'] == '1':
+            print(
+                'SLC_diff_intf produced an all-zero interferogram with azimuth common-band '
+                'filtering enabled; retrying once with Igram_Azfflg=0.'
+            )
+            os.remove(DIFF_IFG)
+            _run_slc_diff_intf(
+                Mrslc,
+                Srslc,
+                MrslcPar,
+                SrslcPar,
+                OFF,
+                SIM_UNW,
+                DIFF_IFG,
+                rlks,
+                azlks,
+                templateDict['Igram_Spsflg'],
+                '0',
+            )
+        if _is_binary_all_zero(DIFF_IFG):
+            raise RuntimeError(
+                'SLC_diff_intf produced an invalid all-zero interferogram after one bounded '
+                'azimuth-filter fallback; no further automatic retries will be attempted: %s' % DIFF_IFG
+            )
     
     ##### filtering process & coherence estimation ###########
     DIFFFILT = workDir + '/' +  Pair + '_' + rlks + 'rlks.diff_filt'

third_party/PyINT/pyint/generate_rdc_dem.py

@@ -32,6 +32,26 @@ def _resolve_existing_master_date(slc_dir, requested_date):
     print('masterDate %s not found; using existing SLC date: %s' % (requested_date, resolved))
     return resolved
 
+
+def _run_or_raise(call_str, stage):
+    rc = os.system(call_str)
+    if rc != 0:
+        raise RuntimeError('%s failed with rc=%s: %s' % (stage, rc, call_str))
+    return rc
+
+
+def _run_or_warn(call_str, stage):
+    rc = os.system(call_str)
+    if rc != 0:
+        print('WARNING: %s returned rc=%s; continuing with subsequent GAMMA refinement: %s' % (stage, rc, call_str))
+    return rc
+
+
+def _remove_files(paths):
+    for path in paths:
+        if os.path.isfile(path):
+            os.remove(path)
+
 def cmdLineParse():
     parser = argparse.ArgumentParser(description='Generate radar-coordinates based DEM.',\
                                      formatter_class=argparse.RawTextHelpFormatter,\
@@ -78,38 +98,32 @@ def main(argv):
     azlks = templateDict['azimuth_looks']
 
     if not os.path.isdir(processDir):
-        call_str = 'mkdir ' + processDir
-        os.system(call_str)
+        os.makedirs(processDir)
         
     simDir = scratchDir + '/' + projectName + "/DEM" 
-    if not os.path.isdir(simDir):
-        call_str='mkdir ' + simDir  
-  
-       
     workDir = simDir
     
     if 'DEM' in templateDict: 
         dem = templateDict['DEM'] 
         if not os.path.isfile(dem):
             dem = DEMDir + '/' + projectName + '/' + projectName + '.dem' 
-            call_str = 'echo DEM= ' + dem + ' >> ' + templateFile
-            os.system(call_str)
+            with open(templateFile, 'a') as stream:
+                stream.write('DEM= ' + dem + '\n')
             templateDict['DEM'] = dem
     else: 
         dem = DEMDir + '/' + projectName + '/' + projectName + '.dem'
-        call_str = 'echo DEM = ' + dem + ' >> ' + templateFile
-        os.system(call_str)
+        with open(templateFile, 'a') as stream:
+            stream.write('DEM = ' + dem + '\n')
     
     demPar = dem + ".par"
     
     if not os.path.isfile(dem):
         call_str = 'makedem_pyint.py ' + projectName
-        os.system(call_str)
+        _run_or_raise(call_str, 'makedem_pyint')
     
 # Parameter setting for simPhase
     latovrSimphase = templateDict['dem_lat_ovr']
     lonovrSimphase = templateDict['dem_lon_ovr']
-    
     rposSimphase = templateDict['Simphase_rpos']   
     azposSimphase = templateDict['Simphase_azpos']  
     rwinSimphase = templateDict['Simphase_rwin'] 
@@ -154,12 +168,7 @@ def main(argv):
 
