yuanpeng / rmc_lammps_build_notes.md
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Build LAMMPS with RMCProfile
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We first need to compile
LAMMPS
separately to obtain the library fileliblammps.so.0
, together with a soft link fileliblammps.so
pointing to the library file. Once we have the compiledliblammps.so.0
library file, creating the soft link is as simple as running,ln -s liblammps.so.0 liblammps.so
yuanpeng / Filter_by_time_stamp_ZYP.py
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1 | # |
2 | # Filter_by_time_stamp_ZYP.py |
3 | # |
4 | # --------------------------------------------------------------------------- |
5 | # Script for filtering events based on time stamp |
6 | # --------------------------------------------------------------------------- |
7 | # |
8 | # ---------------------------- |
9 | # Yuanpeng Zhang @ Nov-10-2024 |
10 | # ---------------------------- |
yuanpeng / Filter_combined_ZYP.py
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1 | # |
2 | # Filter_combined_ZYP.py |
3 | # |
4 | # --------------------------------------------------------------------------- |
5 | # This is a combined script for event filter by either sample log or time. |
6 | # The two ways of conducting event filter is not compatible with each other |
7 | # and users can choose which one to use by setting the `filter_by_time` |
8 | # variable in the 'Input section' below to either `True` (to enable filter by |
9 | # time) or `False` (to enable filter by sample log). |
10 | # --------------------------------------------------------------------------- |
yuanpeng / rmc2cif_win_linux
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1 | data2config -noannotate -order [Ga P O] -supercell [1 1 1] -cif gapo4_xray.rmc6f |
yuanpeng / slurm_example.sh
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1 | #!/bin/bash |
2 | # |
3 | #SBATCH --job-name=MY_JOB_NAME |
4 | #SBATCH --output=MY_OUTPUT_NAME.out |
5 | # |
6 | #SBATCH --ntasks=1 |
7 | #SBATCH --cpus-per-task=4 |
8 | #SBATCH --time=1000000:00 |
9 | #SBATCH --mem-per-cpu=256 |
yuanpeng / snippet.py
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1 | if "-" in str(energy_theory[0]): |
2 | energy_theory = energy_theory[1:] |
3 | Percentage_theory = Percentage_theory[1:] |
yuanpeng / rebin_example.py
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1 | from mantid.simpleapi import * |
2 | import matplotlib.pyplot as plt |
3 | import numpy as np |
4 | |
5 | |
6 | def rebin_data(datax, datay, xmin, xmax, xbin): |
7 | """Rebin input data with specified binning params |
8 | |
9 | Parameters: |
10 | datax (numpy.ndarray): Input data X array |
yuanpeng / submit.slurm
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Run Jobs on NERSC
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First, download the RMCProfile package on Linux platform here and untar it somewhere in our home directory. Once logged onto NERSC from terminal, we can do this,
cd SOMEWHERE wget https://yr.iris-home.net/rmclinux -O RMCProfile_V6.7.9_Linux_64.tgz tar xzvf RMCProfile_V6.7.9_Linux_64.tgz
yuanpeng / si_mts.json
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1 | { |
2 | "Facility": "SNS", |
3 | "Instrument": "NOM", |
4 | "Title": "NOM_Si_640d_sgb_12_by_12", |
5 | "Sample": { |
6 | "Runs": "197077", |
7 | "Background": { |
8 | "Runs": "197075", |
9 | "Background": { |
10 | "Runs": "197073" |
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