Powder diffraction exercise

import mcstasscript as ms
import make_powder_instrument
from mcstasutils import plot
import quizlib

quiz = quizlib.Powder_Quiz()

Powder diffraction exercise#

In this notebook you will work with a McStas model of a simplified powder diffraction instrument. You will have to answer questions in the notebook by working with this model, both by running simulations and expanding the model. We will use the Python McStas API McStasScript to work with the instrument, you can find documentation here.

Get the instrument object#

First we need the McStas instrument object. Here it is retrieved from a local python function that generates it.

instrument = make_powder_instrument.make()

Investigate instrument#

The first task is to investigate the instrument object instrument using some of the available methods available on that object. Each method that show something about the instrument starts with the word show, so you can use tab to autocomplete in the cell to see the relevant methods.

In particular, look at what parameters are available and take a look at the instrument geometry.

Hide code cell content

 
instrument.show_parameters()

       l_min                      = 0.5          // Minimum simulated 
                                                     wavelength [AA] 
       l_max                      = 4.0          // Maximum simulated 
                                                     wavelength [AA] 
int    n_pulses                   = 1            // Number of simulated pulses
       guide_curve_deg            = 1.0          // 
       chopper_wavelength_center  = 2.5          // Center of wavelength band 
                                                     [AA] 
double frequency_multiplier       = 1            // [1] Chopper frequency as 
                                                     multiple of source frequency 
       detector_height            = 2.5          // 
       sample_radius              = 0.005        // 
       sample_height              = 0.02         // 
string sample_choice              = "sample_Si"  // 

# instrument.show_instrument(format='window')
instrument.show_diagram()
../_images/dac7d8fdbea1f88a9acae43069c52a30592cbc8be3bf76c882bb67589c6e6d1d.png ../_images/a0fd52de6bc36c336186fc8082906e028f6cbe842460e50430eab2be2774d754.png

Set the instrument settings to a reasonable value for the number of neutrons and MPI processes. This will be used in the following simulations.

instrument.settings(ncount=4.0e8, mpi=2, suppress_output=True, NeXus=True)

Run reference sample: Si#

# Set frequency multiplier to 3 for high resolution
instrument.set_parameters(sample_choice='"sample_Si"', frequency_multiplier=3, detector_height=1.5)
instrument.settings(output_path="output_sample_Si")

data_si = instrument.backengine()

plot(data_si, orders_of_mag=5)
../_images/46f48f6aa327aec5d3e54c5dea599fd764dfa200aa0ef3fd5b8b1e906c62cf7c.png

Run calibration sample: Vanadium#

instrument.set_parameters(sample_choice='"sample_Vanadium"')
instrument.settings(output_path="output_sample_vanadium")

data_vanadium = instrument.backengine()

plot(data_vanadium, orders_of_mag=5)
../_images/89a345d921706703efec23d2ad901be0e8a7169e322ddaaab0ffcaea3414078b.png

Run main sample: LBCO#

instrument.set_parameters(sample_choice='"sample_LBCO"')
instrument.settings(output_path="output_sample_LBCO")

data_sample_lbco = instrument.backengine()

plot(data_sample_lbco, orders_of_mag=5)
../_images/29c659a1f7d3152eadec12cb7f139170ba07ff26d7b6d684b3d6f974586c7628.png
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