McStas API for creating and running McStas/McXtrace instruments from python scripting.
Prototype for an API that allow interaction with McStas through an interface like Jupyter Notebooks created under WP5 of PaNOSC.
Full documentation can be found here!
McStasScript does not include the McStas installation, so McStas/McXtrace should be installed separately, link to instructions here. McStasScript can be installed using pip from a terminal,
python3 -m pip install McStasScript --upgrade
After installation it is necessary to configure the package so the McStas/McXtrace installation can be found, here we show how the appropriate code for an Ubuntu system as an example. The configuration is saved permanently, and only needs to be updated when McStas or McStasScript is updated. This has to be done from a python terminal or from within a python environment.
import mcstasscript as ms
my_configurator = ms.Configurator()
my_configurator.set_mcrun_path("/usr/bin/")
my_configurator.set_mcstas_path("/usr/share/mcstas/2.5/")
my_configurator.set_mxrun_path("/usr/bin/")
my_configurator.set_mcxtrace_path("/usr/share/mcxtrace/1.5/")
To get a python terminal, run the command python in a terminal and then copy, paste and execute the lines above one at a time. Exit with ctrl+D.
For the second case,
- open a text editor (not MS Word but something like Gedit...),
- copy and paste the code above,
- save the file as a Python script, for example, myMcStasScript_config.py
- In a terminal, run it by typing python myMcStasScript_config.py
On a Mac OS X system, the paths to the mcrun executable and mcstas folder are through the application folder:
my_configurator.set_mcrun_path("/Applications/McStas-2.5.app/Contents/Resources/mcstas/2.5/bin/")
my_configurator.set_mcstas_path("/Applications/McStas-2.5.app/Contents/Resources/mcstas/2.5/")
my_configurator.set_mxrun_path("/Applications/McXtrace-1.5.app/Contents/Resources/mcxtrace/1.5/bin/")
my_configurator.set_mcxtrace_path("/Applications/McXtrace-1.5.app/Contents/Resources/mcxtrace/1.5/")
McStasScript was tested on Windows 10 installed using this guide, it is necessary to include MPI using MSMpiSetup.exe and msmpisdk.msi located in the extras folder.
Open the McStas-shell cmd (shortcut should be available on desktop) and install McStasScript / jupyter notebook with these commands:
python -m pip install notebook
python -m pip install McStasScript --upgrade
Using the McStas-shell one can start a jupyter notebook server with this command:
jupyter notebook
For a standard McStas installation on Windows, the appropriate configuration can be set with these commands in a notebook:
import mcstasscript as ms
my_configurator = ms.Configurator()
my_configurator.set_mcrun_path("\\mcstas-2.6\\bin\\")
my_configurator.set_mcstas_path("\\mcstas-2.6\\lib\\")
my_configurator.set_mxrun_path("\\mcxtrace-1.5\\bin\\")
my_configurator.set_mcxtrace_path("\\mcxtrace-1.5\\lib\\")
Double backslashes are necessary since backslash is the escape character in python strings.
This section provides a quick way to get started, a more in depth tutorial using Jupyter Notebooks is available in the tutorial folder. The following commands suppose that you are either typing them in a Python environment from a terminal or in a file to be run as the end of the editing by typing a command like, 'python my_file.py' or in a Jupyter notebook
Import the interface
import mcstasscript as ms
Now the package can be used. Start with creating a new instrument, just needs a name. For a McXtrace instrument use McXtrace_instr instead.
my_instrument = ms.McStas_instr("my_instrument_file")
Then McStas components can be added, here we add a source and ask for help on the parameters.
my_source = my_instrument.add_component("source", "Source_simple")
my_source.show_parameters() # Can be used to show available parameters for Source simple
The second line prints help on the Source_simple component and current status of our component object. The output is shown here, but without bold, underline and color which is used to show which parameters are required, default or user specified.
___ Help Source_simple _____________________________________________________________
|optional parameter|required parameter|default value|user specified value|
radius = 0.1 [m] // Radius of circle in (x,y,0) plane where neutrons are
generated.
yheight = 0.0 [m] // Height of rectangle in (x,y,0) plane where neutrons are
generated.
xwidth = 0.0 [m] // Width of rectangle in (x,y,0) plane where neutrons are
generated.
dist = 0.0 [m] // Distance to target along z axis.
focus_xw = 0.045 [m] // Width of target
focus_yh = 0.12 [m] // Height of target
E0 = 0.0 [meV] // Mean energy of neutrons.
dE = 0.0 [meV] // Energy half spread of neutrons (flat or gaussian sigma).
lambda0 = 0.0 [AA] // Mean wavelength of neutrons.
dlambda = 0.0 [AA] // Wavelength half spread of neutrons.
flux = 1.0 [1/(s*cm**2*st*energy unit)] // flux per energy unit, Angs or meV if
flux=0, the source emits 1 in 4*PI whole
space.
gauss = 0.0 [1] // Gaussian (1) or Flat (0) energy/wavelength distribution
target_index = 1 [1] // relative index of component to focus at, e.g. next is
+1 this is used to compute 'dist' automatically.
