Metadata-Version: 2.1
Name: raypyng
Version: 0.0.9
Summary: Python interface for RAY-UI x-ray tracing program
Author-email: "Simone Vadilonga, Ruslan Ovsyannikov" <simone.vadilonga@helmholtz-berlin.de>
License: The MIT License (MIT)
        
        Copyright (c) <2022> <Simone Vadilonga, Ruslan Ovsyannikov>
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in
        all copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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Project-URL: Homepage, https://gitlab.helmholtz-berlin.de/RAY/raypyng
Project-URL: Bug Tracker, https://gitlab.helmholtz-berlin.de/RAY/raypyng/-/issues
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE

## Project Description
raypyng provides a simple API to work with RAY-UI, a software for optical simulation of synchrotron beamlines and x-ray systems developed by Helmholtz-Zentrum Berlin.

raypyng works only under linux distributions.


## Install RAY-UI

Download the RAY-UI installer from https://www.helmholtz-berlin.de/forschung/oe/wi/optik-strahlrohre/arbeitsgebiete/ray_en.html, and run the installer.


## Install xvfb 
xvfb is a virtual X11 framebuffer server that let you run RAY-UI headless

Install xvfb:
```
sudo apt install xvfb
```

Note: xvfb-run script is a part of the xvfb distribuion and runs an app on a new virtual X11 server

## Install raypyng
```
pip install raypyng
```

## Use raypyng
The documentation is still in production. At the moment a few examples are available at this link.

### Minimal example
raypyng is not able to create a beamline from scratch. To do so, use RAY-UI, create a beamline, and save it. What you save is `.rml` file, that you have to pass as an argumet to the `Simulate` simulate class. In the following example we use the file for a beamline called `elisa`, and the file is saved in `rml/elisa.rml`. The `hide` parameter can be set to true only if `xvfb` is installed.

```python
from raypyng import Simulate
rml_file = 'rml/elisa.rml'

sim = Simulate(rml_file, hide=True)
elisa = sim.rml.beamline
```
The elements of the beamline are now available as python objects, as well as their properties. If working in ipython, tab autocompletion is available. For instance to acess the source, a dipole in this case: 
```python 
# this is the dipole object
elisa.Dipole 
# to acess its parameter, for instance the photonFlux
elisa.Dipole.photonFlux
# to acess the value 
elisa.Dipole.photonFlux.cdata
# to modify the value
elisa.Dipole.photonFlux.cdata = 10
```
To perform simulation, any number of parameters can varied. 
For instance one can vary the photon energy of the source, and set a certain aperture of the exit slits:
```python
# define the values of the parameters to scan 
energy    = np.arange(200, 7201,250)
SlitSize  = np.array([0.1])

# define a list of dictionaries with the parameters to scan
params = [  
            {elisa.Dipole.photonEnergy:energy}, 
            {elisa.ExitSlit.totalHeight:SlitSize}
        ]

#and then plug them into the Simulation class
sim.params=params
```
It is also possible to define coupled parameters. If for instance one wants to increase the number of rays with the photon energy
```python
# define the values of the parameters to scan 
energy    = np.arange(200, 7201,250)
nrays     = energy*100
SlitSize  = np.array([0.1])

# define a list of dictionaries with the parameters to scan
params = [  
            {elisa.Dipole.photonEnergy:energy, elisa.Dipole.numberRays:nrays}, 
            {elisa.ExitSlit.totalHeight:SlitSize}
        ]

#and then plug them into the Simulation class
sim.params=params
```

The simulations files and the results will be saved in a folder called 'RAYPy_simulation_' + a name at your choce, that can be set. This folder will be saved, by default, in the folder where the program is executed, but it can be eventually be modified
```python
sim.simulation_folder = '/home/raypy/Documents/simulations'
sim.simulation_name = 'test'
```
This will create a simulation folder with the following path and name: `/home/raypy/Documents/simulations/RAYPy_simulation_test`.

