thomasaarholt

branch () {
    branches=$(git for-each-ref --sort=-committerdate refs/heads/ --format='%(color:cyan)%(refname:short)|%(color:bold green)%(committerdate:relative)|%(color:magenta)%(authorname)%(color:reset)' --color=always|column -ts'|') &&
    branch=$(echo "$branches" | fzf --multi --ansi --height=20%)
    if [ -z "${branch}" ]; 
        then return 0 
        else git switch $(echo "$branch" | sed "s/ .*//")
    fi
}

thomasaarholt

import numpy as np
import matplotlib
import matplotlib.pyplot as plt
Arc = matplotlib.patches.Arc

def halfangle(a, b):
    "Gets the middle angle between a and b, when increasing from a to b"
    if b < a:
        b += 360
    return (a + b)/2 % 360

thomasaarholt

def autoscale(ax=None, axis='y', margin=0.1):
    '''Autoscales the x or y axis of a given matplotlib ax object
    to fit the margins set by manually limits of the other axis,
    with margins in fraction of the width of the plot
    
    Defaults to current axes object if not specified.
    '''
    import matplotlib.pyplot as plt
    import numpy as np
    if ax is None:

thomasaarholt

venv () {
    RED='\033[0;31m'
    NC='\033[0m' # No Color
    # create virtualenv
    if [ ! -d .venv ] # if venv does not exist already
    then
        python -m venv .venv --system-site-packages
    else
        echo -e "${RED}.venv${NC} already exists!"
        return 0

thomasaarholt

def train_test_split(
    df: pl.DataFrame, train_fraction: float = 0.75
) -> Tuple[pl.DataFrame, pl.DataFrame]:
    """Split polars dataframe into two sets.

    Args:
        df (pl.DataFrame): Dataframe to split
        train_fraction (float, optional): Fraction that goes to train. Defaults to 0.75.

thomasaarholt

# must not use gcc version > 10
module load CUDA/11.0 CMake/3.21.1-GCCcore-11.2.0

# Clone with recursive! Otherwise you get dmlc error later on!
git clone --recursive https://github.com/dmlc/xgboost
cd xgboost/python-package

# clean out any old build files that may break things if try to recompile
rm -rf build

thomasaarholt

module load CUDA/11.0 CMake/3.21.1-GCCcore-11.2.0 Boost/1.74.0-GCC-10.2.0

pip install lightgbm --install-option=--gpu

# If running from notebook, ensure that the following contains Boost:
# import os
# os.environ["LD_LIBRARY_PATH"].split(":")

thomasaarholt

# From a directory with a Dockerfile
# Example Dockerfile with "Dockerfile" as filename
FROM python:3.10-slim-buster
RUN pip install numpy


# Then, run the following

docker build -t your_image_name .

thomasaarholt

from pprint import pprint
import temscript as ts
from math import pi

dwelltime = 1e-5 # seconds

tem = ts.Microscope()
illumination = tem._tem_illumination
instrument = ts.GetInstrument()

thomasaarholt

import matplotlib.pyplot as plt

def save(filepath="image.png", fig=None):
    '''Save the current image with no whitespace
    Example filepath: "myfig.png" or r"C:\myfig.pdf" 
    Based on answers from https://stackoverflow.com/questions/11837979/
    '''
    import matplotlib.pyplot as plt
    if not fig:
        fig = plt.gcf()