-------------------------------------------------------------------------------------
The parameters of the source can be adjusted directly as attributes of the python object
my_source.xwidth = 0.12
my_source.yheight = 0.12
my_source.lambda0 = 3
my_source.dlambda = 2.2
my_source.focus_xw = 0.05
my_source.focus_yh = 0.05
A monitor is added as well to get data out of the simulation (few bins so it is easy to print the results)
PSD = my_instrument.add_component("PSD", "PSD_monitor", AT=[0,0,1], RELATIVE="source")
PSD.xwidth = 0.1
PSD.yheight = 0.1
PSD.nx = 5
PSD.ny = 5
PSD.filename = '"PSD.dat"'
Settings for the simulation can be adjusted with the settings method, an output_path for the data is needed.
my_instrument.settings(output_path="first_run", ncount=1E7)
The simulatiuon is performed with the backengine method. This returns the data generated from the simulation.
data = my_instrument.backengine()
Results from the monitors would be stored as a list of McStasData objects in the returned data. The counts are stored as numpy arrays. We can read and change the intensity directly and manipulate the data before plotting.
data[0].Intensity
In a python terminal this would display the data directly:
array([[0. , 0. , 0. , 0. , 0. ],
[0. , 0.1422463 , 0.19018485, 0.14156196, 0. ],
[0. , 0.18930076, 0.25112956, 0.18897898, 0. ],
[0. , 0.14121589, 0.18952508, 0.14098576, 0. ],
[0. , 0. , 0. , 0. , 0. ]])
Plotting is usually done in a subplot of all monitors recorded.
plot = ms.make_sub_plot(data)
When using McStasScript in a jupyter notebook, it is possible to plot the data with a widget system instead. To do so, import the jupyter notebook widget interface and use show.
import mcstasscript.jb_interface as ms_widget
ms_widget.show(data)
There is also a widget solution for performing the simulation which works as an alternative to backengine, this method is also included in the jb_interface show command, just provide an instrument object instead of data. This interface includes setting parameters, simulation options and plotting of the resulting data.
ms_widget.show(instr)
If one wants to have access to the data generated in the widget, the widget needs to be created as an object with SimInterface. The resulting object will have a show_interface method to display the interface, and a get_data method to retrieve the latest generated dataset.
sim_widget = ms_widget.SimInterface(instr)
sim_widget.show_interface()
data = sim_widget.get_data()
If one wish to work on existing projects using McStasScript, there is a reader included that will read a McStas Instrument file and write the corresponding McStasScript python instrument to disk. Here is an example where the PSI_DMC.instr example is converted:
Reader = ms.McStas_file("PSI_DMC.instr")
Reader.write_python_file("PSI_DMC_generated.py")
It is highly advised to run a check between the output of the generated file and the original to ensure the process was sucessful.
Here is a quick overview of the available methods of the main classes in the project. Most have more options from keyword arguments that are explained in the manual, but also in python help. To get more information on for example the show_components method of the McStas_instr class, one can use the python help command help(instr.McStas_instr.show_components). Many methods take a reference to a component, that can either be a string with the component name or a component object, here written as Cref in type hint.
instr
└── McStas_instr(str instr_name) # Returns McStas instrument object on initialize
├── show_parameters() # Prints list of parameters
├── show_settings() # Prints current instrument settings
├── show_variables() # Prints list of declare variables and user vars
├── show_components() # Prints list of components and their location
├── show_instrument() # Shows instrument drawing with current parameters
├── show_instr_file() # Prints the current instrument file
├── show_diagram() # Show figure describing the instrument object
├── set_parameters() # Sets instrument parameters as keyword arguments
├── available_components(str category_name) # Show available components in given category
├── component_help(Cref component_name) # Prints component parameters for given component name
├── add_component(str name, str component_name) # Adds component to instrument and returns object
├── copy_component(str name, Cref original_name) # Copies a component to instrument and returns object
├── remove_component(Cref name) # Removes component
├── move_component(str name, Cref before / after, ) # Moves component to either before or after another
├── get_component(str name) # Gets component object
├── get_last_component() # Gets last component object
├── add_parameter(str name) # Adds instrument parameter with name
├── add_declare_var(str type, str name) # Adds declared variable with type and name
├── add_user_var(str type, str name) # Adds user var with type and name
├── append_declare(str string) # Appends a line to declare section (c syntax)
├── append_initialize(str string) # Appends a line to initialize (c syntax)
├── append_finally(str string) # Appends a line to finally (c syntax)
├── write_full_instrument() # Writes instrument to disk with given name + ".instr"
├── settings(kwargs) Settings as keyword arguments.
└── backengine() # Runs simulation.
component # returned by add_component
├── set_AT(list at_list) # Sets component position (list of x,y,z positions in [m])
├── set_ROTATED(list rotated_list) # Sets component rotation (list of x,y,z rotations in [deg])
├── set_RELATIVE(str component_name) # Sets relative to other component name
├── set_parameters(dict input) # Set parameters using dict input
├── set_comment(str string) # Set comment explaining something about the component
└── print_long() # Prints currently contained information on component
mcstasscript functions
├── name_search(str name, list McStasData) # Returns data set with given name from McStasData list
├── name_plot_options(str name, list McStasData, kwargs) # Sends kwargs to dataset with given name
├── load_data(str foldername) # Loads data from folder with McStas data as McStasData list
└── Configurator()
├── set_mcrun_path(str path) # sets mcrun path
├── set_mcstas_path(str path) # sets mcstas path
└── set_line_length(int length) # sets maximum line length
mcstasscript plotter
├── make_plot(list McStasData) # Plots each data set individually
├── make_sub_plot(list McStasData) # Plots data as subplot
└── interface(list McStasData) # Shows plotting interface in jupyter notebook
mcstasscript reader
└── McStas_file(str filename) # Returns a reader that can extract information from given instr file
InstrumentReader # returned by McStas_file
├── generate_python_file(str filename) # Writes python file with information contaiend in isntrument
└── add_to_instr(McStas_instr Instr) # Adds information from instrument to McStasScirpt instrument