Extract SEG-Y ingestion logic into modular framework

src/mdio/ingestion/__init__.py

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+"""MDIO ingestion helpers."""

src/mdio/ingestion/coordinates.py

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+"""Generic coordinate population for ingestion."""
+
+from __future__ import annotations
+
+from typing import TYPE_CHECKING
+
+import numpy as np
+
+from mdio.segy.scalar import SCALE_COORDINATE_KEYS
+from mdio.segy.scalar import _apply_coordinate_scalar
+
+if TYPE_CHECKING:
+    from segy.arrays import HeaderArray as SegyHeaderArray
+    from xarray import Dataset as xr_Dataset
+
+    from mdio.core.grid import Grid
+
+
+def populate_dim_coordinates(
+    dataset: xr_Dataset, grid: Grid, drop_vars_delayed: list[str]
+) -> tuple[xr_Dataset, list[str]]:
+    """Populate the xarray dataset with dimension coordinate variables."""
+    for dim in grid.dims:
+        dataset[dim.name].values[:] = dim.coords
+        drop_vars_delayed.append(dim.name)
+    return dataset, drop_vars_delayed
+
+
+def populate_non_dim_coordinates(
+    dataset: xr_Dataset,
+    grid: Grid,
+    coordinates: dict[str, SegyHeaderArray],
+    drop_vars_delayed: list[str],
+    spatial_coordinate_scalar: int,
+) -> tuple[xr_Dataset, list[str]]:
+    """Populate the xarray dataset with coordinate variables.
+
+    Memory optimization: Processes coordinates one at a time and explicitly
+    releases intermediate arrays to reduce peak memory usage.
+    """
+    non_data_domain_dims = grid.dim_names[:-1]
+
+    coord_names = list(coordinates.keys())
+    for coord_name in coord_names:
+        coord_values = coordinates.pop(coord_name)
+        da_coord = dataset[coord_name]
+
+        coord_shape = da_coord.shape
+
+        fill_value = da_coord.encoding.get("_FillValue") or da_coord.encoding.get("fill_value")
+        if fill_value is None:
+            fill_value = np.nan
+        tmp_coord_values = np.full(coord_shape, fill_value, dtype=da_coord.dtype)
+
+        coord_axes = tuple(non_data_domain_dims.index(coord_dim) for coord_dim in da_coord.dims)
+        coord_slices = tuple(slice(None) if idx in coord_axes else 0 for idx in range(len(non_data_domain_dims)))
+
+        coord_trace_indices = np.asarray(grid.map[coord_slices])
+
+        not_null = coord_trace_indices != grid.map.fill_value
+
+        if not_null.any():
+            valid_indices = coord_trace_indices[not_null]
+            tmp_coord_values[not_null] = coord_values[valid_indices]
+
+        if coord_name in SCALE_COORDINATE_KEYS:
+            tmp_coord_values = _apply_coordinate_scalar(tmp_coord_values, spatial_coordinate_scalar)
+
+        dataset[coord_name][:] = tmp_coord_values
+        drop_vars_delayed.append(coord_name)
+
+        del tmp_coord_values, coord_trace_indices, not_null, coord_values
+
+        # TODO(Altay): Add verification of reduced coordinates being the same as the first
+        # https://github.com/TGSAI/mdio-python/issues/645
+
+    return dataset, drop_vars_delayed

src/mdio/ingestion/grid_qc.py

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+"""Grid sparsity quality control for ingestion."""
+
+from __future__ import annotations
+
+import logging
+from typing import TYPE_CHECKING
+
+import numpy as np
+
+from mdio.converters.exceptions import GridTraceSparsityError
+from mdio.core.config import MDIOSettings
+
+if TYPE_CHECKING:
+    from mdio.core.grid import Grid
+
+logger = logging.getLogger(__name__)
+
+
+def grid_density_qc(grid: Grid, num_traces: int) -> None:
+    """Quality control for sensible grid density during SEG-Y to MDIO conversion.
+
+    This function checks the density of the proposed grid by comparing the total possible traces
+    (`grid_traces`) to the actual number of traces in the SEG-Y file (`num_traces`). A warning is
+    logged if the sparsity ratio (`grid_traces / num_traces`) exceeds a configurable threshold,
+    indicating potential inefficiency or misconfiguration.
+
+    The warning threshold is set via the environment variable `MDIO__GRID__SPARSITY_RATIO_WARN`
+    (default 2), and the error threshold via `MDIO__GRID__SPARSITY_RATIO_LIMIT` (default 10). To
+    suppress the exception (but still log warnings), set `MDIO_IGNORE_CHECKS=1`.
+
+    Args:
+        grid: The Grid instance to check.
+        num_traces: Expected number of traces from the SEG-Y file.
+
+    Raises:
+        GridTraceSparsityError: If the sparsity ratio exceeds `MDIO__GRID__SPARSITY_RATIO_LIMIT`
+            and `MDIO_IGNORE_CHECKS` is not set to a truthy value (e.g., "1", "true").
+    """
+    settings = MDIOSettings()
+    grid_traces = np.prod(grid.shape[:-1], dtype=np.uint64)
+
+    sparsity_ratio = float("inf") if num_traces == 0 else grid_traces / num_traces
+
+    warning_ratio = settings.grid_sparsity_ratio_warn
+    error_ratio = settings.grid_sparsity_ratio_limit
+    ignore_checks = settings.ignore_checks
+
+    should_warn = sparsity_ratio > warning_ratio
+    should_error = sparsity_ratio > error_ratio and not ignore_checks
+
+    if not should_warn and not should_error:
+        return
+
+    dims = dict(zip(grid.dim_names, grid.shape, strict=True))
+    msg = (
+        f"Ingestion grid is sparse. Sparsity ratio: {sparsity_ratio:.2f}. "
+        f"Ingestion grid: {dims}. "
+        f"SEG-Y trace count: {num_traces}, grid trace count: {grid_traces}."
+    )
+    for dim_name in grid.dim_names:
+        dim_min = grid.get_min(dim_name)
+        dim_max = grid.get_max(dim_name)
+        msg += f"\n{dim_name} min: {dim_min} max: {dim_max}"
+
+    if should_warn:
+        logger.warning(msg)
+
+    if should_error:
+        raise GridTraceSparsityError(grid.shape, num_traces, msg)

