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Thomas Aarholt thomasaarholt

  • University of Oxford
  • Oxford, UK
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View quantum_espresso_compilation
(/shared/users/thomasaar/py37) /shared/users/thomasaar/downloads/q-e-gpu-qe-gpu-6.4.1a1: ./configure --with-cuda=/opt/pgi/linux86-64/2018/cuda/9.2/bin --with-cuda-runtime=9.2 --with-cuda-cc=7.5 --enable-openmp --with-scalapack=no --prefix=/shared/users/thomasaar/compiled/q-e-gpu
checking build system type... x86_64-pc-linux-gnu
checking ARCH... x86_64
checking setting AR... ... /shared/users/thomasaar/py37/bin/x86_64-conda_cos6-linux-gnu-ar
checking setting ARFLAGS... ... ruv
checking whether the Fortran compiler works... yes
checking for Fortran compiler default output file name... a.out
checking for suffix of executables...
checking whether we are cross compiling... no
checking for suffix of object files... o
import numpy as np
x = np.array([500, 500, 500, 1000, 1000, 1000, 1500])
y = np.array([1,2,3,4,5,6,7])
data = np.stack([x,y]).T
means = []
stds = []
for xi in np.unique(data[:,0]):
thomasaarholt /
Last active Jun 17, 2019
Get DCFI shifts from a velox STEM file, then apply them to all the raw signals in the dataset.
# Script should be applied to a single Velox emd file, where the file contains a single DCFI dataset
# that has been applied to the detector signal that one wishes to apply to the other detector signals
# A good example is using DCFI on a DF image, and then applying this correction to HAADF, BF and ABF.
import hyperspy.api as hs
import json
import h5py
import numpy as np
def get_nonDCFI_signals(list_of_signals):
thomasaarholt / gist:5fc33ed59c846bbf64999a17324b1432
Created Jun 15, 2019 from attempted compiling of quantum espresso GPU version
View gist:5fc33ed59c846bbf64999a17324b1432
(/shared/users/thomasaar/py37) /shared/users/thomasaar/downloads/q-e-gpu/install: more
# @configure_input@
# compilation rules
.SUFFIXES : .o .c .f .f90
# most fortran compilers can directly preprocess c-like directives: use
# $(MPIF90) $(F90FLAGS) -c $<
import numpy as np
machineTime = {
'm1': {
thomasaarholt /
Last active Mar 4, 2019
Calculate the standard deviation of the gaussian distribution in defocus caused by chromatic aberration in the STEM
import matplotlib.pyplot as plt
import numpy as np
import sympy as sp
E0, dE, Cc = sp.symbols('E0, dE, C_c, ')
deltaZ_sigma = Cc*dE/E0#*2*sp.sqrt(2*sp.log(2))
zlp = 0.9
thomasaarholt / .profile
Created Feb 27, 2019
.profile used on Machine Learning Cluster
View .profile
GNU nano 2.5.3 File: /shared/users/thomasaar/.profile
PS1='$(pwd): '
echo 'Hello Thomas - edit PATH using "profile"'
# This is a comment
echo 'Enabling environment for pyprismatic'
export CPLUS_INCLUDE_PATH=/usr/local/cuda-10.0/include:$CPLUS_INCLUDE_PATH
export LD_LIBRARY_PATH=$HOME/fftw_gcc5_build/lib64:/usr/local/cuda-10.0/lib64:$HOME/prismatic_gcc5/lib:$LD_LIBRARY_PATH
export LIBRARY_PATH=$HOME/fftw_gcc5_build/lib64:/usr/local/cuda-10.0/lib64:$HOME/prismatic_gcc5/lib:$LIBRARY_PATH
thomasaarholt / .inputrc
Created Feb 27, 2019
Absolutely necessary .inputrc hotkeys for navigating in bash
View .inputrc
"\e[A": history-search-backward
"\e[B": history-search-forward
"\e[C": forward-char
"\e[D": backward-char
thomasaarholt /
Last active Mar 11, 2019
Add colorbar next to image
from mpl_toolkits.axes_grid1 import make_axes_locatable
def colorbar(mappable):
"mappable is img = plt.imshow()"
ax = mappable.axes
fig = ax.figure
divider = make_axes_locatable(ax)
cax = divider.append_axes("right", size="5%", pad=0.05)
cax.aname = 'colorbar'
return fig.colorbar(mappable, cax=cax)
thomasaarholt /
Created Feb 26, 2019
Convert Windows filepath to Ubuntu on Windows filepath
from pathlib import Path
def win2lin(rpath: r"C:\Users..."):
path = rpath.replace("\\", "/").replace(":/", "/")
drive = path[0]
path = Path("/mnt/") / Path(drive.lower() + path[1:])
return path
### Example:
# >>> win2lin(r"C:\Users\myuser\Documents")
# PosixPath('/mnt/c/Users/myuser/Documents')
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