 ### remove DEM look up table if it existed for considering gamma overlapping
 
-    if os.path.isfile(UTMDEM):   
-        os.remove(UTMDEM)
-    if os.path.isfile(UTMDEMpar):   
-        os.remove(UTMDEMpar)
-    if os.path.isfile(UTM2RDC):   
-        os.remove(UTM2RDC)
+    _remove_files([UTMDEM, UTMDEMpar, UTM2RDC, SIMSARUTM, PIX, LSMAP])
 
     nWidthUTMDEM0 = ut.read_gamma_par(demPar, 'read', 'width')
     DateFormat = ut.read_gamma_par(demPar, 'read', 'data_format:')
@@ -174,42 +183,46 @@ def main(argv):
     
     if not os.path.isfile(tmp_dem):
         call_str = 'replace_values ' + dem + ' -32767 0 ' + tmp_dem + ' ' + nWidthUTMDEM0 + ' 2 ' + DF_type
-        os.system(call_str)
+        _run_or_raise(call_str, 'replace_values_dem_voids')
         call_str = 'cp ' + tmp_dem + ' ' + dem
-        os.system(call_str)
+        _run_or_raise(call_str, 'copy_dem_without_voids')
 
     call_str = "multi_look " + MslcImg + " " + MslcPar + " " + MamprlksImg + " " + MamprlksPar + " " + rlks + " " + azlks
-    os.system(call_str)
+    _run_or_raise(call_str, 'multi_look_master_for_dem')
 
-    call_str = 'gc_map1 ' + MamprlksPar + ' ' + '-' + ' ' + demPar + ' ' + dem + ' ' + UTMDEMpar + ' ' + UTMDEM + ' ' + UTM2RDC + ' ' + latovrSimphase + ' ' + lonovrSimphase + ' ' + SIMSARUTM + ' - - - - ' + PIX + ' ' + LSMAP + ' - 3 128' 
-    #call_str = 'gc_map2 ' + MamprlksPar + ' ' + demPar + ' ' + dem + ' ' + UTMDEMpar + ' ' + UTMDEM + ' ' + UTM2RDC + ' ' + latovrSimphase + ' ' + lonovrSimphase + ' ' + ' ' + LSMAP + ' - - - -  ' + SIMSARUTM + ' - - - ' + PIX   
-    os.system(call_str)
+    def run_gc_map1(stage, lat_ovr, lon_ovr):
+        call = 'gc_map1 ' + MamprlksPar + ' ' + '-' + ' ' + demPar + ' ' + dem + ' ' + UTMDEMpar + ' ' + UTMDEM + ' ' + UTM2RDC + ' ' + lat_ovr + ' ' + lon_ovr + ' ' + SIMSARUTM + ' - - - - ' + PIX + ' ' + LSMAP + ' - 3 128'
+        _run_or_raise(call, stage)
+
+    run_gc_map1('gc_map1_initial_dem_segment', latovrSimphase, lonovrSimphase)
 
     nWidthUTMDEM = ut.read_gamma_par(UTMDEMpar, 'read', 'width')
     nLinePWR1 = ut.read_gamma_par(MamprlksPar, 'read', 'azimuth_lines')
     nWidth = ut.read_gamma_par(MamprlksPar, 'read', 'range_samples')
    
-    call_str = 'geocode ' + UTM2RDC + ' ' + SIMSARUTM + ' ' + nWidthUTMDEM + ' ' + SIMSARRDC + ' ' + nWidth + ' ' + nLinePWR1 + ' 0 0'
-    os.system(call_str)
+    # 30 m DEM grids can be much sparser than LT-1 multi-look radar pixels.
+    # Keep this in GAMMA by widening geocode's search radius for RDC filling.
+    call_str = 'geocode ' + UTM2RDC + ' ' + SIMSARUTM + ' ' + nWidthUTMDEM + ' ' + SIMSARRDC + ' ' + nWidth + ' ' + nLinePWR1 + ' 0 0 - - 2 64 1'
+    _run_or_raise(call_str, 'geocode_sim_sar_to_rdc')
 
     call_str = 'create_diff_par ' + MamprlksPar + ' ' + MamprlksPar + ' ' + SIMDIFFpar + ' 1 < ' + BLANK
-    os.system(call_str)
+    _run_or_raise(call_str, 'create_diff_par_sim')
 
     call_str = 'init_offsetm ' + SIMSARRDC + ' ' + MamprlksImg + ' ' + SIMDIFFpar + ' 2 2 ' + rposSimphase + ' ' + azposSimphase #+ ' - - - 512'
-    os.system(call_str)
+    _run_or_warn(call_str, 'init_offsetm_sim')
 
