pydsstools.core.gridinfo.transforms

Coordinate transformation and grid utility functions.

This module provides utilities for: - Converting between affine transforms and grid coordinates - Calculating grid extents - Checking grid spatial relationships - Validating grid consistency

Functions

`grid_extent`(gridinfo)	Calculate geographic extent of a grid.
`grids_overlap`(gridinfo1, gridinfo2[, tolerance])	Check if two grids overlap spatially.
`lower_left_cell_from_minxy`(minxy, shape, ...)	Calculate lower-left cell indices from minimum coordinates.
`lower_left_cell_from_transform`(transform, shape)	Calculate lower-left cell indices from affine transform.
`minxy_from_transform_shape`(transform, shape)	Calculate minimum (x, y) coordinates from affine transform and shape.
`validate_grid_consistency`(gridinfo)	Check grid metadata for common configuration errors.

pydsstools.core.gridinfo.transforms.minxy_from_transform_shape(transform, shape)[source]

Calculate minimum (x, y) coordinates from affine transform and shape.

Parameters:

transform (tuple) – 6-element affine transform: (dx, 0, xmin, 0, dy, ymax). dy is typically negative for north-up orientation.
shape (tuple[int, int]) – Grid dimensions as (rows, cols).

Returns:

Minimum (x, y) coordinates of grid extent.

Return type:

tuple[float, float]

Warning

Logs warning if cell sizes in x and y directions differ.

Examples

>>> transform = (1000, 0, 500000, 0, -1000, 4200000)
>>> shape = (200, 300)
>>> minxy = minxy_from_transform_shape(transform, shape)
>>> print(minxy)
(500000.0, 4000000.0)

Notes

The transform follows GDAL convention: - transform[0]: pixel width (dx) - transform[2]: x-coordinate of upper-left corner - transform[4]: pixel height (dy, negative for north-up) - transform[5]: y-coordinate of upper-left corner

pydsstools.core.gridinfo.transforms.lower_left_cell_from_minxy(minxy, shape, cellsize, xcoord_cell0=0, ycoord_cell0=0)[source]

Calculate lower-left cell indices from minimum coordinates.

Computes the cell indices for the lower-left grid cell based on minimum coordinates and projection origin.

Parameters:

minxy (tuple[float, float]) – Minimum (x, y) coordinates of grid extent.
shape (tuple[int, int]) – Grid dimensions as (rows, cols).
cellsize (float) – Cell size in projection units.
xcoord_cell0 (float, optional) – X-coordinate of projection origin (false easting), default 0.
ycoord_cell0 (float, optional) – Y-coordinate of projection origin (false northing), default 0.

Returns:

Lower-left cell indices as (x_cell, y_cell).

Return type:

tuple[int, int]

Examples

For SHG/Albers grid:

>>> minxy = (-1500000, 500000)  # In EPSG:5070 coordinates
>>> shape = (100, 150)
>>> cellsize = 2000.0
>>> llc = lower_left_cell_from_minxy(minxy, shape, cellsize, 0, 0)
>>> print(llc)
(-750, 250)

Notes

Used primarily for Albers/SHG grids where the projection origin (xcoord_cell0, ycoord_cell0) is typically (0, 0) and different from the grid’s actual spatial extent.

The calculation: - Converts coordinates to easting/northing relative to origin - Divides by cell size to get cell indices - Uses floor() to get integer cell indices

pydsstools.core.gridinfo.transforms.lower_left_cell_from_transform(transform, shape, xcoord_cell0=0, ycoord_cell0=0)[source]

Calculate lower-left cell indices from affine transform.

Parameters:

transform (tuple) – 6-element affine transform: (dx, 0, xmin, 0, dy, ymax).
shape (tuple[int, int]) – Grid dimensions as (rows, cols).
xcoord_cell0 (float, optional) – X-coordinate of projection origin (false easting), default 0.
ycoord_cell0 (float, optional) – Y-coordinate of projection origin (false northing), default 0.

