replace_nans¶

Overview¶

replace_nans replaces every NaN (IEEE-754 floating point Not-a-Number) value in an input array with a user-provided scalar. The function supports 1D–4D numeric NumPy arrays of any dtype; all inputs are coerced to float64 internally for consistent numerical behavior in the Rust layer.

Signature¶

replace_nans(arr, value)[source]¶

Replace all NaNs in arr with value.

Parameters:

arr (numpy.ndarray) – Input array (1D–4D supported).
value (float) – Replacement for every NaN.

Returns:

Array with NaNs replaced.

Return type:

numpy.ndarray

Parameters (Docstring Summary)¶

arr : numpy.ndarray Input array (1D, 2D, 3D, or 4D). Any numeric dtype is accepted.
value : float Scalar value to substitute for every NaN encountered.

Returns¶

numpy.ndarray (float64) with identical shape where all NaNs have been replaced by value.

Behavior & Notes¶

If the input contains no NaNs, the output is still a float64 copy (dtype coercion step).
Replacement is unconditional—original finite values are left untouched.
The operation is applied element-by-element in Rust (no Python loops).
Time or spatial semantics are not interpreted; dimensions are passed through unchanged.
Useful as a final cleanup step after masking operations that produced NaNs.

Example¶

import numpy as np
from eo_processor import replace_nans

arr = np.array([[np.nan, 1.2], [3.4, np.nan]], dtype=np.float32)
filled = replace_nans(arr, -9999.0)
# filled -> array([[-9999.,    1.2],
#                  [   3.4, -9999.]])

Interaction With Masking¶

When combining with masking utilities: 1. Apply a mask (e.g., mask_vals or mask_out_range). 2. Then call replace_nans to assign a sentinel value if downstream tools

cannot handle NaNs directly.