     call_str = 'offset_pwrm ' + SIMSARRDC + ' ' + MamprlksImg + ' ' + SIMDIFFpar + ' ' + SIMOFFS + ' ' + SIMSNR + ' ' + rwinSimphase + ' ' + azwinSimphase + ' ' + SIMOFFSET #+ ' - 128 128 ' + threshSimphase 
-    os.system(call_str)
+    _run_or_raise(call_str, 'offset_pwrm_sim')
 
     call_str = 'offset_fitm ' + SIMOFFS + ' ' + SIMSNR + ' ' + SIMDIFFpar + ' ' + SIMCOFF + ' ' + SIMCOFFSETS + ' - > ' + OFFSTD
-    os.system(call_str)
+    _run_or_raise(call_str, 'offset_fitm_sim')
 
     call_str = 'gc_map_fine ' + UTM2RDC + ' ' + nWidthUTMDEM + ' ' + SIMDIFFpar + ' ' + UTMTORDC + ' 1'
     #print(call_str)
-    os.system(call_str)
+    _run_or_raise(call_str, 'gc_map_fine')
 
-    call_str = 'geocode ' + UTMTORDC + ' ' + UTMDEM + ' ' + nWidthUTMDEM + ' ' + HGTSIM + ' ' + nWidth + ' ' + nLinePWR1 + ' 0 0 - - 1 1 1'
-    os.system(call_str)
+    call_str = 'geocode ' + UTMTORDC + ' ' + UTMDEM + ' ' + nWidthUTMDEM + ' ' + HGTSIM + ' ' + nWidth + ' ' + nLinePWR1 + ' 0 0 - - 2 64 1'
+    _run_or_raise(call_str, 'geocode_dem_to_rdc')
 
 
     required_outputs = [UTMDEMpar, UTMDEM, UTMTORDC, HGTSIM]

third_party/PyINT/pyint/geocode_gamma.py

@@ -8,21 +8,16 @@
 import os
 import sys  
 import argparse
-import numpy as np
 
 from pyint import _utils as ut
 
 
-def sanitize_gamma_float(filepath, valid_max=1e6):
-    """清理 GAMMA 浮点数据文件中的无效值 (NaN/Inf/极端值 → 0.0)"""
-    data = np.fromfile(filepath, dtype=np.float32)
-    bad_mask = ~np.isfinite(data) | (np.abs(data) > valid_max)
-    n_bad = int(np.sum(bad_mask))
-    if n_bad > 0:
-        data[bad_mask] = 0.0
-        data.tofile(filepath)
-        print(f'  [sanitize] {os.path.basename(filepath)}: '
-              f'清理 {n_bad} 个无效像素')
+def _run_or_raise(call_str, stage):
+    rc = os.system(call_str)
+    if rc != 0:
+        raise RuntimeError('%s failed with rc=%s: %s' % (stage, rc, call_str))
+    return rc
+
 
 def geocode(inFile, outFile, UTMTORDC, nWidth, nWidthUTMDEM, nLineUTMDEM, geo_interp='0'):
     
@@ -37,7 +32,7 @@ def geocode(inFile, outFile, UTMTORDC, nWidth, nWidthUTMDEM, nLineUTMDEM, geo_in
     else:
         call_str = 'geocode_back ' + inFile + ' ' + nWidth + ' ' + UTMTORDC + ' ' + outFile + ' ' + nWidthUTMDEM + ' ' + nLineUTMDEM+ ' ' + geo_interp + ' 1'
 
-    os.system(call_str)
+    _run_or_raise(call_str, 'geocode_back_' + os.path.basename(outFile))
     
     return
     
@@ -160,13 +155,10 @@ def geocode_pot(projectName, Pair, templateDict):
 
     if not os.path.isfile(geo_real):
         os.system(f'cpx_to_real {geo_disp} {geo_real} {eqa_width} 0')
-        sanitize_gamma_float(geo_real, disp_max_m)
     if not os.path.isfile(geo_imag):
         os.system(f'cpx_to_real {geo_disp} {geo_imag} {eqa_width} 1')
-        sanitize_gamma_float(geo_imag, disp_max_m)
     if not os.path.isfile(geo_mag):
         os.system(f'cpx_to_real {geo_disp} {geo_mag} {eqa_width} 3')
-        sanitize_gamma_float(geo_mag, disp_max_m)
 
     # ===== Step D: 地理编码 MLI 背景 =====
     geo_mli = workDir + '/geo_' + masterDate + '.mli'
@@ -288,10 +280,13 @@ def main(argv):
 
