Modified TSMap estimator arguments
@@ -90,6 +90,12 @@ class TSMapEstimator(Estimator):
Source model kernel. If set to None, assume point source model, PointSpatialModel.
kernel_width : `~astropy.coordinates.Angle`
Width of the kernel to use: the kernel will be truncated at this size
+ n_sigma : int
+ Number of sigma for flux error. Default is 1.
+ ul_method : ['covar', 'conf']
+ Upper limit estimation method.
+ n_sigma_ul : int
+ Number of sigma for flux upper limits. Default is 2.
downsampling_factor : int
Sample down the input maps to speed up the computation. Only integer
values that are a multiple of 2 are allowed. Note that the kernel is
@@ -108,12 +114,6 @@ class TSMapEstimator(Estimator):
analytically.
error_method : ['covar', 'conf']
Error estimation method.
- error_sigma : int (1)
- Sigma for flux error.
- ul_method : ['covar', 'conf']
- Upper limit estimation method.
- ul_sigma : int (2)
- Sigma for flux upper limits.
threshold : float (None)
If the TS value corresponding to the initial flux estimate is not above
this threshold, the optimizing step is omitted to save computing time.
@@ -148,9 +148,9 @@ class TSMapEstimator(Estimator):
downsampling_factor=None,
method="root brentq",
error_method="covar",
- error_sigma=1,
+ n_sigma=1,
ul_method="covar",
- ul_sigma=2,
+ n_sigma_ul=2,
threshold=None,
rtol=0.001,
):
@@ -174,9 +174,9 @@ class TSMapEstimator(Estimator):
self.parameters = {
"method": method,
"error_method": error_method,
- "error_sigma": error_sigma,
+ "n_sigma": n_sigma,
"ul_method": ul_method,
- "ul_sigma": ul_sigma,
+ "n_sigma_ul": n_sigma_ul,
"threshold": threshold,
"rtol": rtol,
}
@@ -397,9 +397,9 @@ class TSMapEstimator(Estimator):
method=p["method"],
error_method=error_method,
threshold=p["threshold"],
- error_sigma=p["error_sigma"],
+ error_sigma=p["n_sigma"],
ul_method=ul_method,
- ul_sigma=p["ul_sigma"],
+ ul_sigma=p["n_sigma_ul"],
rtol=p["rtol"],
)
