Update README.md

README.md

@@ -1,9 +1,11 @@
 # sem_io
 
-Provides some helper functions to extract and view parameters stored in the header of SEM images (.tif) recorded using the software Zeiss SmartSEM V06.
+Provides some helper functions to extract and view parameters stored in the header of SEM images (.tif) recorded using either Zeiss SmartSEM or Thermo Fisher Scientific xT software.
 
 This is a single Python module and can either be installed or easily incorporated into other projects (the license must be retained in this case).
 
+<BR>
+
 ### Installation
 
 Please clone/download the repository and install with pip
@@ -13,6 +15,9 @@ cd sem_io
 pip install .
 ```
 
+<BR>
+
+
 ### Usage
 
 *Command line*
@@ -23,6 +28,9 @@ To print an overview of parameters from the image header in the console, at the
 sem_io path_to_my_image.tif
 ```
 
+<BR>
+
+
 *Python*
 
 You can also import the module and use the functions directly in Python.
@@ -31,28 +39,63 @@ You can also import the module and use the functions directly in Python.
 >>> import sem_io
 ```
 
+<BR>
+
 To print an overview of parameters from the image header in the console:
 
 ```python
 >>> my_params = sem_io.SEMparams("path_to_my_image.tif")
 ```
 
+<BR>
+
+
 If you just want to collect and store the parameters and not print them, you can do:
 
 ```python
 >>> my_params = sem_io.SEMparams("path_to_my_image.tif", verbose=False)
 ```
 
-Then, to extract a particular parameter, you can then do:
+<BR>
+
+
+You can print ALL the header parameters to the console like this:
+
+```python
+>>> my_params.print_param_dict(my_params.params)
+```
+
+<BR>
+
+
+You can print A SELECTION OF the header parameters (given in the class definition) to the console like this:
 
 ```python
->>> my_params.get_parameter("Aperture Size")
-(120.0, 'µm')
->>> my_params.get_parameter("Date")
-'25 Nov 2020'
+>>> my_params.print_param_dict(my_params.params_grouped)
 ```
 
-Parameters with a value and a unit are returned as a 2-Tuple. Other parameters are returned as a string.
+<BR>
+
+
+Both my_params.params and my_params.params_groups are dictionaries and any parameter can be accessed, e.g.
+
+```python
+>>> date = my_params.params_grouped["General"]["Date"]
+```
+
+<BR>
+
+
+Alternatively you can dump all the header parameters to a json file (optionally including a key giving the original image path) like this:
+
+```python
+>>> my_params.dump_params_to_json(my_params.params, "my_json_path.json", image_path=my_params.img_path)
+```
+
+
+<BR>
+
+### Getting the Image Pixel Size and Adding a Scalebar
 
 All the functions are staticmethods, so you don't need to instantiate the SEMparams class at all. For example, there is a bespoke function for getting the image pixel size and its unit in one line of code:
 
@@ -74,11 +117,16 @@ This is useful if you want to plot the SEM image using [matplotlib](https://matp
 >>> ax.add_artist(my_scalebar)
 ```
 
+*Even Electron Channeling Patterns acquired in rocking beam mode are correctly handled by sem_io.SEMparams.get_image_pixel_size()*
+
+<BR>
+
+
 ### Dependencies
 
 * [Pillow](https://python-pillow.org/)
 
 ### General
 
-* The parameters defined in SEMparams form a subset of those available in the header of the .tif image. If you are interested in other parameters, the program can be easily customised.
+* The selected parameters defined in the class definition of SEMparams form a subset of those available in the header of the .tif image. If you are interested in other parameters, the program can be easily customised - all the header parameters are extracted and are available as the "params" instance attribute.
 * If there are any issues, please feel free to get in touch using the [issues mechanism](https://github.com/tgwoodcock/sem_io/issues)