         # --- 基础产品地理编码 (hyp3/licsbas 均需) ---
         geo_interp = templateDict['geo_interp']
+        atmcor_use_for_disp = str(templateDict.get('atmcor_use_for_disp', '0')).strip() == '1'
         geocode(Mamp,    GeoMamp, UTMTORDC, nWidth, nWidthUTMDEM, nLineUTMDEM, geo_interp=geo_interp)
         geocode(CORIFG,  GeoCOR,  UTMTORDC, nWidth, nWidthUTMDEM, nLineUTMDEM, geo_interp=geo_interp)
         geocode(DIFFIFG, GeoDIFF, UTMTORDC, nWidth, nWidthUTMDEM, nLineUTMDEM, geo_interp=geo_interp)
         geocode(UNWIFG,  GeoUNW,  UTMTORDC, nWidth, nWidthUTMDEM, nLineUTMDEM, geo_interp=geo_interp)
+        if os.path.isfile(ATMCOR_UNW):
+            geocode(ATMCOR_UNW, GeoATMCOR_UNW, UTMTORDC, nWidth, nWidthUTMDEM, nLineUTMDEM, geo_interp=geo_interp)
         geocode(diffifg, geodiff, UTMTORDC, nWidth, nWidthUTMDEM, nLineUTMDEM, geo_interp=geo_interp)
         geocode(rdcdem,  Geodem,  UTMTORDC, nWidth, nWidthUTMDEM, nLineUTMDEM, geo_interp=geo_interp)
 
@@ -303,29 +298,31 @@ def main(argv):
         # --- hyp3 专属: dispmap (LOS/vert 位移场) ---
         if need_hyp3:
             print('  [hyp3] dispmap + geocode 位移场')
-            los_disp_rdc  = workDir + '/' + Pair + '_' + rlks + 'rlks.los_disp'
-            vert_disp_rdc = workDir + '/' + Pair + '_' + rlks + 'rlks.vert_disp'
+            disp_unw_source = ATMCOR_UNW if atmcor_use_for_disp and os.path.isfile(ATMCOR_UNW) else UNWIFG
+            disp_tag = '.atmcor' if disp_unw_source == ATMCOR_UNW else ''
+            los_disp_rdc  = workDir + '/' + Pair + '_' + rlks + 'rlks' + disp_tag + '.los_disp'
+            vert_disp_rdc = workDir + '/' + Pair + '_' + rlks + 'rlks' + disp_tag + '.vert_disp'
 
-            if os.path.isfile(UNWIFG) and os.path.isfile(SLCpar) and os.path.isfile(OFFpar):
+            if os.path.isfile(disp_unw_source) and os.path.isfile(SLCpar) and os.path.isfile(OFFpar):
                 hgt_arg = rdcdem if os.path.isfile(rdcdem) else '-'
                 if not os.path.isfile(los_disp_rdc):
-                    os.system(f'dispmap {UNWIFG} {hgt_arg} {SLCpar} {OFFpar} {los_disp_rdc} 0')
+                    _run_or_raise(f'dispmap {disp_unw_source} {hgt_arg} {SLCpar} {OFFpar} {los_disp_rdc} 0', 'dispmap_los')
                 if not os.path.isfile(vert_disp_rdc):
-                    os.system(f'dispmap {UNWIFG} {hgt_arg} {SLCpar} {OFFpar} {vert_disp_rdc} 1')
+                    _run_or_raise(f'dispmap {disp_unw_source} {hgt_arg} {SLCpar} {OFFpar} {vert_disp_rdc} 1', 'dispmap_vertical')
 