Returns:

Lower-left cell indices as (x_cell, y_cell).

Return type:

tuple[int, int]

Warning

Logs warning if cell sizes in x and y directions differ.

Examples

>>> transform = (2000, 0, -1500000, 0, -2000, 700000)
>>> shape = (100, 150)
>>> llc = lower_left_cell_from_transform(transform, shape, 0, 0)
>>> print(llc)
(-750, 250)

See also

lower_left_cell_from_minxy: Calculate from coordinates
minxy_from_transform_shape: Extract min_xy from transform

References

pydsstools.core.gridinfo.transforms.grid_extent(gridinfo)[source]

Calculate geographic extent of a grid.

Parameters:: gridinfo (GridInfo or subclass) – Grid metadata object.
Returns:: Grid extent as (xmin, ymin, xmax, ymax) in projection coordinates.
Return type:: tuple[float, float, float, float]
Raises:: ValueError – If gridinfo.min_xy is None.

Examples

>>> from pydsstools.core.gridinfo import GridInfoCreate, GridType, DataType
>>> info = GridInfoCreate(
...     grid_type=GridType.specified,
...     data_type=DataType.inst_val,
...     shape=(200, 300),
...     cell_size=1000.0,
...     min_xy=(500000, 4000000),
...     crs="EPSG:32610",
...     nodata=-9999.0
... )
>>> extent = grid_extent(info)
>>> print(extent)
(500000.0, 4000000.0, 800000.0, 4200000.0)

See also

grids_overlap: Check if two grids overlap spatially

pydsstools.core.gridinfo.transforms.grids_overlap(gridinfo1, gridinfo2, tolerance=0.001)[source]

Check if two grids overlap spatially.

Parameters:

gridinfo1 (GridInfo or subclass) – First grid metadata object.
gridinfo2 (GridInfo or subclass) – Second grid metadata object.
tolerance (float, optional) – Tolerance for floating point comparison, default 0.001.

Returns:

True if grids overlap, False otherwise.

Return type:

bool

Raises:

ValueError – If either gridinfo has min_xy = None.

Examples

>>> from pydsstools.core.gridinfo import GridInfoCreate, GridType, DataType
>>> info1 = GridInfoCreate(
...     grid_type=GridType.undefined,
...     data_type=DataType.inst_val,
...     shape=(100, 100),
...     cell_size=1000.0,
...     min_xy=(0, 0)
... )
>>> info2 = GridInfoCreate(
...     grid_type=GridType.undefined,
...     data_type=DataType.inst_val,
...     shape=(100, 100),
...     cell_size=1000.0,
...     min_xy=(50000, 50000)
... )
>>> grids_overlap(info1, info2)
True

Notes

This function only checks spatial overlap based on extents. It does not check: - CRS compatibility - Cell size compatibility - Grid alignment

See also

grid_extent: Calculate grid extent

pydsstools.core.gridinfo.transforms.validate_grid_consistency(gridinfo)[source]

Check grid metadata for common configuration errors.

Validates: - Coordinate consistency (min_xy, coords_cell0, lower_left_cell) - Cell size reasonableness - Grid dimensions - CRS definition (for specified grids) - Statistics (min <= max, etc.)

Parameters:: gridinfo (GridInfo or subclass) – Grid metadata object to validate.
Returns:: List of validation issues found. Empty list if no issues.
Return type:: list[str]

Examples

>>> from pydsstools.core.gridinfo import GridInfoCreate, GridType, DataType
>>> info = GridInfoCreate(
...     grid_type=GridType.albers,
...     data_type=DataType.inst_val,
...     shape=(100, 150),
...     cell_size=2000.0,
...     min_xy=(-1500000, 500000)
... )
>>> issues = validate_grid_consistency(info)
>>> if issues:
...     for issue in issues:
...         print(f"Warning: {issue}")

Notes

This is a non-exhaustive validation. It catches common errors but may not detect all possible inconsistencies.

See also

grid_extent: Calculate grid extent for spatial validation