docs: fix the example of using DiffractionObject.get_array_index in the documentation

docs/source/examples/diffraction_objects_example.rst

@@ -180,7 +180,7 @@ For example, attempting to add a diffraction object and a string will raise an e
 
 .. code-block:: python
 
-    tth_ninety_index = diff_object1.get_array_index(90, xtype="tth")
+    tth_ninety_index = diff_object1.get_array_index(xvalue=90, xtype="tth")
     intensity_at_ninety = diff_object1.on_tth()[1][tth_ninety_index]
 
 If you do not specify an ``xtype``, it will default to the ``xtype`` used when creating the ``DiffractionObject``.
@@ -190,8 +190,8 @@ you can find its closest index for ``q=0.25`` by typing either of the following:
 .. code-block:: python
 
     print(do._input_xtype)     # remind ourselves which array was input.  prints "q" in this case.
-    index = do.get_array_index(0.25) # no xtype passed, defaults to do._input_xtype, or in this example, q
-    index = do.get_array_index(0.25, xtype="q") # explicitly choose an xtype to specify a value
+    index = do.get_array_index(xvalue=0.25) # no xtype passed, defaults to do._input_xtype, or in this example, q
+    index = do.get_array_index(xvalue=0.25, xtype="q") # explicitly choose an xtype to specify a value
 
 5. The ``dump`` function saves the diffraction data and relevant information to an xy format file with headers
 (widely used chi format used, for example, by Fit2D and diffpy.  These files can be read by ``LoadData()``

docs/source/examples/parsers_example.rst

@@ -104,8 +104,7 @@ Now we can extract specific data table columns from the dictionary.
 
      parsed_file_data = serialize_data('<PATH to data.txt>', hdata, data_table, serial_file='<PATH to serialfile.json>')
 
-   The returned value, ``parsed_file_data``, is the dictionary we just added to ``serialfile.json``.
-   To extract the data from the serial file, we use ``deserialize_data``.
+The returned value, ``parsed_file_data``, is the dictionary we just added to ``serialfile.json``. To extract the data from the serial file, we use ``deserialize_data``.
 
 .. code-block:: python
 

docs/source/examples/resample_example.rst

@@ -23,18 +23,6 @@ given enough datapoints.
 Each data table has two columns: first is the grid and second is the function value.
 To extract the columns, we can utilize the serialize function ...
 
-.. code-block:: python
-
-     from diffpy.utils.parsers.serialization import serialize_data
-     nickel_data = serialize_data('Nickel.gr', {}, nickel_datatable, dt_colnames=['grid', 'func'])
-     nickel_grid = nickel_data['Nickel.gr']['grid']
-     nickel_func = nickel_data['Nickel.gr']['func']
-     target_data = serialize_data('NiTarget.gr', {}, nitarget_datatable, dt_colnames=['grid', 'function'])
-     target_grid = nickel_data['Nickel.gr']['grid']
-     target_func = nickel_data['Nickel.gr']['func']
-
-To extract the columns, we can utilize the serialize function ...
-
 .. code-block:: python
 
      from diffpy.utils.parsers.serialization import serialize_data

news/fix-docs-example.rst

@@ -0,0 +1,23 @@
+**Added:**
+
+* No news added: Fix some examples in the documentation.
+
+**Changed:**
+
+* <news item>
+
+**Deprecated:**
+
+* <news item>
+
+**Removed:**
+
+* <news item>
+
+**Fixed:**
+
+* <news item>
+
+**Security:**
+
+* <news item>