-            geo_los  = workDir + '/geo_' + Pair + '_' + rlks + 'rlks.los_disp'
-            geo_vert = workDir + '/geo_' + Pair + '_' + rlks + 'rlks.vert_disp'
+            geo_los  = workDir + '/geo_' + Pair + '_' + rlks + 'rlks' + disp_tag + '.los_disp'
+            geo_vert = workDir + '/geo_' + Pair + '_' + rlks + 'rlks' + disp_tag + '.vert_disp'
             if os.path.isfile(los_disp_rdc) and not os.path.isfile(geo_los):
-                os.system(f'geocode_back {los_disp_rdc} {nWidth} {UTMTORDC} {geo_los} {nWidthUTMDEM} {nLineUTMDEM} 1 0')
+                _run_or_raise(f'geocode_back {los_disp_rdc} {nWidth} {UTMTORDC} {geo_los} {nWidthUTMDEM} {nLineUTMDEM} {geo_interp} 0', 'geocode_back_los_disp')
             if os.path.isfile(vert_disp_rdc) and not os.path.isfile(geo_vert):
-                os.system(f'geocode_back {vert_disp_rdc} {nWidth} {UTMTORDC} {geo_vert} {nWidthUTMDEM} {nLineUTMDEM} 1 0')
+                _run_or_raise(f'geocode_back {vert_disp_rdc} {nWidth} {UTMTORDC} {geo_vert} {nWidthUTMDEM} {nLineUTMDEM} {geo_interp} 0', 'geocode_back_vert_disp')
 
         # --- hyp3 专属: 缠绕相位 ---
         if need_hyp3:
             print('  [hyp3] 提取缠绕相位')
             geo_wrapped_pha = workDir + '/geo_' + Pair + '_' + rlks + 'rlks.diff_filt.pha'
             if os.path.isfile(GeoDIFF) and not os.path.isfile(geo_wrapped_pha):
-                os.system(f'cpx_to_real {GeoDIFF} {geo_wrapped_pha} {nWidthUTMDEM} 4')
+                _run_or_raise(f'cpx_to_real {GeoDIFF} {geo_wrapped_pha} {nWidthUTMDEM} 4', 'cpx_to_real_wrapped_phase')
 
         # --- hyp3/licsbas 共需: look_vector ---
         if need_hyp3 or need_licsbas:
@@ -334,7 +331,7 @@ def main(argv):
             lv_phi   = workDir + '/lv_phi'
             if not os.path.isfile(lv_theta) or not os.path.isfile(lv_phi):
                 if os.path.isfile(SLCpar) and os.path.isfile(OFFpar) and os.path.isfile(UTMDEMpar0) and os.path.isfile(UTMDEM):
-                    os.system(f'look_vector {SLCpar} {OFFpar} {UTMDEMpar0} {UTMDEM} {lv_theta} {lv_phi}')
+                    _run_or_raise(f'look_vector {SLCpar} {OFFpar} {UTMDEMpar0} {UTMDEM} {lv_theta} {lv_phi}', 'look_vector')
 
         # --- BMP 可视化 ---
         os.system('rasmph_pwr ' + GeoDIFF + ' ' + GeoMamp + ' ' + nWidthUTMDEM + ' - - - - ')

third_party/PyINT/pyint/makedem_pyint.py

@@ -114,7 +114,6 @@ def _build_dem_from_existing_source(
 
     print(f"Using prepared DEM source: {source_dem}")
     print(f"Clipping prepared DEM window: west={west}, south={south}, east={east}, north={north}")
-
     _run_checked(
         [
             "gdal_translate",
@@ -130,6 +129,7 @@ def _build_dem_from_existing_source(
         ],
         cwd=str(work_dir),
     )
+
     _run_checked(
         [
             "makedem.py",

third_party/PyINT/pyint/pyint.template

@@ -193,6 +193,10 @@ diff_all_parallel    =     4     # Number of parallel processors
 unwrap_all           =     1     # Unwrap interferograms [0: skip; 1: process]
 unwrap_all_parallel  =     4     # Number of parallel processors
 
+atmcor_all           =     0     # Gamma atmospheric phase correction [0: skip; 1: process]
+atmcor_all_parallel  =     1     # Number of parallel processors
+atmcor_use_for_disp  =     0     # Use atmcor unwrapped phase for dispmap [0: no; 1: yes]
+
 geocode_all          =     1     # Geocode products [0: skip; 1: process]
 geocode_all_parallel =     4     # Number of parallel processors
 

third_party/PyINT/pyint/unwrap_gamma.py

@@ -108,7 +108,6 @@ def main(argv):
     CORMASK = workDir + '/' + Pair + '_' +rlks + 'rlks.diff_filt.cor'
     WRAPlks = workDir + '/' + Pair + '_' +rlks + 'rlks.diff_filt'
     UNWlks = workDir + '/' + Pair + '_' +rlks + 'rlks.diff_filt.unw'
-    
     CORMASKbmp = CORMASK.replace('.diff_filt.cor','.diff_filt.cor_mask.bmp')
     
     if os.path.isfile(CORMASKbmp):