cbpygit

# This is a work-around around Google Slides' limitation to 1600x1600 pixel images which make full-screen graphics look pixelated
# See this thread: https://support.google.com/docs/thread/9031600/how-can-i-stop-google-slides-applying-their-extreme-image-compression-and-resampling?hl=en

# requires ImageMagick
# Run on image of e.g. 3840x2160 size for 16:9 4K
convert YOUR-IMAGE-NAME.png -crop 3x2-0-0@ +repage +adjoin YOUR-IMAGE-NAME-tile-%d.png

# This create 2x3 = 6 tiles that can be pasted into Google Slides. They can be grouped and act as one single image which renders sharply.

cbpygit

from functools import wraps


def allow_simulate_exception(exception_class=Exception):
    def _allow_simulate_exception(method):
        """Decorator that allows to raise an exception """

        @wraps(method)
        def _raise_exception_if_method_name_fits(self, *method_args,
                                                 **method_kwargs):

cbpygit

from cachetools import cached, LRUCache, Cache
from cachetools.keys import hashkey
from time import sleep
​
class LRUCacheEnsemble:
    
    def __init__(self, maxsize_ensemble, maxsize_caches):
        self.maxsize_ensemble = maxsize_ensemble
        self.maxsize_caches = maxsize_caches
        self.caches = LRUCache(maxsize=maxsize_ensemble)

cbpygit

import numpy as np

def find_nearest(array, value):
    array = np.asarray(array)
    idx = (np.abs(array - value)).argmin()
    return idx, array[idx]

cbpygit

import pypmj as jpy

class SimulationSetClean(jpy.SimulationSet):
    """ Extends `SimulationSet` and simply forces to start with an empty
    H5-store each time it is initialized. 

    """
    
    def __init__(self, *args, **kwargs):
        self._start_withclean_H5_store = True