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import matplotlib as mpl
import matplotlib.pyplot as plt

# whatever the data is
a = np.arange(5, 15)

# get colors for data from colormap (viridis in this case)
norm = mpl.colors.Normalize(vmin=a.min(), vmax=a.max())
rgba_color = plt.cm.viridis([norm(v) for v in a]) 

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find . *.ipynb -maxdepth 0 -type f -exec jupyter nbconvert --ExecutePreprocessor.timeout=-1 --to notebook {} --execute --output {} \;

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{
	"name": "Default color scheme for shell prompts",
	"groups": {
		"hostname":         { "fg": "brightyellow", "bg": "mediumorange", "attrs": [] },
		"environment":      { "fg": "white", "bg": "darkestgreen", "attrs": [] },
		"virtualenv":      { "fg": "gray2", "bg": "solarized:green", "attrs": [] },
		"mode":             { "fg": "darkestgreen", "bg": "brightgreen", "attrs": ["bold"] },
		"attached_clients": { "fg": "white", "bg": "darkestgreen", "attrs": [] },
		"gitstatus":                 { "fg": "gray8",           "bg": "gray2", "attrs": [] },
	    "gitstatus_branch":          { "fg": "gray8",           "bg": "gray2", "attrs": [] },

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from pathlib import Path

import pandas as pd


@pd.api.extensions.register_series_accessor("path")
@pd.api.extensions.register_index_accessor("path")
class PathAccessor:
    def __init__(self, pandas_obj):
        self._validate(pandas_obj)

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import os
import time
from itertools import repeat
import random
from deap import creator, base, tools, algorithms

import numpy as np
from joblib import Parallel, delayed
from joblib import dump, load

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from collections import Counter, deque
from copy import copy
from dataclasses import dataclass, asdict
import datetime
from itertools import islice
import json
import os
from pathlib import Path
import sys
import time