Added new Basic Model Fitting Example and updated upcoming_changelod entry

Author: Angelus Vincent

examples/data_handling/energy_conversion.py

@@ -8,7 +8,7 @@
 """
 
 # %%
-# Load exemplementary data
+# Load examplary data
 import lumispy as lum
 import numpy as np
 

examples/data_handling/map_function.py

@@ -13,7 +13,7 @@
 import numpy as np
 
 # %%
-# Loading Exemplementary Data
+# Loading examplary Data
 # ---------------------------
 #
 # Choosing the spectrum at the navigation coordinates ``(15, 12)`` to see a spike

examples/data_handling/peak_analysis.py

@@ -10,7 +10,7 @@
 """
 
 # %%
-# Load exemplementary data
+# Load examplary data
 import lumispy as lum
 
 s = lum.data.asymmetric_peak_map()

examples/model_fitting/README.rst

@@ -0,0 +1,4 @@
+Model Fitting
+=============
+
+Gallery of Examples for model fitting in lumispy/hyperspy.

examples/model_fitting/basic_model_fitting.py

@@ -0,0 +1,58 @@
+"""
+Basic Model Fitting
+====================
+In this Example we will give a brief introduction to model fitting in Lumispy/Hyperspy.
+"""
+
+# %%
+# Load examplary data
+import hyperspy.api as hs
+import lumispy as lum
+
+s = lum.data.asymmetric_peak_map()
+
+# %%
+# First we need to initialize the model:
+m = s.create_model()
+
+# %%
+# A Hyperspy model can be composed of multiple components (functions).
+# To take a look at the components of the model we can use ``m.components``.
+m.components
+
+# %%
+# Since we dont hav any yet, we need to create some components and add them to the model.
+# Since we have an asymmetric peak, we will use a single SkewNormal component.
+# For successful Fit we need to pass the center wavelength ``x0=650nm`` [#f1]_.
+g1 = hs.model.components1D.SkewNormal(x0=650)
+# Alternative way to set the start value of x0:
+# g1.x0.value = 650
+m.append(g1)
+m.components
+
+# %%
+# To see the parameters of our components and their values, we can print all parameter values:
+m.print_current_values()
+
+# %%
+# To apply the fit, we can use the ``fit()`` function. In this case it will only be using the current index for fitting.
+# The fit for the other spectra will be the same. If you want to apply the fit to all spectra of the map, you can use ``multifit()`` instead.
+m.fit()
+
+# %%
+# We can now plot the model together with the data:
+m.plot()
+
+# %%
+# After we applied the fit, we can again print the fitted parameter at the current index:
+m.print_current_values()
+
+# %%
+# If we used ``multifit()``, we could aswell return the fitted parameter as Signal objects.
+m.multifit()
+g1.A.as_signal().plot(cmap="viridis")
+
+# %%
+# sphinx_gallery_thumbnail_number = 2
+#
+# .. [#f1] Note that Hyperspy has a range of built-in functions covering most needs that can be addedd as components to a model. However, it aslo has an intuitive mechanism to define custom functions.

upcoming_changes/253.new.rst

@@ -1 +1 @@
-Indexing, Map Function, Energy Conversion, ROI, Peak Analysis Example for the Gallery of Examples
+Indexing, Map Function, Energy Conversion, ROI, Peak Analysis, Basic Model Fitting Example for the Gallery of Examples