Module: sarpyx.sla.metrics
File: sarpyx/sla/metrics.py
Sub-look metrics. Example: from srp.sarpyx.sla.metrics import stack_metrics
Exported Symbols (__all__)
No explicit __all__ list. Public symbols inferred from implementation.
Public Functions (5)
enl function
Computes equivalent number of looks (ENL).
File location: sarpyx/sla/metrics.py:16
Signature
enl(x: np.ndarray, axis=None, eps: float=1e-12) -> np.ndarrayParameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
x | np.ndarray | yes | - | Intensity or complex samples. |
axis | inferred from implementation | no | None | Axis of looks. |
eps | float | no | 1e-12 | Small value to avoid division by zero. |
Return Type
np.ndarray
np.ndarray: ENL estimate.
Exceptions
None explicitly documented; inferred from implementation.
Side Effects
- inferred from implementation
Example Usage
from sarpyx.sla.metrics import enl
result = enl(x=<x>)Edge Cases
Includes optional parameters with implementation-defined fallback behavior.
dispersion_ratio function
Computes dispersion ratio (normalized variance).
File location: sarpyx/sla/metrics.py:33
Signature
dispersion_ratio(x: np.ndarray, axis=None, eps: float=1e-12) -> np.ndarrayParameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
x | np.ndarray | yes | - | Intensity or complex samples. |
axis | inferred from implementation | no | None | Axis of looks. |
eps | float | no | 1e-12 | Small value to avoid division by zero. |
Return Type
np.ndarray
np.ndarray: Dispersion ratio.
Exceptions
None explicitly documented; inferred from implementation.
Side Effects
- inferred from implementation
Example Usage
from sarpyx.sla.metrics import dispersion_ratio
result = dispersion_ratio(x=<x>)Edge Cases
Includes optional parameters with implementation-defined fallback behavior.
interlook_coherence function
Computes inter-look coherence between two complex looks.
File location: sarpyx/sla/metrics.py:50
Signature
interlook_coherence(a: np.ndarray, b: np.ndarray, axis=None, eps: float=1e-12) -> np.ndarrayParameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
a | np.ndarray | yes | - | First complex look. |
b | np.ndarray | yes | - | Second complex look. |
axis | inferred from implementation | no | None | Averaging axis. |
eps | float | no | 1e-12 | Small value to avoid division by zero. |
Return Type
np.ndarray
np.ndarray: Coherence magnitude in [0, 1].
Exceptions
None explicitly documented; inferred from implementation.
Side Effects
- inferred from implementation
Example Usage
from sarpyx.sla.metrics import interlook_coherence
result = interlook_coherence(a=<a>, b=<b>)Edge Cases
Includes optional parameters with implementation-defined fallback behavior.
phase_variance function
Computes circular phase variance.
File location: sarpyx/sla/metrics.py:67
Signature
phase_variance(x: np.ndarray, axis=None) -> np.ndarrayParameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
x | np.ndarray | yes | - | Complex samples. |
axis | inferred from implementation | no | None | Axis of looks. |
Return Type
np.ndarray
np.ndarray: Circular phase variance in [0, 1].
Exceptions
None explicitly documented; inferred from implementation.
Side Effects
- inferred from implementation
Example Usage
from sarpyx.sla.metrics import phase_variance
result = phase_variance(x=<x>)Edge Cases
Includes optional parameters with implementation-defined fallback behavior.
stack_metrics function
Computes all metrics from a sub-look stack.
File location: sarpyx/sla/metrics.py:81
Signature
stack_metrics(stack: np.ndarray, look_axis: int=0, pair=(0, 1), eps: float=1e-12)Parameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
stack | np.ndarray | yes | - | Complex sub-look stack. |
look_axis | int | no | 0 | Axis of looks. |
pair | inferred from implementation | no | (0, 1) | Look indices for coherence. |
eps | float | no | 1e-12 | Small value to avoid division by zero. |
Return Type
inferred from implementation
tuple[np.ndarray, np.ndarray, np.ndarray, np.ndarray]: ENL, coherence, dispersion ratio, phase variance.
Exceptions
None explicitly documented; inferred from implementation.
Side Effects
- inferred from implementation
Example Usage
from sarpyx.sla.metrics import stack_metrics
result = stack_metrics(stack=<stack>)Edge Cases
Includes optional parameters with implementation-defined fallback behavior.
Public Classes (0)
No public classes detected.