src/mdio/ingestion/metadata.py

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+"""Generic dataset metadata helpers for ingestion."""
+
+from __future__ import annotations
+
+from typing import TYPE_CHECKING
+from typing import Any
+
+if TYPE_CHECKING:
+    from mdio.builder.schemas import Dataset
+
+
+def _add_grid_override_to_metadata(dataset: Dataset, grid_overrides: dict[str, Any] | None) -> None:
+    """Add grid override to Dataset metadata if needed."""
+    if dataset.metadata.attributes is None:
+        dataset.metadata.attributes = {}
+
+    if grid_overrides is not None:
+        dataset.metadata.attributes["gridOverrides"] = grid_overrides

src/mdio/ingestion/segy/__init__.py

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+"""SEG-Y specific ingestion helpers."""

src/mdio/ingestion/segy/coordinates.py

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+"""Coordinate extraction and unit resolution for SEG-Y ingestion."""
+
+from __future__ import annotations
+
+import logging
+from typing import TYPE_CHECKING
+
+import numpy as np
+from segy.standards.codes import MeasurementSystem as SegyMeasurementSystem
+from segy.standards.fields import binary as binary_header_fields
+
+from mdio.builder.schemas.v1.units import AngleUnitEnum
+from mdio.builder.schemas.v1.units import AngleUnitModel
+from mdio.builder.schemas.v1.units import LengthUnitEnum
+from mdio.builder.schemas.v1.units import LengthUnitModel
+from mdio.ingestion.coordinates import populate_dim_coordinates
+from mdio.ingestion.coordinates import populate_non_dim_coordinates
+
+if TYPE_CHECKING:
+    from segy.arrays import HeaderArray as SegyHeaderArray
+    from xarray import Dataset as xr_Dataset
+
+    from mdio.builder.templates.base import AbstractDatasetTemplate
+    from mdio.core.dimension import Dimension
+    from mdio.core.grid import Grid
+    from mdio.segy.file import SegyFileInfo
+
+logger = logging.getLogger(__name__)
+
+
+MEASUREMENT_SYSTEM_KEY = binary_header_fields.Rev0.MEASUREMENT_SYSTEM_CODE.model.name
+ANGLE_UNIT_KEYS = ["angle", "azimuth"]
+SPATIAL_UNIT_KEYS = [
+    "cdp_x",
+    "cdp_y",
+    "source_coord_x",
+    "source_coord_y",
+    "group_coord_x",
+    "group_coord_y",
+    "offset",
+]
+
+
+def _get_coordinates(
+    grid: Grid,
+    segy_headers: SegyHeaderArray,
+    mdio_template: AbstractDatasetTemplate,
+) -> tuple[list[Dimension], dict[str, SegyHeaderArray]]:
+    """Get the data dim and non-dim coordinates from the SEG-Y headers and MDIO template.
+
+    Select a subset of the segy_dimensions that corresponds to the MDIO dimensions
+    The dimensions are ordered as in the MDIO template.
+    The last dimension is always the vertical domain dimension
+
+    Args:
+        grid: Inferred MDIO grid for SEG-Y file.
+        segy_headers: Headers read in from SEG-Y file.
+        mdio_template: The MDIO template to use for the conversion.
+
+    Returns:
+        A tuple containing:
+            - A list of dimension coordinates (1-D arrays).
+            - A dict of non-dimension coordinates (str: N-D arrays).
+    """
+    dimensions_coords = [grid.select_dim(name) for name in mdio_template.dimension_names]
+    non_dim_coords = {name: np.array(segy_headers[name]) for name in mdio_template.coordinate_names}
+    return dimensions_coords, non_dim_coords
+
+
+def _populate_coordinates(
+    dataset: xr_Dataset,
+    grid: Grid,
+    coords: dict[str, SegyHeaderArray],
+    spatial_coordinate_scalar: int,
+) -> tuple[xr_Dataset, list[str]]:
+    """Populate dim and non-dim coordinates in the xarray dataset and write to Zarr.
+
+    This will write the xr Dataset with coords and dimensions, but empty traces and headers.
+
+    Args:
+        dataset: The xarray dataset to populate.
+        grid: The grid object containing the grid map.
+        coords: The non-dim coordinates to populate.