Sometimes, instead of using millions of rays, it is more convenient to repeat the simulations and average the results
The we can set which parameters of which optical elements can be exported. The number of rounds of simulations can be set like this:
```python
# repeat the simulations as many time as needed
sim.repeat = 1
``` 
One can decide weather want RAY-UI or raypyng to do a prelimanary analysis of the results. 
To let RAY-UI analyze the results, one has to set:
```python
sim.analyze = True # let RAY-UI analyze the results
```
In this case the following exports are available:
```ipython
In [23]: sim.possible_exports
Out[23]: 
['AnglePhiDistribution',
 'AnglePsiDistribution',
 'BeamPropertiesPlotSnapshot',
 'EnergyDistribution',
 'FootprintAbsorbedRays',
 'FootprintAllRays',
 'FootprintOutgoingRays',
 'FootprintPlotSnapshot',
 'FootprintWastedRays',
 'IntensityPlotSnapshot',
 'IntensityX',
 'IntensityYZ',
 'PathlengthDistribution',
 'RawRaysBeam',
 'RawRaysIncoming',
 'RawRaysOutgoing',
 'ScalarBeamProperties',
 'ScalarElementProperties']
```
To let raypyng analyze the results set:
```python
sim.analyze = False # don't let RAY-UI analyze the results
sim.raypyng_analysis=True # let raypyng analyze the results
```
In this case only these exports are possible
```ipython
In [24]: sim.possible_exports_without_analysis
Out[24]: ['RawRaysIncoming', 'RawRaysOutgoing']
```
The exports are available for each optical element in the beamline, ImagePlanes included, and can be set like this:
```python
## This must be a list of dictionaries
sim.exports  =  [{elisa.Dipole:['ScalarElementProperties']},
                {elisa.DetectorAtFocus:['ScalarBeamProperties']}
                ]
```

Finally the simulations can be run using
```python
sim.run(multiprocessing=5, force=True)
```
where the `multiprocessing` parameter can be set either to False or to an int, corresponding to the number of parallel instances of RAY-UI to be used. Generally speaking the number of instances of RAY-UI must be lower than the number of cores available. If simulation using many rays, monitor the RAM usage of your computer. If the computation uses all the possible RAM of the computer the program may get blocked or not execute correctly.

### Exports

#### Analysis perfomed by RAY-UI 
If you decided to let RAY-UI doing the analysis, you should expect the following files to be saved in your simulation folder:
- one file for each parameter you set with the values that you passed to the program. If for instance you input the Dipole numberRays, you will find a file called `input_param_Dipole_numberRays.dat`
- one folder called `round_n` for each repetition of the simulations. For instance if you set `sim.repeat=2` you will have two folders `round_0` and `round_1`
- inside each `round_n` folder you will find the beamline files modified with the parameters you set in `sim.params`, these are the `.rml` files, that can be opened by RAY-UI.
- inside each `round_n` folder you will find your exported files, one for each simulation. If for instance you exported the `ScalarElementProperties` of the Dipole, you will have a list of files `0_Dipole-ScalarElementProperties.csv`

#### Analysis perfomed by raypyng
If you decided to let raypyng doing the analysis, you should expect the following files to be saved in your simulation folder:
- one file for each parameter you set with the values that you passed to the program. If for instance you input the Dipole numberRays, you will find a file called `input_param_Dipole_numberRays.dat`
- one folder called `round_n` for each repetition of the simulations. For instance if you set `sim.repeat=2` you will have two folders `round_0` and `round_1`
- inside each `round_n` folder you will find the beamline files modified with the parameters you set in `sim.params`, these are the `.rml` files, that can be opened by RAY-UI.
- inside each `round_n` folder you will find your exported files, one for each simulation. If for instance you exported the `RawRaysOutgoing` of the Dipole, you will have a list of files `0_Dipole-RawRaysOutgoing.csv`
- for each `RawRaysOutgoing` file, raypyng calculates some properties, and saves a corresponding file, for instance `0_Dipole_analyzed_rays.dat`. Each of these files contains the followin informations:
  - SourcePhotonFlux
  - NumberRaysSurvived		 
  - PercentageRaysSurvived   
  - PhotonFlux				
  - Bandwidth				 
  - HorizontalFocusFWHM	  
  - VerticalFocusFWHM
- In the simulation folder, all the for each exported element is united (and in case of more rounds of simulations averaged) in one single file. For the dipole the fill is called `Dipole.dat`
  
## Recipees
Documentation still not available, see the examples.

## List of examples avalable and short expalanation
In the example folder, the following examples are available:
- `example_simulation_analyze.py` : simulate a beamline, let Ray-UI do the analysis
- `example_simulation_noanalyze.py` simulate a beamline, let Ray-UI do the analysis
- `example_eval_noanalyze_and_analyze.py` plot the results of the two previous simulations
- `example_simulation_Flux.py` simulations using the flux recipee, useful if you intent is to simulate the flux of your beamline
- `example_simulation_RP.py`simulations using the resolving power (RP) recipee, useful if you intent is to simulate the RP of your beamline. The reflectivity of every optical element is switched to 100% and not calculated using the substrate and coiating(s) material(s). The information about the Flux of the beamline are therefore not reliable.
- `example_beamwaist.py`: raypyng is able to plot the beamwaist of the x-rays across your beamline. It performs simulations using the beamwaist recipee, and it exports the raw raysoutgoing from each optical element. It then uses a simple geometrical x-ray tracer to propagate each ray until the next optical element, and plots the results (both top view and side view). This is still experimental and it may fail.   
