Transformers
Abstract Class
- class Transformer[source]
These classes can be used to compose functions applied to a radiance for use in a MeasurementVectorElement.
Altitude Normalizations
- class AltitudeNormalization(norm_alts: Tuple[float, float], nan_above=False, couple_altitudes: bool = True)[source]
Apply an altitude normalization
- Parameters:
norm_alts (Tuple[float, float]) – Tuple consisting of low and high altitude limits of the normalization range.
nan_above (bool) – Make values above the altitude normalization range NaN. Default False
couple_altitude (bool) – Account for altitude coupling in the Jacobian. Default True
Examples
>>> from ali.retrieval.measvec.transformer import AltitudeNormalization >>> from ali.retrieval.measvec import MeasurementVectorElement >>> alt_norm = AltitudeNormalization((35000.0, 40000.0)) >>> meas_vec_el = MeasurementVectorElement() >>> meas_vec_el.add_transform(alt_norm)
- class AltitudeNormalizationShift(norm_alts: Tuple[float, float], nan_above=False, couple_altitudes: bool = True)[source]
Apply an altitude normalization that shifts the measurements rather than using a division. This can be useful for cases when
- Parameters:
norm_alts (Tuple[float, float]) – Tuple consisting of low and high altitude limits of the normalization range.
Wavelength Normalizations
Spectral Ratio
- class SpectralRatio(wavel_1: float, wavel_2: float)[source]
Spectral ratio at two wavelengths.
- Parameters:
wavel_1 (float) – Wavelength of numerator.
wavel_2 (float) – Wavelength of numerator.
Frame Ratio
- class FrameRatio(index_1: int = 0, index_2: int = 1)[source]
Data Selection
- class WavelengthSelect(wavelength: float, method='nearest')[source]
Select a single wavelength
- class FrameSelect(index=0)[source]
Additional Transforms
Measurement Combinations
- class LinearCombination(weights: Dict[int, float])[source]
Compute a linear combination of radiances. l1_data is expected to be a List[RadianceBase]. Often useful for computing polarization states.
\[y = \sum_{i=0}^{N} l1[key_i] * weight_i\]- Parameters:
weights (Dict[int, float]) – Dictionary in the form {frame_index: weight, …}
Smoothing
- class SplineSmoothing(smoothing=200)[source]
Derivatives
- class VerticalDerivative(smoothing=200)[source]
Log Space
- class LogRadiance[source]