+        spatial_coordinate_scalar: The X/Y coordinate scalar from the SEG-Y file.
+
+    Returns:
+        Xarray dataset with filled coordinates and updated variables to drop after writing
+    """
+    drop_vars_delayed = []
+    dataset, drop_vars_delayed = populate_dim_coordinates(dataset, grid, drop_vars_delayed=drop_vars_delayed)
+
+    dataset, drop_vars_delayed = populate_non_dim_coordinates(
+        dataset,
+        grid,
+        coordinates=coords,
+        drop_vars_delayed=drop_vars_delayed,
+        spatial_coordinate_scalar=spatial_coordinate_scalar,
+    )
+
+    return dataset, drop_vars_delayed
+
+
+def _get_spatial_coordinate_unit(segy_file_info: SegyFileInfo) -> LengthUnitModel | None:
+    """Get the coordinate unit from the SEG-Y headers."""
+    measurement_system_code = int(segy_file_info.binary_header_dict[MEASUREMENT_SYSTEM_KEY])
+
+    if measurement_system_code not in {s.value for s in SegyMeasurementSystem}:
+        logger.warning(
+            "Unexpected value in coordinate unit (%s) header: %s. Can't extract coordinate unit and will "
+            "ingest without coordinate units.",
+            MEASUREMENT_SYSTEM_KEY,
+            measurement_system_code,
+        )
+        return None
+
+    if measurement_system_code == SegyMeasurementSystem.METERS:
+        unit = LengthUnitEnum.METER
+    if measurement_system_code == SegyMeasurementSystem.FEET:
+        unit = LengthUnitEnum.FOOT
+
+    return LengthUnitModel(length=unit)
+
+
+def _update_template_units(template: AbstractDatasetTemplate, unit: LengthUnitModel | None) -> AbstractDatasetTemplate:
+    """Update the template with dynamic and some pre-defined units."""
+    new_units = {key: AngleUnitModel(angle=AngleUnitEnum.DEGREES) for key in ANGLE_UNIT_KEYS}
+
+    if unit is None:
+        template.add_units(new_units)
+        return template
+
+    for key in SPATIAL_UNIT_KEYS:
+        current_value = template.get_unit_by_key(key)
+        if current_value is not None:
+            logger.warning("Unit for %s already in template. Will keep the original unit: %s", key, current_value)
+            continue
+
+        new_units[key] = unit
+
+    template.add_units(new_units)
+    return template

src/mdio/ingestion/segy/file_headers.py

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+"""Attach SEG-Y text and binary file headers to the dataset."""
+
+from __future__ import annotations
+
+import base64
+from typing import TYPE_CHECKING
+
+from mdio.core.config import MDIOSettings
+
+if TYPE_CHECKING:
+    from xarray import Dataset as xr_Dataset
+
+    from mdio.segy.file import SegyFileInfo
+
+
+def _add_segy_file_headers(xr_dataset: xr_Dataset, segy_file_info: SegyFileInfo) -> xr_Dataset:
+    """Attach the SEG-Y text and binary file headers as attrs on a scalar variable."""
+    settings = MDIOSettings()
+
+    if not settings.save_segy_file_header:
+        return xr_dataset
+
+    expected_rows = 40
+    expected_cols = 80
+
+    text_header_rows = segy_file_info.text_header.splitlines()
+    text_header_cols_bad = [len(row) != expected_cols for row in text_header_rows]
+
+    if len(text_header_rows) != expected_rows:
+        err = f"Invalid text header count: expected {expected_rows}, got {len(segy_file_info.text_header)}"
+        raise ValueError(err)
+
+    if any(text_header_cols_bad):
+        err = f"Invalid text header columns: expected {expected_cols} per line."
+        raise ValueError(err)
+
+    xr_dataset["segy_file_header"] = ((), "")
+    xr_dataset["segy_file_header"].attrs.update(
+        {
+            "textHeader": segy_file_info.text_header,
+            "binaryHeader": segy_file_info.binary_header_dict,
+        }
+    )
+    if settings.raw_headers:
+        raw_binary_base64 = base64.b64encode(segy_file_info.raw_binary_headers).decode("ascii")
+        xr_dataset["segy_file_header"].attrs.update({"rawBinaryHeader": raw_binary_base64})
+
+    return xr_dataset