lineshape¶
Module: skretrieval.core.lineshape
LineShape¶
-
class
LineShape¶ Base class for implementing line shapes. A line shape represents integration across a high resolution measurement down to a lower resolution measurement.
-
bounds()¶ Boundaries of the line shape. Values outside this range are 0
- Returns
Left and right boundaries of the line shape
- Return type
(left, right)
-
abstract
integration_weights(mean: float, available_samples: numpy.ndarray, normalize=True)¶ Integration weights for the line shape.
- Parameters
mean (float) – Value to integrate to
available_samples (np.ndarray) – Array of sample values that are available to use in the integration.
normalize (bool, Optional) – If true, resulting weights are normalized such that np.nansum(weights) = 1
- Returns
Integration weights, same size as available_samples.
- Return type
np.ndarray
-
Gaussian¶
-
class
Gaussian(fwhm: Optional[float] = None, stdev: Optional[float] = None, max_stdev=5, mode='linear')¶ -
bounds()¶ If integration_weights is called with mean=0, all values outside the range [lower_bound, upper_bound] are guaranteed to be 0.
- Returns
- Return type
[lower_bound, upper_bound]
-
integration_weights(mean: float, available_samples: numpy.ndarray, normalize=True)¶ The lineshape converts a function at high resolution, H, to one at low resolution, L.
L(mean) = np.dot(H, integration_weights(mean, available_samples))
- Parameters
mean (float) – value (in the range of available_samples) to integrate to
available_samples (np.ndarray) – Values that the high resolution function is available at
normalize (bool, optional) – If true, the returned weights will sum to 1
- Returns
Weights to use in the high resolution integration
- Return type
np.ndarray
-
DeltaFunction¶
-
class
DeltaFunction¶ -
bounds()¶ Boundaries of the line shape. Values outside this range are 0
- Returns
Left and right boundaries of the line shape
- Return type
(left, right)
-
integration_weights(mean: float, available_samples: numpy.ndarray, normalize=True, tolerance=1e-07)¶ Integration weights for the line shape.
- Parameters
mean (float) – Value to integrate to
available_samples (np.ndarray) – Array of sample values that are available to use in the integration.
normalize (bool, Optional) – If true, resulting weights are normalized such that np.nansum(weights) = 1
- Returns
Integration weights, same size as available_samples.
- Return type
np.ndarray
-
Rectangle¶
-
class
Rectangle(width, mode='linear')¶ -
bounds()¶ Boundaries of the line shape. Values outside this range are 0
- Returns
Left and right boundaries of the line shape
- Return type
(left, right)
-
integration_weights(mean: float, available_samples: numpy.ndarray, normalize=True)¶ Integration weights for the line shape.
- Parameters
mean (float) – Value to integrate to
available_samples (np.ndarray) – Array of sample values that are available to use in the integration.
normalize (bool, Optional) – If true, resulting weights are normalized such that np.nansum(weights) = 1
- Returns
Integration weights, same size as available_samples.
- Return type
np.ndarray
-