Add FuxProfileEstimator to docs

gammapy · Nov 22, 2021 · 7fe3d56 · 7fe3d56
1 parent d342c5a
commit 7fe3d56
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Showing 4 changed files with 6 additions and 3 deletions.
diff --git a/docs/estimators/index.rst b/docs/estimators/index.rst
@@ -204,6 +204,7 @@ Gammapy tutorial notebooks that show examples using ``gammapy.estimators``:
    ../tutorials/analysis/2D/detect.ipynb
    ../tutorials/analysis/1D/spectral_analysis.ipynb
    ../tutorials/analysis/3D/analysis_3d.ipynb
+   ../tutorials/analysis/3D/flux_profiles.ipynb
 
 
 Reference/API

diff --git a/examples/models/spectral/plot_template_spectral.py b/examples/models/spectral/plot_template_spectral.py
@@ -23,6 +23,7 @@
 import numpy as np
 from astropy import units as u
 import matplotlib.pyplot as plt
+
 # %%
 # Spectral correction
 # Corrections to templates can be applied by multiplication with a normalized spectral model,

diff --git a/gammapy/estimators/__init__.py b/gammapy/estimators/__init__.py
@@ -14,15 +14,15 @@
         ASmoothMapEstimator,
         LightCurveEstimator,
         SensitivityEstimator,
-        ImageProfileEstimator,
+        FluxProfileEstimator,
     ]
 )
 """Registry of estimator classes in Gammapy."""
 
 __all__ = [
     "ESTIMATOR_REGISTRY",
     "FluxPoints",
-    "ImageProfile",
+    "FluxMaps",
     "Estimator",
 ]
 __all__.extend(cls.__name__ for cls in ESTIMATOR_REGISTRY)
diff --git a/gammapy/modeling/fit.py b/gammapy/modeling/fit.py
@@ -529,6 +529,7 @@ class CovarianceResult(FitStepResult):
 
 class OptimizeResult(FitStepResult):
     """Optimize result object."""
+
     def __init__(self, parameters, nfev, total_stat, trace, **kwargs):
         self._parameters = parameters
         self._nfev = nfev
@@ -573,6 +574,7 @@ class FitResult:
     covariance_result : `CovarianceResult`
         Result of the covariance step.
     """
+
     def __init__(self, optimize_result=None, covariance_result=None):
         self._optimize_result = optimize_result
         self._covariance_result = covariance_result
@@ -644,4 +646,3 @@ def __repr__(self):
             str_ += str(self.covariance_result)
 
         return str_
-