included Laurent's suggestions

src/toolbox_scs/detectors/hrixs.py

@@ -395,6 +395,10 @@ class hRIXS:
                        **kwargs):
         """find the curvature correction coefficients
 
+        The hRIXS has some abberations which leads to the spectroscopic lines
+        being curved on the detector. We approximate these abberations with
+        a parabola for later correction.
+
         Load a run and determine the curvature. The curvature is set in `self`,
         and returned as a pair of floats.
 
@@ -413,7 +417,7 @@ class hRIXS:
         Example
         -------
 
-           h.find_curvature(155)  # use run 155 to fit the curvature
+            h.find_curvature(155)  # use run 155 to fit the curvature
         """
         data = self.from_run(runNB, proposal)
 
@@ -431,9 +435,9 @@ class hRIXS:
     def centroid(self, data, bins=None):
         """calculate a spectrum by finding the centroid of individual photons
 
-        This takes the `xarray` `data` and returns a copy of it, with a new
-        dataarray named `spectrum` added, which contains the energy spectrum
-        calculated for each hRIXS image.
+        This takes the `xarray.Dataset` `data` and returns a copy of it, with
+        a new `xarray.DataArray` named `spectrum` added, which contains the
+        energy spectrum calculated for each hRIXS image.
 
         Example
         -------
@@ -481,6 +485,7 @@ class hRIXS:
 
         Example
         -------
+
             data = h.integrate(data)  # create spectrum by summing pixels
             data.spectrum[0, :].plot()  # plot the spectrum of the first image
         """
@@ -514,13 +519,14 @@ class hRIXS:
     def aggregate(self, ds, dim="trainId"):
         """aggregate (i.e. mostly sum) all data within one dataset
 
-        talk all images in a dataset and aggregate them and their metadata.
+        take all images in a dataset and aggregate them and their metadata.
         For images, spectra and normalizations that means adding them, for
         others (e.g. delays) adding would not make sense, so we treat them
         properly.
 
         Example
         -------
+
             data = h.centroid(data)  # create spectra from finding photons
             agg = h.aggregate(data)  # sum all spectra
             agg.spectrum.plot()  # plot the resulting spectrum