thomasaarholt

"\e[A": history-search-backward
"\e[B": history-search-forward
"\e[C": forward-char
"\e[D": backward-char

thomasaarholt

Using Jupyter notebook remotely via a ssh tunnel.

Especially good for running on headless devices, such as supercomputers or clusters.

Remotely:

# remote_port should be value between 8888 and 9000
jupyter notebook --no-browser --port=remote_port

Locally, new terminal window

bencholmes

function X = forceFFTSymmetry(X)
% forceFFTSymmetry  A function to force conjugate symmetry on an FFT such that when an
% IFFT is performed the result is a real signal.

% The function has been written to replace MATLAB's ifft(X,'symmetric'), as this function
% is not compatible with MATLAB Coder.
  
% Licensed under Creative Commons Zero (CC0) so use freely.

XStartFlipped = fliplr(X(2:floor(end/2)));

thomasaarholt

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

'''
Python script to load any format supported by hyperspy directly into GMS
Must be copied and pasted into Gatan DigitalMicrograph (aka Gatan Microscopy Suite) version 3.4+
Call by `load_img(filepath)` at the bottom of the script. Can not be called outside of GMS.
Does not automatically convert the data type to EELS or EDS
Written by Thomas Aarholt, see https://gist.github.com/thomasaarholt/fccf06d56ff84cf76345b44dae30871e for newer versions
Feedback and forks are very welcome.
MUST: First import of hyperspy (or scipy) must NOT be run with "Execute on background thread" checked. One
can then swap to background thread and rerun.
v. 0.3: Added delete statements to ensure python objects don't stay in memory.

wassname

"""Another way, note this one will load the whole array into memory ."""
from keras.preprocessing.image import ImageDataGenerator
import h5py
from keras.utils.io_utils import HDF5Matrix
seed=0
batch_size=32

# we create two instances with the same arguments
data_gen_args = dict( 
    rotation_range=90.,

bluepichu

from __future__ import annotations
from collections import defaultdict

from os import path
from typing import DefaultDict, List, NamedTuple, Optional, Sequence, Set, Tuple, cast
import requests
import re
from copy import copy
from pyrsistent import m, s, v, PMap, PSet, PVector

thomasaarholt

echo 'Hello Thomas - edit PATH using "profile"'

alias ls="ls --color"

alias cd..='cd ../'                         # Go back 1 directory level (for fast typers)
alias cd...='cd ../../'
alias ..='cd ../'                           # Go back 1 directory level
alias ...='cd ../../'                       # Go back 2 directory levels
alias .3='cd ../../../'                     # Go back 3 directory levels
alias .4='cd ../../../../'                  # Go back 4 directory levels

andrewjesaitis

import matplotlib as mpl
num_colors = len(values)
cm = mpl.cm.get_cmap(name='YlGnBu_r')
currentColors = [cm(1.*i/num_colors) for i in range(num_colors)]

zonca

import numpy as np

def rebin(a, new_shape):
    """
    Resizes a 2d array by averaging or repeating elements, 
    new dimensions must be integral factors of original dimensions

    Parameters
    ----------
    a : array_like